fix: apply pnpm overrides for HIGH severity vulnerabilities

- Add immutable >=5.1.5 override to openmemory/ui (CVE-2026-29063)
- Add langsmith >=0.6.0 override to openclaw (CVE-2026-32460)
- Add langsmith >=0.6.0 override to mem0-ts (CVE-2026-32460)

Fixes #5318, #5320

.claude-plugin/marketplace.json

@@ -12,7 +12,7 @@
       "name": "mem0",
       "source": "./mem0-plugin",
       "description": "Mem0 memory layer for AI applications. Add persistent memory, personalization, and semantic search to Claude workflows.",
-      "version": "0.1.1"
+      "version": "0.2.8"
     }
   ]
 }

.codex-plugin/marketplace.json

@@ -0,0 +1,20 @@
+{
+  "name": "mem0-plugins",
+  "interface": {
+    "displayName": "Mem0 Plugins"
+  },
+  "plugins": [
+    {
+      "name": "mem0",
+      "source": {
+        "source": "local",
+        "path": "./mem0-plugin"
+      },
+      "policy": {
+        "installation": "AVAILABLE",
+        "authentication": "ON_INSTALL"
+      },
+      "category": "Productivity"
+    }
+  ]
+}

.cursor-plugin/marketplace.json

@@ -12,7 +12,7 @@
       "name": "mem0",
       "source": "./mem0-plugin",
       "description": "Mem0 memory layer for AI applications. Add persistent memory, personalization, and semantic search.",
-      "version": "0.1.1"
+      "version": "0.2.8"
     }
   ]
 }

.github/workflows/ci.yml

@@ -3,18 +3,7 @@ name: ci
 on:
   push:
     branches: [main]
-    paths:
-      - 'mem0/**'
-      - 'tests/**'
-      - 'embedchain/**'
-      - '.github/workflows/**'
-      - 'pyproject.toml'
   pull_request:
-    paths:
-      - 'mem0/**'
-      - 'tests/**'
-      - 'embedchain/**'
-      - 'pyproject.toml'
 
 jobs:
   changelog_check:
@@ -60,9 +49,8 @@ jobs:
     runs-on: ubuntu-latest
     outputs:
       mem0_changed: ${{ steps.filter.outputs.mem0 }}
-      embedchain_changed: ${{ steps.filter.outputs.embedchain }}
     steps:
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
     - uses: dorny/paths-filter@v2
       id: filter
       with:
@@ -70,25 +58,28 @@ jobs:
           mem0:
             - 'mem0/**'
             - 'tests/**'
-            - '.github/workflows/**'
+            - '.github/workflows/ci.yml'
             - 'pyproject.toml'
-          embedchain:
-            - 'embedchain/**'
 
   build_mem0:
     needs: check_changes
-    if: needs.check_changes.outputs.mem0_changed == 'true'
     runs-on: ubuntu-latest
     strategy:
       matrix:
         python-version: ["3.10", "3.11", "3.12"]
     steps:
-      - uses: actions/checkout@v3
+      - name: Skip — no relevant changes
+        if: needs.check_changes.outputs.mem0_changed != 'true'
+        run: echo "No changes in mem0/, tests/, pyproject.toml, or ci.yml — skipping"
+      - uses: actions/checkout@v4
+        if: needs.check_changes.outputs.mem0_changed == 'true'
       - name: Set up Python ${{ matrix.python-version }}
+        if: needs.check_changes.outputs.mem0_changed == 'true'
         uses: actions/setup-python@v4
         with:
           python-version: ${{ matrix.python-version }}
       - name: Clean up disk space
+        if: needs.check_changes.outputs.mem0_changed == 'true'
         run: |
           df -h
           sudo rm -rf /usr/share/dotnet /usr/local/lib/android /opt/ghc /opt/hostedtoolcache/CodeQL
@@ -96,61 +87,27 @@ jobs:
           sudo docker builder prune -a
           df -h
       - name: Install Hatch
+        if: needs.check_changes.outputs.mem0_changed == 'true'
         run: pip install hatch
       - name: Load cached venv
+        if: needs.check_changes.outputs.mem0_changed == 'true'
         id: cached-hatch-dependencies
         uses: actions/cache@v3
         with:
           path: .venv
           key: venv-mem0-${{ runner.os }}-${{ hashFiles('**/pyproject.toml') }}
       - name: Install GEOS Libraries
+        if: needs.check_changes.outputs.mem0_changed == 'true'
         run: sudo apt-get update && sudo apt-get install -y libgeos-dev
       - name: Install dependencies
+        if: needs.check_changes.outputs.mem0_changed == 'true' && steps.cached-hatch-dependencies.outputs.cache-hit != 'true'
         run: |
           pip install --upgrade pip
           pip install -e ".[test,graph,vector_stores,llms,extras]"
           pip install ruff
-        if: steps.cached-hatch-dependencies.outputs.cache-hit != 'true'
       - name: Run Linting
+        if: needs.check_changes.outputs.mem0_changed == 'true'
         run: make lint
       - name: Run tests and generate coverage report
+        if: needs.check_changes.outputs.mem0_changed == 'true'
         run: make test
-
-  build_embedchain:
-    needs: check_changes
-    if: needs.check_changes.outputs.embedchain_changed == 'true'
-    runs-on: ubuntu-latest
-    strategy:
-      matrix:
-        python-version: ["3.9", "3.10", "3.11", "3.12"]
-    steps:
-      - uses: actions/checkout@v3
-      - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v4
-        with:
-          python-version: ${{ matrix.python-version }}
-      - name: Install Hatch
-        run: pip install hatch
-      - name: Load cached venv
-        id: cached-hatch-dependencies
-        uses: actions/cache@v3
-        with:
-          path: .venv
-          key: venv-embedchain-${{ runner.os }}-${{ hashFiles('**/pyproject.toml') }}
-      - name: Install dependencies
-        run: cd embedchain && make install_all
-        if: steps.cached-hatch-dependencies.outputs.cache-hit != 'true'
-      - name: Run Formatting
-        run: |
-          mkdir -p embedchain/.ruff_cache && chmod -R 777 embedchain/.ruff_cache
-          cd embedchain && hatch run format
-      - name: Lint with ruff
-        run: cd embedchain && make lint
-      - name: Run tests and generate coverage report
-        run: cd embedchain && make coverage
-      - name: Upload coverage reports to Codecov
-        uses: codecov/codecov-action@v3
-        with:
-          file: coverage.xml
-        env:
-          CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}

.github/workflows/opencode-plugin-cd.yml

@@ -0,0 +1,44 @@
+name: Publish @mem0/opencode-plugin 📦 to npm
+
+on:
+  release:
+    types: [published]
+
+jobs:
+  build-n-publish:
+    name: Build and publish @mem0/opencode-plugin 📦 to npm
+    if: startsWith(github.event.release.tag_name, 'opencode-v')
+    runs-on: ubuntu-latest
+    permissions:
+      id-token: write
+    defaults:
+      run:
+        working-directory: mem0-plugin/.opencode-plugin
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Install Bun
+        uses: oven-sh/setup-bun@v2
+        with:
+          bun-version: latest
+
+      - name: Set up Node.js
+        uses: actions/setup-node@v4
+        with:
+          node-version: '22'
+          registry-url: 'https://registry.npmjs.org'
+
+      - name: Install dependencies
+        run: bun install --frozen-lockfile
+
+      - name: Build
+        run: bun run build
+
+      - name: Publish to npm
+        run: |
+          if [ "${{ github.event.release.prerelease }}" = "true" ]; then
+            PREID=$(node -p "require('./package.json').version.split('-')[1].split('.')[0]")
+            npx npm@latest publish --provenance --access public --tag "$PREID"
+          else
+            npx npm@latest publish --provenance --access public
+          fi

.github/workflows/opencode-plugin-checks.yml

@@ -0,0 +1,40 @@
+name: opencode-plugin checks
+
+on:
+  workflow_dispatch:
+  push:
+    branches: [main]
+    paths:
+      - 'mem0-plugin/.opencode-plugin/**'
+      - '.github/workflows/opencode-plugin-checks.yml'
+  pull_request:
+    paths:
+      - 'mem0-plugin/.opencode-plugin/**'
+      - '.github/workflows/opencode-plugin-checks.yml'
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+    defaults:
+      run:
+        working-directory: mem0-plugin/.opencode-plugin
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Install Bun
+        uses: oven-sh/setup-bun@v2
+        with:
+          bun-version: latest
+
+      - name: Install dependencies
+        run: bun install --frozen-lockfile
+
+      - name: Type check
+        run: bun run type-check
+
+      - name: Build
+        run: bun run build
+
+      - name: Verify dist output exists
+        run: |
+          test -f dist/index.js || (echo "Build output missing: dist/index.js" && exit 1)

.gitignore

@@ -170,7 +170,6 @@ cython_debug/
 # Database
 db
 test-db
-!embedchain/embedchain/core/db/
 
 .vscode
 .idea/

AGENTS.md

@@ -27,13 +27,12 @@ This is a **polyglot monorepo** containing Python and TypeScript packages, CLIs,
 | `server/` | FastAPI REST server for self-hosted Mem0 (Docker: FastAPI + PostgreSQL/pgvector + Neo4j) |
 | `openmemory/` | Self-hosted memory platform — `api/` (FastAPI + Alembic + MCP server) and `ui/` (Next.js 15 + React 19) |
 | `mem0-plugin/` | AI editor plugins (Claude Code, Cursor, Codex) — MCP server connection, lifecycle hooks, skills |
-| `skills/` | Claude Code skill definitions — `mem0/`, `mem0-cli/`, `mem0-vercel-ai-sdk/` |
+| `skills/` | Claude Code skill definitions. Reference skills (SDK knowledge, always-on): `mem0/`, `mem0-cli/`, `mem0-vercel-ai-sdk/`. Pipeline skills (run on demand): `mem0-integrate/`, `mem0-test-integration/` |
 | `docs/` | Documentation site (Mintlify) |
 | `tests/` | Python SDK tests (pytest) |
 | `evaluation/` | Benchmarking framework — LOCOMO evals, experiment runner, score generation |
 | `examples/` | Sample projects — demo apps, Chrome extension, multi-agent patterns |
 | `cookbooks/` | Jupyter notebooks — customer support chatbot, AutoGen integration |
-| `embedchain/` | Legacy Embedchain RAG framework (maintained separately, Poetry-based) |
 | `pr-reviews/` | Pull request review materials |
 | `scripts/` | Repo-wide utility scripts (e.g., `check-llms-txt-coverage.py` for docs/llms.txt sync) |
 
@@ -330,7 +329,7 @@ make run-openai                    # OpenAI comparison
   - Root SDK: line length **120**
   - Python CLI: line length **100** with extended rule set (UP, B, SIM, RUF)
 - **isort** with `profile = "black"` for import sorting.
-- Ruff excludes `embedchain/` and `openmemory/` from root config.
+- Ruff excludes `openmemory/` from root config.
 
 ### TypeScript Conventions
 
@@ -387,7 +386,9 @@ Model Context Protocol support in multiple places:
 ### Plugin & Skills System
 
 - `mem0-plugin/` provides integrations for Claude Code, Cursor, and Codex via MCP server connections and lifecycle hooks for automatic memory capture.
-- `skills/` contains structured skill definitions for AI agents, covering SDK usage, CLI workflows, and Vercel AI SDK patterns.
+- `skills/` contains structured skill definitions for AI agents, split into two categories:
+  - **Reference skills** (always-on SDK knowledge): `mem0` (Python + TS SDKs, framework integrations), `mem0-cli` (terminal workflows), `mem0-vercel-ai-sdk` (Vercel AI provider).
+  - **Pipeline skills** (run on demand): `mem0-integrate` wires Mem0 into an existing repo via a TDD pipeline; `mem0-test-integration` verifies what the integrator produced on the same branch. The two are loosely coupled via `.mem0-integration/` artifacts.
 
 ### Adding a New Provider
 
@@ -412,7 +413,7 @@ To add a new LLM, embedding, vector store, or reranker provider:
 | Python CLI | `cli-python-ci.yml` | Push to `cli/python/`, PRs, manual | Ruff lint + pytest + hatch build on Python 3.10, 3.11, 3.12 |
 | Node CLI | `cli-node-ci.yml` | Push to `cli/node/`, PRs, manual | Biome lint + tsc + vitest + tsup build on Node 20, 22 |
 | OpenClaw | `openclaw-checks.yml` | Push to `openclaw/`, PRs, manual | tsc + vitest (with Codecov) + tsup build on Node 20, 22 |
-| Embedchain | `ci.yml` (shared) | PRs on `embedchain/` | Ruff + pytest + coverage on Python 3.9–3.12 |
+| OpenCode Plugin | `opencode-plugin-checks.yml` | Push to `mem0-plugin/.opencode-plugin/`, PRs, manual | Bun: tsc type-check + build + dist artifact check |
 
 ### CD Workflows (automated publishing)
 
@@ -424,6 +425,7 @@ To add a new LLM, embedding, vector store, or reranker provider:
 | Node CLI | `cli-node-cd.yml` | `cli-node-v*` | npm (`@mem0/cli`) |
 | Vercel AI SDK | `vercel-ai-cd.yml` | `vercel-ai-v*` | npm (`@mem0/vercel-ai-provider`) |
 | OpenClaw | `openclaw-cd.yml` | `openclaw-v*` | npm (`@mem0/openclaw-mem0`) |
+| OpenCode Plugin | `opencode-plugin-cd.yml` | `opencode-v*` | npm (`@mem0/opencode-plugin`) |
 
 - All publishing uses **OIDC trusted publishing** — no tokens or secrets required.
 - First publish of a new npm package must be done manually; OIDC works for subsequent versions.
@@ -574,7 +576,6 @@ N/A
 - Modify CI/CD workflows without explicit approval.
 - Add new Python dependencies to the core `dependencies` list in `pyproject.toml` without discussion — use optional dependency groups instead.
 - Commit `.env` files, API keys, or credentials.
-- Modify `embedchain/` unless specifically working on that package — it has its own build system (Poetry).
 - Skip pre-commit hooks.
 - Use npm or yarn in TypeScript packages — this repo uses pnpm exclusively.
 - Use `require()` for imports in TypeScript — use ES module `import` syntax.

MIGRATION_GUIDE_v1.0.md

@@ -1,221 +0,0 @@
-# Migration Guide: Upgrading to mem0 1.0.0
-
-## TL;DR
-
-**What changed?** We simplified the API by removing confusing version parameters. Now everything returns a consistent format: `{"results": [...]}`.
-
-**What you need to do:**
-1. Upgrade: `pip install mem0ai==1.0.0`
-2. Remove `version` and `output_format` parameters from your code
-3. Update response handling to use `result["results"]` instead of treating responses as lists
-
-**Time needed:** ~5-10 minutes for most projects
-
----
-
-## Quick Migration Guide
-
-### 1. Install the Update
-
-```bash
-pip install mem0ai==1.0.0
-```
-
-### 2. Update Your Code
-
-**If you're using the Memory API:**
-
-```python
-# Before
-memory = Memory(config=MemoryConfig(version="v1.1"))
-result = memory.add("I like pizza")
-
-# After
-memory = Memory()  # That's it - version is automatic now
-result = memory.add("I like pizza")
-```
-
-**If you're using the Client API:**
-
-```python
-# Before
-client.add(messages, output_format="v1.1")
-client.search(query, version="v2", output_format="v1.1")
-
-# After
-client.add(messages)  # Just remove those extra parameters
-client.search(query)
-```
-
-### 3. Update How You Handle Responses
-
-All responses now use the same format: a dictionary with `"results"` key.
-
-```python
-# Before - you might have done this
-result = memory.add("I like pizza")
-for item in result:  # Treating it as a list
-    print(item)
-
-# After - do this instead
-result = memory.add("I like pizza")
-for item in result["results"]:  # Access the results key
-    print(item)
-
-# Graph relations (if you use them)
-if "relations" in result:
-    for relation in result["relations"]:
-        print(relation)
-```
-
----
-
-## Enhanced Message Handling
-
-The platform client (MemoryClient) now supports the same flexible message formats as the OSS version:
-
-```python
-from mem0 import MemoryClient
-
-client = MemoryClient(api_key="your-key")
-
-# All three formats now work:
-
-# 1. Single string (automatically converted to user message)
-client.add("I like pizza", user_id="alice")
-
-# 2. Single message dictionary
-client.add({"role": "user", "content": "I like pizza"}, user_id="alice")
-
-# 3. List of messages (conversation)
-client.add([
-    {"role": "user", "content": "I like pizza"},
-    {"role": "assistant", "content": "I'll remember that!"}
-], user_id="alice")
-```
-
-### Async Mode Configuration
-
-The `async_mode` parameter now defaults to `True` but can be configured:
-
-```python
-# Default behavior (async_mode=True)
-client.add(messages, user_id="alice")
-
-# Explicitly set async mode
-client.add(messages, user_id="alice", async_mode=True)
-
-# Disable async mode if needed
-client.add(messages, user_id="alice", async_mode=False)
-```
-
-**Note:** `async_mode=True` provides better performance for most use cases. Only set it to `False` if you have specific synchronous processing requirements.
-
----
-
-## That's It!
-
-For most users, that's all you need to know. The changes are:
-- ✅ No more `version` or `output_format` parameters
-- ✅ Consistent `{"results": [...]}` response format
-- ✅ Cleaner, simpler API
-
----
-
-## Common Issues
-
-**Getting `KeyError: 'results'`?**
-
-Your code is still treating the response as a list. Update it:
-```python
-# Change this:
-for memory in response:
-
-# To this:
-for memory in response["results"]:
-```
-
-**Getting `TypeError: unexpected keyword argument`?**
-
-You're still passing old parameters. Remove them:
-```python
-# Change this:
-client.add(messages, output_format="v1.1")
-
-# To this:
-client.add(messages)
-```
-
-**Seeing deprecation warnings?**
-
-Remove any explicit `version="v1.0"` from your config:
-```python
-# Change this:
-memory = Memory(config=MemoryConfig(version="v1.0"))
-
-# To this:
-memory = Memory()
-```
-
----
-
-## What's New in 1.0.0
-
-- **Better vector stores:** Fixed OpenSearch and improved reliability across all stores
-- **Cleaner API:** One way to do things, no more confusing options
-- **Enhanced GCP support:** Better Vertex AI configuration options
-- **Flexible message input:** Platform client now accepts strings, dicts, and lists (aligned with OSS)
-- **Configurable async_mode:** Now defaults to `True` but users can override if needed
-
----
-
-## Need Help?
-
-- Check [GitHub Issues](https://github.com/mem0ai/mem0/issues)
-- Read the [documentation](https://docs.mem0.ai/)
-- Open a new issue if you're stuck
-
----
-
-## Advanced: Configuration Changes
-
-**If you configured vector stores with version:**
-
-```python
-# Before
-config = MemoryConfig(
-    version="v1.1",
-    vector_store=VectorStoreConfig(...)
-)
-
-# After
-config = MemoryConfig(
-    vector_store=VectorStoreConfig(...)
-)
-```
-
----
-
-## Testing Your Migration
-
-Quick sanity check:
-
-```python
-from mem0 import Memory
-
-memory = Memory()
-
-# Add should return a dict with "results"
-result = memory.add("I like pizza", user_id="test")
-assert "results" in result
-
-# Search should return a dict with "results"
-search = memory.search("food", user_id="test")
-assert "results" in search
-
-# Get all should return a dict with "results"
-all_memories = memory.get_all(user_id="test")
-assert "results" in all_memories
-
-print("✅ Migration successful!")
-```

README.md

@@ -47,7 +47,7 @@
 | Benchmark | Old | New  | Tokens  | Latency p50  |
 | --- | --- | --- | --- | --- |
 | **LoCoMo** | 71.4 | **91.6** | 7.0K  | 0.88s  |
-| **LongMemEval** | 67.8 | **93.4** | 6.8K  | 1.09s  |
+| **LongMemEval** | 67.8 | **94.8** | 6.8K  | 1.09s  |
 | **BEAM (1M)** | — | **64.1** | 6.7K  | 1.00s  |
 | **BEAM (10M)** | — | **48.6** | 6.9K  | 1.05s  |
 
@@ -58,12 +58,13 @@ All benchmarks run on the same production-representative model stack. Single-pas
 - **Agent-generated facts are first-class** -- when an agent confirms an action, that information is now stored with equal weight.
 - **Entity linking** -- entities are extracted, embedded, and linked across memories for retrieval boosting.
 - **Multi-signal retrieval** -- semantic, BM25 keyword, and entity matching scored in parallel and fused.
+- **Temporal Reasoning** -- time-aware retrieval that ranks the right dated instance for queries about current state, past events, and upcoming plans.
 
 See the [migration guide](https://docs.mem0.ai/migration/oss-v2-to-v3) for upgrade instructions. The [evaluation framework](https://github.com/mem0ai/memory-benchmarks) is open-sourced so anyone can reproduce the numbers.
 
 ## Research Highlights
 - **91.6 on LoCoMo** -- +20 points over the previous algorithm
-- **93.4 on LongMemEval** -- +26 points, with +53.6 on assistant memory recall
+- **94.8 on LongMemEval** -- +27 points, with +53.6 on assistant memory recall
 - **64.1 on BEAM (1M)** -- production-scale memory evaluation at 1M tokens
 - [Read the full paper](https://mem0.ai/research)
 
@@ -85,6 +86,26 @@ See the [migration guide](https://docs.mem0.ai/migration/oss-v2-to-v3) for upgra
 
 ## 🚀 Quickstart Guide <a name="quickstart"></a>
 
+### Sign up as an agent
+
+AI agents can mint a working Mem0 API key in under five seconds — no email, no dashboard, no OTP. Four commands end-to-end:
+
+```bash
+# 1. Install
+npm install -g @mem0/cli      # or: pip install mem0-cli
+
+# 2. Sign up as an agent (replace `claude-code` with your name)
+mem0 init --agent --agent-caller claude-code
+
+# 3. Add a memory
+mem0 add "I am using mem0"
+
+# 4. Search
+mem0 search "am I using mem0"
+```
+
+The human owner can claim the account later with `mem0 init --email <their-email>` — same key, memories preserved. Full guide: [Sign up as an agent](https://docs.mem0.ai/platform/agent-signup).
+
 | | Library | Self-Hosted Server | Cloud Platform |
 |---|---------|-------------------|----------------|
 | **Best for** | Testing, prototyping | Teams running on their own infrastructure | Zero-ops production use |
@@ -132,6 +153,7 @@ See the [self-hosted docs](https://docs.mem0.ai/open-source/overview) for config
 
 1. Sign up on [Mem0 Platform](https://app.mem0.ai?utm_source=oss&utm_medium=readme)
 2. Embed the memory layer via SDK or API keys
+3. Using hosted Qdrant vectors? See the [Platform migration guide](https://docs.mem0.ai/migration/oss-to-platform) to import them into Mem0 Platform.
 
 ### CLI
 
@@ -147,6 +169,27 @@ mem0 search "What does Alice prefer?" --user-id alice
 
 See the [CLI documentation](https://docs.mem0.ai/platform/cli) for the full command reference.
 
+### Agent Skills
+
+Teach your AI coding assistant (Claude Code, Codex, Cursor, Windsurf, OpenCode, OpenClaw, and any tool that supports the skills standard) how to build with Mem0. Two categories:
+
+**Reference skills — always on** (SDK knowledge loaded into the assistant's context):
+
+```bash
+npx skills add https://github.com/mem0ai/mem0 --skill mem0
+npx skills add https://github.com/mem0ai/mem0 --skill mem0-cli
+npx skills add https://github.com/mem0ai/mem0 --skill mem0-vercel-ai-sdk
+```
+
+**Pipeline skills — run on demand** (execute an end-to-end workflow in an existing repo):
+
+```bash
+npx skills add https://github.com/mem0ai/mem0 --skill mem0-integrate
+npx skills add https://github.com/mem0ai/mem0 --skill mem0-test-integration
+```
+
+Use `/mem0-integrate` to wire Mem0 into an existing repo via a test-first pipeline, then `/mem0-test-integration` to verify. See the [skills catalog](./skills/) or [Vibecoding with Mem0](https://docs.mem0.ai/vibecoding) for the full picture.
+
 ### Basic Usage
 
 Mem0 requires an LLM to function, with `gpt-5-mini` from OpenAI as the default. However, it supports a variety of LLMs; for details, refer to our [Supported LLMs documentation](https://docs.mem0.ai/components/llms/overview).

cli/cli-spec.json

@@ -503,7 +503,7 @@
     },
     {
       "name": "init",
-      "description": "Setup wizard for mem0 CLI. Supports email login (--email) or manual API key (--api-key).",
+      "description": "Setup wizard for mem0 CLI. Supports Agent Mode bootstrap (--agent), email login (--email), or manual API key (--api-key).",
       "usage": "mem0 init [OPTIONS]",
       "needsBackend": false,
       "needsConfig": false,
@@ -516,7 +516,9 @@
         { "name": "user-id", "flags": ["-u", "--user-id"], "type": "string", "default": null, "help": "Default user ID (skip prompt)." },
         { "name": "email", "flags": ["--email"], "type": "string", "default": null, "help": "Login via email verification code." },
         { "name": "code", "flags": ["--code"], "type": "string", "default": null, "help": "Verification code (use with --email for non-interactive login)." },
-        { "name": "force", "flags": ["--force"], "type": "boolean", "default": false, "help": "Overwrite existing config without confirmation." }
+        { "name": "force", "flags": ["--force"], "type": "boolean", "default": false, "help": "Overwrite existing config without confirmation." },
+        { "name": "agent", "flags": ["--agent"], "type": "boolean", "default": false, "help": "Bootstrap an unattended Agent Mode account (no email required)." },
+        { "name": "source", "flags": ["--source"], "type": "string", "default": null, "help": "Channel attribution for signup (e.g. github, hn, ph)." }
       ]
     },
     {

cli/node/CHANGELOG.md

@@ -0,0 +1,36 @@
+# Changelog
+
+All notable changes to `@mem0/cli` are documented here.
+
+The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
+and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
+
+## [0.2.7] — 2026-05-20
+
+### Added
+
+- `mem0 whoami` — print the active agent's `default_user_id` (the AGENTRUSH
+  leaderboard identifier). Reads from local config, no network call.
+- `mem0 agent-rush <add | search>` — subcommand group that wraps the new
+  `/v1/agent-rush/` platform endpoints for the 7-day AGENTRUSH game. Project
+  routing is implicit (resolved server-side); no flags exposed. Pretty-prints
+  platform error codes into actionable hints (e.g. `agentrush_search_first`
+  → "Run 3 'mem0 agent-rush search' commands before adding.").
+- PII safety prompt on first `mem0 agent-rush add`. Interactive runs require
+  explicit `y` to acknowledge that AGENTRUSH memories are public; the
+  acknowledgement is persisted in `~/.mem0/config.json` under
+  `agent_rush.acknowledged_at` so the prompt only appears once per machine.
+  Non-interactive (agent) invocations surface the warning to stderr without
+  blocking.
+- New config schema field: `agent_rush.acknowledged_at` (ISO timestamp,
+  empty until first interactive acknowledgement).
+
+### Changed
+
+- HTTP requests from the new agent-rush commands send `X-Mem0-Mode: agent-rush`
+  in addition to the existing source headers, so platform telemetry can split
+  game traffic from regular CLI usage.
+
+## [0.2.6] and earlier
+
+Unlogged historical releases. See git history under `cli/node/`.

cli/node/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@mem0/cli",
-  "version": "0.2.4",
+  "version": "0.2.7",
   "description": "The official CLI for mem0 — the memory layer for AI agents",
   "type": "module",
   "bin": {

cli/node/src/agent-detect.ts

@@ -0,0 +1,32 @@
+/**
+ * Detect whether the CLI is being invoked from inside an AI-agent context.
+ *
+ * Used by `mem0 init` to auto-enter Agent Mode (Rule 3 bootstrap) when an
+ * agent runtime env var is present. The return value is a context **trigger
+ * only** — the canonical agent identity is self-declared by the agent via
+ * `--agent-caller <name>` (Proof Editor-style) and never sniffed from env
+ * vars to fill the `agent_caller` field on the APIKey row.
+ *
+ * Returns a short name or null. Honest reporting depends on `--agent-caller`;
+ * this list is just enough to enable the zero-friction auto-bootstrap UX.
+ */
+
+const AGENT_CALLER_ENV: ReadonlyArray<readonly [string, readonly string[]]> = [
+	["claude-code", ["CLAUDECODE", "CLAUDE_CODE"]],
+	["cursor", ["CURSOR_AGENT", "CURSOR_SESSION_ID"]],
+	["codex", ["CODEX_CLI", "OPENAI_CODEX"]],
+	["cline", ["CLINE_AGENT", "CLINE"]],
+	["continue", ["CONTINUE_AGENT", "CONTINUE_SESSION"]],
+	["aider", ["AIDER_SESSION"]],
+	["goose", ["GOOSE_AGENT"]],
+	["windsurf", ["WINDSURF_AGENT"]],
+] as const;
+
+export function detectAgentCaller(): string | null {
+	for (const [name, envVars] of AGENT_CALLER_ENV) {
+		if (envVars.some((v) => process.env[v])) {
+			return name;
+		}
+	}
+	return null;
+}

cli/node/src/backend/platform.ts

@@ -3,7 +3,7 @@
  */
 
 import type { PlatformConfig } from "../config.js";
-import { isAgentMode } from "../state.js";
+import { captureNotice, isAgentMode } from "../state.js";
 import { CLI_VERSION } from "../version.js";
 import {
 	APIError,
@@ -90,7 +90,39 @@ export class PlatformBackend implements Backend {
 		if (resp.status === 204) {
 			return {};
 		}
-		return resp.json();
+
+		const data = await resp.json();
+
+		// Pull the unclaimed-Agent-Mode notice out of the body (or the header
+		// fallback for endpoints returning non-dict / non-dict-leading payloads)
+		// and stash for end-of-command surfacing.
+		let notice: string | null = null;
+		if (
+			data &&
+			typeof data === "object" &&
+			!Array.isArray(data) &&
+			"mem0_notice" in data
+		) {
+			notice = (data as Record<string, unknown>).mem0_notice as string;
+			// biome-ignore lint/performance/noDelete: intentional strip so downstream consumers don't see duplicate notice
+			delete (data as Record<string, unknown>).mem0_notice;
+		} else if (
+			Array.isArray(data) &&
+			data.length > 0 &&
+			typeof data[0] === "object" &&
+			data[0] !== null &&
+			"mem0_notice" in data[0]
+		) {
+			notice = (data[0] as Record<string, unknown>).mem0_notice as string;
+			// biome-ignore lint/performance/noDelete: see above.
+			delete (data[0] as Record<string, unknown>).mem0_notice;
+		}
+		if (!notice) {
+			notice = resp.headers.get("X-Mem0-Notice-Message") ?? null;
+		}
+		captureNotice(notice);
+
+		return data;
 	}
 
 	async add(

cli/node/src/commands/agent-mode.ts

@@ -0,0 +1,285 @@
+/**
+ * Agent Mode commands — bootstrap (unattended signup) and OTP-based claim.
+ */
+
+import readline from "node:readline";
+import { colors, printError, printInfo, printSuccess } from "../branding.js";
+import { type Mem0Config, saveConfig } from "../config.js";
+
+const { brand, dim } = colors;
+
+const SOURCE_HEADERS = {
+	"X-Mem0-Source": "cli",
+	"X-Mem0-Client-Language": "node",
+} as const;
+
+export interface BootstrapEnvelope {
+	api_key: string;
+	default_user_id: string;
+	org_id: string;
+	project_id: string;
+	mcp_url?: string;
+	smoke_test_url?: string;
+	claim_command?: string;
+	mem0_notice?: string;
+}
+
+function isValidEnvelope(v: unknown): v is BootstrapEnvelope {
+	return (
+		!!v &&
+		typeof v === "object" &&
+		typeof (v as BootstrapEnvelope).api_key === "string" &&
+		(v as BootstrapEnvelope).api_key.length > 0 &&
+		typeof (v as BootstrapEnvelope).default_user_id === "string" &&
+		(v as BootstrapEnvelope).default_user_id.length > 0
+	);
+}
+
+/**
+ * POST /api/v1/auth/agent_mode/ and mutate config in place.
+ *
+ * @param config - Mem0Config mutated in place with the new platform values.
+ * @param source - `--source` flag passthrough (analytics tag, free-form).
+ * @param agentCaller - Self-declared agent identity passed via `--agent-caller`
+ *   (e.g. `claude-code`, `cursor`). May be null when the caller omitted the
+ *   flag; the agent can backfill later via `mem0 identify <name>`. Sent to the
+ *   backend in the request body and saved into `platform.agentCaller` for
+ *   local introspection.
+ */
+export async function bootstrapViaBackend(
+	config: Mem0Config,
+	{
+		source,
+		agentCaller,
+	}: { source?: string | null; agentCaller?: string | null } = {},
+): Promise<void> {
+	const baseUrl = (config.platform.baseUrl || "https://api.mem0.ai").replace(
+		/\/+$/,
+		"",
+	);
+	const body: Record<string, unknown> = {};
+	if (source) body.source = source;
+	if (agentCaller) body.agent_caller = agentCaller;
+
+	let resp: Response;
+	try {
+		resp = await fetch(`${baseUrl}/api/v1/auth/agent_mode/`, {
+			method: "POST",
+			headers: {
+				...SOURCE_HEADERS,
+				"Content-Type": "application/json",
+			},
+			body: JSON.stringify(body),
+			signal: AbortSignal.timeout(30_000),
+		});
+	} catch (err) {
+		printError(
+			`Network error contacting Mem0: ${err instanceof Error ? err.message : String(err)}`,
+		);
+		process.exit(1);
+	}
+
+	if (resp.status === 429) {
+		printError("Rate-limited. Try again in a few minutes.");
+		process.exit(1);
+	}
+	if (resp.status === 503) {
+		printError("Agent Mode is temporarily disabled. Try again later.");
+		process.exit(1);
+	}
+	if (!resp.ok) {
+		let detail: string = resp.statusText;
+		try {
+			const errBody = (await resp.json()) as {
+				error?: string;
+				detail?: string;
+			};
+			detail = errBody.error ?? errBody.detail ?? resp.statusText;
+		} catch {
+			/* leave detail as statusText */
+		}
+		// Backend's @ratelimit decorator raises PermissionDenied, which DRF
+		// translates to a generic 403 "You do not have permission to perform
+		// this action." That's opaque — surface it as the rate-limit message
+		// it actually is.
+		if (resp.status === 403 && /permission/i.test(detail)) {
+			printError(
+				"Daily Agent Mode signup limit reached for this network (5/day). Try again from a different IP or after midnight UTC.",
+			);
+			process.exit(1);
+		}
+		printError(`Bootstrap failed: ${detail}`);
+		process.exit(1);
+	}
+
+	const envelope = (await resp.json()) as BootstrapEnvelope;
+	if (!isValidEnvelope(envelope)) {
+		// Defend against partial/malformed backend responses (e.g. {api_key: null}).
+		// Without this guard, the typed `string` field is silently set to
+		// undefined/null and persisted, producing confusing downstream errors.
+		printError(
+			"Bootstrap response missing required fields — please update the CLI.",
+		);
+		process.exit(1);
+	}
+
+	config.platform.apiKey = envelope.api_key;
+	config.platform.baseUrl = baseUrl;
+	config.platform.agentMode = true;
+	config.platform.createdVia = "agent_mode";
+	config.platform.agentCaller = agentCaller ?? "";
+	config.platform.claimedAt = "";
+	config.platform.defaultUserId = envelope.default_user_id;
+	// Adopt the slug-derived user_id as the default scope for memory ops.
+	config.defaults.userId = envelope.default_user_id;
+	saveConfig(config);
+
+	printSuccess(
+		`Agent Mode active. Default user_id: ${envelope.default_user_id}`,
+	);
+	if (envelope.mem0_notice) {
+		console.log(`\n\x1b[33m🔔 ${envelope.mem0_notice}\x1b[0m\n`);
+	} else {
+		// Fallback for older backends without the unified notice field.
+		const claimCmd = envelope.claim_command ?? "mem0 init --email <your-email>";
+		console.log(`  ${dim(`To claim this account later: ${claimCmd}`)}`);
+	}
+
+	if (!agentCaller) {
+		console.log(
+			`  ${dim("If you are an AI agent, identify yourself: `mem0 identify <your-name>` (e.g. claude-code, cursor).")}`,
+		);
+	}
+}
+
+/**
+ * Claim an existing Agent Mode account via OTP — no browser, no polling.
+ *
+ * Hits /api/v1/auth/email_code/ to send a verification code, prompts for it
+ * interactively (or accepts via `code`), then sends it to /verify/ alongside
+ * `agent_mode_api_key`. Backend's verify_email_code runs upgrade-in-place
+ * inline and returns the claim result.
+ */
+export async function claimViaOtp(
+	config: Mem0Config,
+	{ email, code }: { email: string; code?: string },
+): Promise<void> {
+	const baseUrl = (config.platform.baseUrl || "https://api.mem0.ai").replace(
+		/\/+$/,
+		"",
+	);
+	if (!config.platform.apiKey || !config.platform.agentMode) {
+		printError(
+			"This command requires an active Agent Mode config. Run `mem0 init` first.",
+		);
+		process.exit(1);
+	}
+
+	const rawKey = config.platform.apiKey;
+
+	// Step 1: request OTP (unless --code was supplied)
+	if (!code) {
+		const sendResp = await fetch(`${baseUrl}/api/v1/auth/email_code/`, {
+			method: "POST",
+			headers: { ...SOURCE_HEADERS, "Content-Type": "application/json" },
+			body: JSON.stringify({ email }),
+			signal: AbortSignal.timeout(30_000),
+		});
+		if (sendResp.status === 429) {
+			printError("Too many attempts. Try again in a few minutes.");
+			process.exit(1);
+		}
+		if (!sendResp.ok) {
+			let detail: string = sendResp.statusText;
+			try {
+				const errBody = (await sendResp.json()) as { error?: string };
+				if (errBody.error) detail = errBody.error;
+			} catch {
+				/* leave as statusText */
+			}
+			printError(`Failed to send code: ${detail}`);
+			process.exit(1);
+		}
+
+		printSuccess(`Verification code sent to ${email}. Check your inbox.`);
+
+		if (!process.stdin.isTTY) {
+			printError(
+				"No --code provided and terminal is non-interactive.",
+				`Re-run: mem0 init --email ${email} --code <code>`,
+			);
+			process.exit(1);
+		}
+
+		console.log();
+		code = await promptLine(`  ${brand("Verification Code")}`);
+		if (!code) {
+			printError("Code is required.");
+			process.exit(1);
+		}
+	}
+
+	// Step 2: verify + claim atomically
+	const verifyResp = await fetch(`${baseUrl}/api/v1/auth/email_code/verify/`, {
+		method: "POST",
+		headers: { ...SOURCE_HEADERS, "Content-Type": "application/json" },
+		body: JSON.stringify({
+			email,
+			code: code.trim(),
+			agent_mode_api_key: rawKey,
+		}),
+		signal: AbortSignal.timeout(30_000),
+	});
+
+	if (!verifyResp.ok) {
+		let detail: string = verifyResp.statusText;
+		let errCode = "";
+		try {
+			const errBody = (await verifyResp.json()) as {
+				error?: string;
+				code?: string;
+			};
+			if (errBody.error) detail = errBody.error;
+			if (errBody.code) errCode = errBody.code;
+		} catch {
+			/* leave as statusText */
+		}
+		printError(`Claim failed: ${detail}`);
+		if (errCode === "email_already_claimed") {
+			console.log(
+				`  ${dim("Tip: this email already has a Mem0 account. Sign in at app.mem0.ai with your existing credentials.")}`,
+			);
+		}
+		process.exit(1);
+	}
+
+	const claimBody = (await verifyResp.json()) as {
+		claimed?: boolean;
+		claimed_at?: string;
+	};
+	if (!claimBody.claimed) {
+		printError(`Unexpected verify response: ${JSON.stringify(claimBody)}`);
+		process.exit(1);
+	}
+
+	config.platform.agentMode = false;
+	config.platform.claimedAt = claimBody.claimed_at ?? new Date().toISOString();
+	config.platform.userEmail = email;
+	config.platform.createdVia = "email";
+	saveConfig(config);
+
+	printSuccess(`Agent claimed to ${email}. Your API key is unchanged.`);
+}
+
+function promptLine(label: string): Promise<string> {
+	const rl = readline.createInterface({
+		input: process.stdin,
+		output: process.stdout,
+	});
+	return new Promise((resolve) => {
+		rl.question(`${label}: `, (answer) => {
+			rl.close();
+			resolve(answer.trim());
+		});
+	});
+}

cli/node/src/commands/agent-rush.ts

@@ -0,0 +1,147 @@
+/**
+ * `mem0 agent-rush <add|search> "..."` — wraps the AGENTRUSH platform endpoints.
+ * Project routing is implicit (server-side); zero flags needed.
+ */
+
+import readline from "node:readline";
+import { colors, printError, printSuccess } from "../branding.js";
+import { loadConfig, saveConfig } from "../config.js";
+import { CLI_VERSION } from "../version.js";
+
+const PII_WARNING = [
+	"",
+	"⚠️  AGENTRUSH memories are PUBLIC — visible to any other player.",
+	"   Do not include real names, emails, secrets, work content, or PII.",
+	"",
+].join("\n");
+
+const ERROR_HINTS: Record<string, string> = {
+	agentrush_search_first:
+		"Run 3 'mem0 agent-rush search' commands before adding.",
+	agentrush_search_quota: "You've used your 3 lifetime searches.",
+	agentrush_add_quota: "You've used your 3 lifetime adds.",
+	agentrush_not_agent_mode:
+		"Re-run 'mem0 init --agent' to bootstrap an agent-mode key.",
+	agentrush_length: "Memory text must be 50-1000 characters.",
+	agentrush_no_urls: "URLs are not allowed.",
+	agentrush_blocklist: "Content contains a blocked term.",
+	agentrush_global_quota: "Event-wide cap reached. Try again later.",
+	agentrush_not_provisioned:
+		"AGENTRUSH is not provisioned in this environment.",
+};
+
+async function callEndpoint(
+	path: string,
+	body: Record<string, unknown>,
+): Promise<unknown> {
+	const config = loadConfig();
+	const baseUrl = (config.platform?.baseUrl ?? "https://api.mem0.ai").replace(
+		/\/+$/,
+		"",
+	);
+
+	if (!config.platform?.apiKey) {
+		printError("Not initialized. Run `mem0 init --agent` first.");
+		process.exit(1);
+	}
+
+	const resp = await fetch(`${baseUrl}${path}`, {
+		method: "POST",
+		headers: {
+			Authorization: `Token ${config.platform.apiKey}`,
+			"Content-Type": "application/json",
+			"X-Mem0-Source": "cli",
+			"X-Mem0-Client-Language": "node",
+			"X-Mem0-Client-Version": CLI_VERSION,
+			"X-Mem0-Mode": "agent-rush",
+		},
+		body: JSON.stringify(body),
+		signal: AbortSignal.timeout(30_000),
+	});
+
+	const json = await resp.json().catch(() => ({}));
+
+	if (!resp.ok) {
+		const code =
+			(json as { error?: { code?: string } }).error?.code ?? "unknown";
+		printError(`AGENTRUSH error: ${code}`);
+		if (ERROR_HINTS[code]) {
+			console.log(`  ${colors.dim(ERROR_HINTS[code])}`);
+		}
+		process.exit(1);
+	}
+
+	return json;
+}
+
+function promptLine(question: string): Promise<string> {
+	const rl = readline.createInterface({
+		input: process.stdin,
+		output: process.stdout,
+	});
+	return new Promise((resolve) => {
+		rl.question(question, (answer) => {
+			rl.close();
+			resolve(answer.trim());
+		});
+	});
+}
+
+/**
+ * Ensure the human has acknowledged that AGENTRUSH memories are PUBLIC.
+ *
+ * Interactive (TTY): show the prompt; on "y" persist `agentRush.acknowledgedAt`
+ * so we never ask the same machine twice. On anything else, abort.
+ *
+ * Non-interactive (agent invocation, no TTY): print the warning to stderr
+ * for the human reading the agent's transcript and proceed — agents can't
+ * answer y/N prompts.
+ */
+async function ensureWarningAcknowledged(): Promise<void> {
+	const config = loadConfig();
+	if (config.agentRush?.acknowledgedAt) return;
+
+	if (!process.stdin.isTTY || !process.stdout.isTTY) {
+		// Agent context: surface the warning to stderr, don't block.
+		console.error(PII_WARNING);
+		return;
+	}
+
+	console.log(PII_WARNING);
+	const answer = (await promptLine("   Continue? [y/N]: ")).toLowerCase();
+	if (answer !== "y" && answer !== "yes") {
+		printError("Aborted.");
+		process.exit(1);
+	}
+
+	config.agentRush.acknowledgedAt = new Date().toISOString();
+	saveConfig(config);
+}
+
+export async function cmdAgentRushAdd(content: string): Promise<void> {
+	await ensureWarningAcknowledged();
+	const result = await callEndpoint("/v1/agent-rush/memories/", { content });
+	printSuccess(
+		`Memory submitted (event_id: ${(result as { event_id?: string }).event_id ?? "?"})`,
+	);
+}
+
+export async function cmdAgentRushSearch(query: string): Promise<void> {
+	const result = (await callEndpoint("/v1/agent-rush/memories/search/", {
+		query,
+	})) as {
+		results?: Array<{ memory?: string }>;
+		memories?: Array<{ memory?: string }>;
+	};
+
+	const memories = result.results ?? result.memories ?? [];
+
+	if (memories.length === 0) {
+		console.log(colors.dim("(no results)"));
+		return;
+	}
+
+	memories.slice(0, 5).forEach((m, i) => {
+		console.log(`  ${i + 1}. ${m.memory ?? JSON.stringify(m)}`);
+	});
+}

cli/node/src/commands/identify.ts

@@ -0,0 +1,75 @@
+/**
+ * mem0 identify — declare which agent owns the current agent-mode key.
+ *
+ * Used when `mem0 init --agent` ran without --agent-caller, so the backend
+ * saved agent_caller=NULL. The agent re-runs `mem0 identify <name>` to PATCH
+ * its own row with its real identity. Idempotent.
+ */
+
+import { printError, printSuccess } from "../branding.js";
+import { loadConfig, saveConfig } from "../config.js";
+
+const SOURCE_HEADERS = {
+	"X-Mem0-Source": "cli",
+	"X-Mem0-Client-Language": "node",
+} as const;
+
+export async function runIdentify(name: string): Promise<void> {
+	const config = loadConfig();
+	if (!config.platform.apiKey) {
+		printError("No API key configured. Run `mem0 init --agent` first.");
+		process.exit(1);
+	}
+	if (!config.platform.agentMode) {
+		printError("This command only works on unclaimed agent-mode keys.");
+		process.exit(1);
+	}
+
+	const clean = (name ?? "").trim();
+	if (!clean) {
+		printError("Agent name is required.");
+		process.exit(1);
+	}
+
+	const baseUrl = (config.platform.baseUrl || "https://api.mem0.ai").replace(
+		/\/+$/,
+		"",
+	);
+
+	let resp: Response;
+	try {
+		resp = await fetch(`${baseUrl}/api/v1/auth/agent_mode/caller/`, {
+			method: "PATCH",
+			headers: {
+				...SOURCE_HEADERS,
+				Authorization: `Token ${config.platform.apiKey}`,
+				"Content-Type": "application/json",
+			},
+			body: JSON.stringify({ agent_caller: clean }),
+			signal: AbortSignal.timeout(30_000),
+		});
+	} catch (err) {
+		printError(
+			`Network error: ${err instanceof Error ? err.message : String(err)}`,
+		);
+		process.exit(1);
+	}
+
+	if (!resp.ok) {
+		let detail: string = resp.statusText;
+		try {
+			const body = (await resp.json()) as { error?: string };
+			if (body.error) detail = body.error;
+		} catch {
+			/* leave as statusText */
+		}
+		printError(`Identify failed: ${detail}`);
+		process.exit(1);
+	}
+
+	const body = (await resp.json()) as { agent_caller?: string };
+	const canonical = body.agent_caller ?? clean;
+	config.platform.agentCaller = canonical;
+	saveConfig(config);
+	printSuccess(`Identified as ${canonical}.`);
+}

cli/node/src/commands/init.ts

@@ -21,6 +21,8 @@ import {
 	redactKey,
 	saveConfig,
 } from "../config.js";
+import { formatJsonEnvelope } from "../output.js";
+import { isAgentMode } from "../state.js";
 
 const { brand, dim } = colors;
 
@@ -33,6 +35,65 @@ function validateEmail(email: string): void {
 	}
 }
 
+/** @internal — exported for unit tests. */
+export async function pingKey(
+	apiKey: string,
+	baseUrl: string,
+	timeoutMs = 5000,
+): Promise<boolean> {
+	// Returns false ONLY on a definitive "invalid key" signal (HTTP 401/403).
+	// Network errors, timeouts, and 5xx responses return true so we prefer
+	// reusing an existing key over silently minting a new shadow on a transient
+	// blip (which would also clobber config + plugin-sync targets).
+	try {
+		const resp = await fetch(`${baseUrl.replace(/\/+$/, "")}/v1/ping/`, {
+			headers: { Authorization: `Token ${apiKey}` },
+			signal: AbortSignal.timeout(timeoutMs),
+		});
+		return resp.status !== 401 && resp.status !== 403;
+	} catch {
+		return true; // unknown — prefer reuse
+	}
+}
+
+async function maybeIdentify(
+	key: string,
+	baseUrl: string,
+	agentCaller: string | undefined,
+): Promise<void> {
+	// Best-effort PATCH agent_caller when --agent-caller is supplied on a
+	// reused key. Silent no-op on any failure — reuse must not break.
+	if (!agentCaller) return;
+	try {
+		const resp = await fetch(
+			`${baseUrl.replace(/\/+$/, "")}/api/v1/auth/agent_mode/caller/`,
+			{
+				method: "PATCH",
+				headers: {
+					Authorization: `Token ${key}`,
+					"Content-Type": "application/json",
+				},
+				body: JSON.stringify({ agent_caller: agentCaller }),
+				signal: AbortSignal.timeout(10_000),
+			},
+		);
+		if (resp.ok) {
+			try {
+				const body = (await resp.json()) as { agent_caller?: string };
+				if (fs.existsSync(CONFIG_FILE)) {
+					const cfg = loadConfig();
+					cfg.platform.agentCaller = body.agent_caller ?? agentCaller;
+					saveConfig(cfg);
+				}
+			} catch {
+				/* swallow — best effort */
+			}
+		}
+	} catch {
+		/* swallow — best effort */
+	}
+}
+
 async function emailLogin(
 	email: string,
 	code: string | undefined,
@@ -196,6 +257,7 @@ async function setupPlatform(config: Mem0Config): Promise<void> {
 		process.exit(1);
 	}
 	config.platform.apiKey = apiKey;
+	config.platform.createdVia = "api_key";
 }
 
 async function setupDefaults(config: Mem0Config): Promise<void> {
@@ -249,14 +311,35 @@ export async function runInit(
 		email?: string;
 		code?: string;
 		force?: boolean;
+		agent?: boolean;
+		source?: string;
+		agentCaller?: string;
 	} = {},
 ): Promise<void> {
+	const { detectAgentCaller } = await import("../agent-detect.js");
+	const { bootstrapViaBackend, claimViaOtp } = await import("./agent-mode.js");
+	const { isAgentMode } = await import("../state.js");
+	const { captureEvent } = await import("../telemetry.js");
+
+	const fireInit = (
+		mode: "agent" | "email" | "api_key" | "existing_key",
+		claimed = false,
+	) => {
+		const props: Record<string, unknown> = { command: "init", mode };
+		// Self-declared via --agent-caller; not sniffed from env vars.
+		if (opts.agentCaller) props.agent_caller = opts.agentCaller;
+		if (opts.source) props.signup_source = opts.source;
+		if (claimed) props.claimed_agent_mode = true;
+		captureEvent("cli.init", props);
+	};
+
 	const config = createDefaultConfig();
 	const savedConfig = loadConfig();
 	const baseUrl =
 		process.env.MEM0_BASE_URL ||
 		savedConfig.platform.baseUrl ||
 		DEFAULT_BASE_URL;
+	config.platform.baseUrl = baseUrl;
 
 	// Guards
 	if (opts.code && !opts.email) {
@@ -268,6 +351,84 @@ export async function runInit(
 		process.exit(1);
 	}
 
+	// ── Claim flow: --email against an existing agent-mode config ───────────
+	if (
+		opts.email &&
+		fs.existsSync(CONFIG_FILE) &&
+		savedConfig.platform.agentMode &&
+		savedConfig.platform.apiKey
+	) {
+		const email = opts.email.trim().toLowerCase();
+		validateEmail(email);
+		printInfo(`Claiming Agent Mode account to ${email}...`);
+		await claimViaOtp(savedConfig, { email, code: opts.code });
+		fireInit("email", true);
+		return;
+	}
+
+	// ── Agent Mode path runs BEFORE the existing-config guard ──────────────
+	// Rule 1/2 will REUSE a valid existing key (not overwrite), so we must
+	// short-circuit before the guard prompts the user about overwriting.
+	// Rule 3 only mints when there's no valid key to reuse — in that case
+	// overwriting is what the user wants.
+	const agentCtx =
+		opts.agent === true || isAgentMode() || detectAgentCaller() !== null;
+	if (!opts.apiKey && !opts.email && agentCtx) {
+		const emitReuseEnvelope = (source: "env" | "config") => {
+			if (isAgentMode()) {
+				formatJsonEnvelope({
+					command: "init",
+					data: {
+						api_key_saved: false,
+						api_key_source: source,
+						agent_mode: false,
+						message:
+							"Existing Mem0 API key found and reused. No Agent Mode key was created.",
+					},
+				});
+			} else {
+				printSuccess(
+					source === "env"
+						? "Existing MEM0_API_KEY is valid; reusing it. No new Agent Mode key was minted."
+						: "Existing API key in config is valid; reusing it. No new Agent Mode key was minted.",
+				);
+			}
+		};
+		// Rule 1: env MEM0_API_KEY valid → reuse, no new key.
+		const envKey = (process.env.MEM0_API_KEY || "").trim();
+		if (envKey && (await pingKey(envKey, baseUrl))) {
+			await maybeIdentify(envKey, baseUrl, opts.agentCaller);
+			emitReuseEnvelope("env");
+			fireInit("existing_key");
+			return;
+		}
+		// Rule 2: existing config api_key valid → reuse.
+		if (
+			savedConfig.platform.apiKey &&
+			(await pingKey(savedConfig.platform.apiKey, baseUrl))
+		) {
+			await maybeIdentify(
+				savedConfig.platform.apiKey,
+				baseUrl,
+				opts.agentCaller,
+			);
+			emitReuseEnvelope("config");
+			fireInit("existing_key");
+			return;
+		}
+		// Rule 3: mint a fresh shadow (no valid key to reuse).
+		// agent_caller is self-declared via --agent-caller (Proof Editor-style),
+		// not derived from env-var sniffing. detectAgentCaller() above is still
+		// used as a context trigger (does this look like an agent?) but never
+		// to fill identity.
+		await bootstrapViaBackend(config, {
+			source: opts.source ?? null,
+			agentCaller: opts.agentCaller ?? null,
+		});
+		fireInit("agent");
+		return;
+	}
+
 	// Warn if an existing config with an API key would be overwritten
 	if (
 		!opts.force &&
@@ -324,6 +485,7 @@ export async function runInit(
 		config.platform.apiKey = apiKeyVal;
 		config.platform.baseUrl = baseUrl;
 		config.platform.userEmail = email;
+		config.platform.createdVia = "email";
 		config.defaults.userId =
 			opts.userId || process.env.USER || process.env.USERNAME || "mem0-cli";
 
@@ -339,13 +501,15 @@ export async function runInit(
 	}
 
 	// ── API key flow ──────────────────────────────────────────────────────────
+	// (Agent Mode branch runs earlier — see above, before the existing-config
+	// guard, so Rules 1/2 can REUSE a valid key without prompting overwrite.)
 
 	// Non-TTY: resolve defaults so partial flags work in pipelines / CI
 	if (!process.stdin.isTTY) {
 		if (!opts.apiKey) {
 			printError(
 				"Non-interactive terminal detected and --api-key is required.",
-				"Usage: mem0 init --api-key <key> [--user-id <id>]",
+				"Usage: mem0 init --api-key <key>, --email <addr>, or --agent for unattended Agent Mode bootstrap.",
 			);
 			process.exit(1);
 		}
@@ -356,6 +520,7 @@ export async function runInit(
 	// Non-interactive: both flags provided
 	if (opts.apiKey && opts.userId) {
 		config.platform.apiKey = opts.apiKey;
+		config.platform.createdVia = "api_key";
 		config.defaults.userId = opts.userId;
 		await validatePlatform(config);
 		saveConfig(config);
@@ -403,6 +568,7 @@ export async function runInit(
 			config.platform.apiKey = apiKeyVal;
 			config.platform.baseUrl = baseUrl;
 			config.platform.userEmail = email;
+			config.platform.createdVia = "email";
 			config.defaults.userId =
 				opts.userId || process.env.USER || process.env.USERNAME || "mem0-cli";
 

cli/node/src/commands/memory.ts

@@ -46,7 +46,7 @@ export async function cmdAdd(
 		file?: string;
 		metadata?: string;
 		immutable: boolean;
-		noInfer: boolean;
+		infer?: boolean;
 		expires?: string;
 		categories?: string;
 		output: string;
@@ -136,7 +136,7 @@ export async function cmdAdd(
 				runId: opts.runId,
 				metadata: meta,
 				immutable: opts.immutable,
-				infer: !opts.noInfer,
+				infer: opts.infer !== false,
 				expires: opts.expires,
 				categories: cats,
 			});

cli/node/src/commands/whoami.ts

@@ -0,0 +1,18 @@
+/**
+ * `mem0 whoami` — print the active agent's default_user_id (AGENTRUSH identifier).
+ * Reads from local config; no network call.
+ */
+
+import { colors, printError, printInfo } from "../branding.js";
+import { loadConfig } from "../config.js";
+
+export async function cmdWhoami(): Promise<void> {
+	const config = loadConfig();
+	const sessionId = config.platform?.defaultUserId;
+	if (!sessionId) {
+		printError("No default_user_id found. Run `mem0 init --agent` first.");
+		process.exit(1);
+	}
+	console.log(`Your AGENTRUSH identifier:  ${colors.brand(sessionId)}`);
+	printInfo("Find your row at https://mem0.ai/agentrush");
+}

cli/node/src/config.ts

@@ -21,6 +21,12 @@ export interface PlatformConfig {
 	apiKey: string;
 	baseUrl: string;
 	userEmail: string;
+	// Agent Mode (unclaimed-shadow signup)
+	agentMode: boolean; // true while the key is an unclaimed agent-mode key
+	createdVia: string; // "agent_mode" | "email" | "api_key" | "existing_key"
+	agentCaller: string; // canonical agent name when createdVia === "agent_mode" (e.g. "claude-code")
+	claimedAt: string; // ISO timestamp once the agent has been claimed
+	defaultUserId: string; // `user_<slug>` returned by bootstrap; auto-default scope
 }
 
 export interface DefaultsConfig {
@@ -34,11 +40,18 @@ export interface TelemetryConfig {
 	anonymousId: string;
 }
 
+export interface AgentRushConfig {
+	// ISO timestamp the human acknowledged the "memories are public" warning.
+	// Empty until first interactive `mem0 agent-rush add`.
+	acknowledgedAt: string;
+}
+
 export interface Mem0Config {
 	version: number;
 	defaults: DefaultsConfig;
 	platform: PlatformConfig;
 	telemetry: TelemetryConfig;
+	agentRush: AgentRushConfig;
 }
 
 export function createDefaultConfig(): Mem0Config {
@@ -54,10 +67,18 @@ export function createDefaultConfig(): Mem0Config {
 			apiKey: "",
 			baseUrl: DEFAULT_BASE_URL,
 			userEmail: "",
+			agentMode: false,
+			createdVia: "",
+			agentCaller: "",
+			claimedAt: "",
+			defaultUserId: "",
 		},
 		telemetry: {
 			anonymousId: "",
 		},
+		agentRush: {
+			acknowledgedAt: "",
+		},
 	};
 }
 
@@ -79,6 +100,11 @@ export function loadConfig(): Mem0Config {
 		config.platform.apiKey = plat.api_key ?? "";
 		config.platform.baseUrl = plat.base_url ?? DEFAULT_BASE_URL;
 		config.platform.userEmail = plat.user_email ?? "";
+		config.platform.agentMode = Boolean(plat.agent_mode ?? false);
+		config.platform.createdVia = plat.created_via ?? "";
+		config.platform.agentCaller = plat.agent_caller ?? "";
+		config.platform.claimedAt = plat.claimed_at ?? "";
+		config.platform.defaultUserId = plat.default_user_id ?? "";
 
 		const defaults = data.defaults ?? {};
 		config.defaults.userId = defaults.user_id ?? "";
@@ -87,6 +113,8 @@ export function loadConfig(): Mem0Config {
 		config.defaults.runId = defaults.run_id ?? "";
 		const telemetry = data.telemetry ?? {};
 		config.telemetry.anonymousId = telemetry.anonymous_id ?? "";
+		const agentRush = data.agent_rush ?? {};
+		config.agentRush.acknowledgedAt = agentRush.acknowledged_at ?? "";
 	}
 
 	// Environment variable overrides
@@ -118,14 +146,36 @@ export function saveConfig(config: Mem0Config): void {
 			api_key: config.platform.apiKey,
 			base_url: config.platform.baseUrl,
 			user_email: config.platform.userEmail,
+			agent_mode: config.platform.agentMode,
+			created_via: config.platform.createdVia,
+			agent_caller: config.platform.agentCaller,
+			claimed_at: config.platform.claimedAt,
+			default_user_id: config.platform.defaultUserId,
 		},
 		telemetry: {
 			anonymous_id: config.telemetry.anonymousId,
 		},
+		agent_rush: {
+			acknowledged_at: config.agentRush.acknowledgedAt,
+		},
 	};
 
 	fs.writeFileSync(CONFIG_FILE, JSON.stringify(data, null, 2));
 	fs.chmodSync(CONFIG_FILE, 0o600);
+
+	// Propagate api_key to ecosystem touchpoints (Claude plugin env injection,
+	// shell rc exports). Idempotent — updates only EXISTING entries; never
+	// creates new ones. Best-effort: errors swallowed so config.json is
+	// always authoritative, never blocked by plugin-state issues.
+	if (config.platform.apiKey) {
+		try {
+			// eslint-disable-next-line @typescript-eslint/no-require-imports
+			const { syncApiKey } = require("./plugin-sync.js");
+			syncApiKey(config.platform.apiKey);
+		} catch {
+			/* swallow */
+		}
+	}
 }
 
 export function redactKey(key: string): string {

cli/node/src/index.ts

@@ -13,7 +13,12 @@ import { colors, printError, printWarning } from "./branding.js";
 import type { Mem0Config } from "./config.js";
 import { loadConfig, saveConfig } from "./config.js";
 import { richFormatHelp } from "./help.js";
-import { setAgentMode } from "./state.js";
+import {
+	isAgentMode,
+	setAgentMode,
+	setCurrentCommand,
+	takeNotice,
+} from "./state.js";
 import { captureEvent } from "./telemetry.js";
 import { CLI_VERSION } from "./version.js";
 
@@ -141,6 +146,11 @@ program
 	.description(
 		`◆ Mem0 CLI v${CLI_VERSION} · Node.js SDK\n\nThe Memory Layer for AI Agents`,
 	)
+	// Positional options: flags AFTER a subcommand name belong to that
+	// subcommand, not the global program. Without this, `mem0 init --agent`
+	// routes `--agent` to the program-level alias (for --json) and init's own
+	// `--agent` (Agent Mode bootstrap) silently never fires.
+	.enablePositionalOptions()
 	.option("--version", "Show version and exit.")
 	.on("option:version", () => {
 		console.log(`  ${colors.brand("◆ Mem0")} CLI v${CLI_VERSION}`);
@@ -149,7 +159,7 @@ program
 	.option("--json", "Output as JSON for agent/programmatic use.")
 	.option(
 		"--agent",
-		"Output as JSON for agent/programmatic use. (alias: --json)",
+		"Output as JSON for agent/programmatic use. (alias: --json) Place BEFORE the subcommand: `mem0 --agent <cmd>`. On `init`, `mem0 init --agent` is the Agent Mode bootstrap flag instead.",
 	)
 	.usage("<command> [options]")
 	.helpOption("--help", "Show this message and exit.")
@@ -166,6 +176,14 @@ program.hook("preAction", (_thisCommand, actionCommand) => {
 			parentName && parentName !== "mem0"
 				? `${parentName}.${commandName}`
 				: commandName;
+		// Stash the active command name in shared state so the JSON
+		// error envelope (printError) can report which command failed
+		// instead of an empty `"command": ""` field.
+		setCurrentCommand(fullCommand);
+		// init fires its own telemetry from runInit with full M1-M6 props
+		// (mode/agent_caller/signup_source/claimed_agent_mode); skip the
+		// auto-fire here so we don't double-count.
+		if (fullCommand === "init") return;
 		const isAgent = !!(program.opts().json || program.opts().agent);
 		captureEvent(
 			`cli.${fullCommand}`,
@@ -193,11 +211,32 @@ program
 		"Verification code (use with --email for non-interactive login).",
 	)
 	.option("--force", "Overwrite existing config without confirmation.", false)
+	.option(
+		"--agent",
+		"Bootstrap an unattended Agent Mode account (no email required).",
+		false,
+	)
+	.option(
+		"--source <channel>",
+		"Channel attribution for signup (e.g. github, hn, ph).",
+	)
+	.option(
+		"--agent-caller <name>",
+		"Self-declared agent identity (e.g. claude-code, cursor). Used with --agent to attribute Agent Mode signups.",
+	)
+	// Accept `--json` at the init level too so the PRD-documented form
+	// `mem0 init --agent --json` works without requiring users to move it
+	// before the subcommand. Effect is identical to the global `--json`:
+	// flip agent-mode output state.
+	.option("--json", "Output as JSON (alias for global `--json`).", false)
 	.addHelpText(
 		"after",
-		"\nExamples:\n  $ mem0 init\n  $ mem0 init --api-key m0-xxx --user-id alice\n  $ mem0 init --email you@example.com\n  $ mem0 init --email you@example.com --code 123456",
+		"\nExamples:\n  $ mem0 init\n  $ mem0 init --api-key m0-xxx --user-id alice\n  $ mem0 init --email you@example.com\n  $ mem0 init --email you@example.com --code 123456\n  $ mem0 init --agent             # Bootstrap an Agent Mode account (unattended)\n  $ mem0 init --email you@example.com  # Claims an existing Agent Mode key when one is present",
 	)
 	.action(async (opts) => {
+		// `--json` at init level mirrors the global flag — flip agent_mode
+		// state so downstream formatters use JSON envelopes.
+		if (opts.json) setAgentMode(true);
 		const { runInit } = await import("./commands/init.js");
 		await runInit({
 			apiKey: opts.apiKey,
@@ -205,9 +244,66 @@ program
 			email: opts.email,
 			code: opts.code,
 			force: opts.force,
+			agent: opts.agent,
+			source: opts.source,
+			agentCaller: opts.agentCaller,
 		});
 	});
 
+// ── Setup: identify (post-bootstrap agent self-tag) ──────────────────────
+
+program
+	.command("identify <name>")
+	.description(
+		"Tag your active Agent Mode key with the AI agent that's using it (e.g. claude-code, cursor).",
+	)
+	.action(async (name: string) => {
+		const { runIdentify } = await import("./commands/identify.js");
+		await runIdentify(name);
+	});
+
+// ── Setup: whoami (print active agent identifier) ────────────────────────
+
+program
+	.command("whoami")
+	.description("Print the active agent's AGENTRUSH identifier.")
+	.action(async () => {
+		const { cmdWhoami } = await import("./commands/whoami.js");
+		await cmdWhoami();
+	});
+
+// ── AGENTRUSH subcommand group ────────────────────────────────────────────
+
+const agentRush = program
+	.command("agent-rush")
+	.description("AGENTRUSH game commands.")
+	.addHelpCommand(false)
+	.configureHelp({ formatHelp: richFormatHelp });
+
+agentRush
+	.command("add <content...>")
+	.description("Submit a memory to AGENTRUSH.")
+	.addHelpText(
+		"after",
+		'\nExamples:\n  $ mem0 agent-rush add "I used mem0 to build a coding agent"\n  $ mem0 agent-rush add "Agents that remember are better agents"',
+	)
+	.action(async (parts: string[]) => {
+		const { cmdAgentRushAdd } = await import("./commands/agent-rush.js");
+		await cmdAgentRushAdd(parts.join(" "));
+	});
+
+agentRush
+	.command("search <query...>")
+	.description("Search AGENTRUSH memories.")
+	.addHelpText(
+		"after",
+		'\nExamples:\n  $ mem0 agent-rush search "agents and memory and tools"\n  $ mem0 agent-rush search "coding assistant"',
+	)
+	.action(async (parts: string[]) => {
+		const { cmdAgentRushSearch } = await import("./commands/agent-rush.js");
+		await cmdAgentRushSearch(parts.join(" "));
+	});
+
 // ── Memory: add ───────────────────────────────────────────────────────────
 
 program
@@ -769,4 +865,16 @@ program
 
 // ── Entrypoint ────────────────────────────────────────────────────────────
 
-program.parse();
+// Surface any unclaimed Agent Mode notice once per command, after the primary
+// output. In JSON/agent mode the notice is folded into the envelope by
+// formatJsonEnvelope, so skip the stderr banner there to avoid duplication.
+function surfaceNotice(): void {
+	const notice = takeNotice();
+	if (notice && !isAgentMode()) {
+		process.stderr.write(`\n\x1b[33m🔔 ${notice}\x1b[0m\n\n`);
+	}
+}
+
+program.parseAsync().finally(() => {
+	surfaceNotice();
+});

cli/node/src/output.ts

@@ -5,6 +5,7 @@
 import boxen from "boxen";
 import Table from "cli-table3";
 import { colors, sym } from "./branding.js";
+import { takeNotice } from "./state.js";
 
 const { brand, accent, success, error: errorColor, dim } = colors;
 
@@ -244,6 +245,15 @@ export function formatJsonEnvelope(opts: {
 	if (opts.count !== undefined) envelope.count = opts.count;
 	if (opts.error) envelope.error = opts.error;
 	envelope.data = opts.data;
+
+	// If the platform flagged this as an unclaimed Agent Mode account, surface
+	// the notice inside the JSON envelope so an agent consuming the output
+	// sees it without needing to inspect HTTP headers.
+	// eslint-disable-next-line @typescript-eslint/no-require-imports
+	const { takeNotice } = require("./state.js");
+	const notice = takeNotice();
+	if (notice) envelope.mem0_notice = notice;
+
 	console.log(JSON.stringify(envelope, null, 2));
 }
 
@@ -356,6 +366,12 @@ export function formatAgentEnvelope(opts: {
 	}
 	if (opts.count !== undefined) envelope.count = opts.count;
 	envelope.data = sanitizeAgentData(opts.command, opts.data);
+
+	// Surface the unclaimed-Agent-Mode notice (if any) in the envelope so an
+	// agent reading the JSON output sees it without inspecting HTTP headers.
+	const notice = takeNotice();
+	if (notice) envelope.mem0_notice = notice;
+
 	console.log(JSON.stringify(envelope, null, 2));
 }
 

cli/node/src/plugin-sync.ts

@@ -0,0 +1,120 @@
+/**
+ * Sync the active Mem0 API key into other ecosystem touchpoints.
+ *
+ * Why: the CLI canonical state is ~/.mem0/config.json. MCP servers
+ * (Claude Code plugin, Codex plugin) read MEM0_API_KEY from env or
+ * their own config files. Without a sync, agent-mode bootstrap mints a
+ * new key into config.json but the plugin's MCP keeps using the old
+ * key from env — silent surprise.
+ *
+ * Design:
+ *  - Update ONLY entries that already exist; never create new ones
+ *  - Preserve surrounding content, formatting, other keys
+ *  - Atomic writes (tmp + rename) so a crash mid-write doesn't corrupt
+ *  - Idempotent — re-running with the same key is a no-op
+ *
+ * Targets:
+ *  - ~/.claude/settings.json::env::MEM0_API_KEY (Claude Code env injection)
+ *  - ~/.zshrc / ~/.bashrc `export MEM0_API_KEY="..."` lines
+ *
+ * Out of scope: Codex / Cursor MCP configs and the plugin's own
+ * <plugin-dir>/.api_key file (plugin-managed, different schema).
+ */
+
+import fs from "node:fs";
+import os from "node:os";
+import path from "node:path";
+
+const CLAUDE_SETTINGS = path.join(os.homedir(), ".claude", "settings.json");
+const SHELL_RCS = [
+	path.join(os.homedir(), ".zshrc"),
+	path.join(os.homedir(), ".bashrc"),
+	path.join(os.homedir(), ".bash_profile"),
+];
+
+// Use [ \t]* (not \s*) so a trailing newline at end-of-file is preserved
+// when the MEM0_API_KEY export is the last line of the rc file.
+const RC_LINE_RE =
+	/^([ \t]*export[ \t]+MEM0_API_KEY[ \t]*=[ \t]*)(["']?)([^"'\n]*)(["']?)[ \t]*$/m;
+
+export function syncApiKey(apiKey: string): string[] {
+	if (!apiKey) return [];
+	const updated: string[] = [];
+	if (updateClaudeSettings(CLAUDE_SETTINGS, apiKey)) {
+		updated.push(CLAUDE_SETTINGS);
+	}
+	for (const rc of SHELL_RCS) {
+		if (updateShellRc(rc, apiKey)) updated.push(rc);
+	}
+	return updated;
+}
+
+/** @internal — exported for unit tests; consumers should use {@link syncApiKey}. */
+export function updateClaudeSettings(
+	filePath: string,
+	apiKey: string,
+): boolean {
+	if (!fs.existsSync(filePath)) return false;
+	let raw: string;
+	let data: Record<string, unknown>;
+	try {
+		raw = fs.readFileSync(filePath, "utf-8");
+		data = JSON.parse(raw);
+	} catch {
+		return false;
+	}
+	const env = data.env;
+	if (!env || typeof env !== "object" || !("MEM0_API_KEY" in env)) {
+		return false; // no existing entry — don't create one
+	}
+	const envObj = env as Record<string, string>;
+	if (envObj.MEM0_API_KEY === apiKey) return false; // already in sync
+	envObj.MEM0_API_KEY = apiKey;
+	atomicWriteText(filePath, `${JSON.stringify(data, null, 2)}\n`);
+	return true;
+}
+
+/** @internal — exported for unit tests; consumers should use {@link syncApiKey}. */
+export function updateShellRc(filePath: string, apiKey: string): boolean {
+	if (!fs.existsSync(filePath)) return false;
+	let text: string;
+	try {
+		text = fs.readFileSync(filePath, "utf-8");
+	} catch {
+		return false;
+	}
+	const match = text.match(RC_LINE_RE);
+	if (!match) return false; // no existing line
+	if (match[3] === apiKey) return false;
+	const newText = text.replace(
+		RC_LINE_RE,
+		(_full, prefix) => `${prefix}"${apiKey}"`,
+	);
+	atomicWriteText(filePath, newText);
+	return true;
+}
+
+function atomicWriteText(filePath: string, content: string): void {
+	const dir = path.dirname(filePath);
+	const tmp = path.join(dir, `.${path.basename(filePath)}.${process.pid}.tmp`);
+	try {
+		fs.writeFileSync(tmp, content, "utf-8");
+		// Preserve permissions if original existed.
+		if (fs.existsSync(filePath)) {
+			try {
+				const mode = fs.statSync(filePath).mode & 0o777;
+				fs.chmodSync(tmp, mode);
+			} catch {
+				/* best-effort */
+			}
+		}
+		fs.renameSync(tmp, filePath);
+	} catch (err) {
+		try {
+			fs.unlinkSync(tmp);
+		} catch {
+			/* ignore */
+		}
+		throw err;
+	}
+}

cli/node/src/state.ts

@@ -5,6 +5,7 @@
 
 let _agentMode = false;
 let _currentCommand = "";
+let _pendingNotice = "";
 
 export function isAgentMode(): boolean {
 	return _agentMode;
@@ -21,3 +22,19 @@ export function getCurrentCommand(): string {
 export function setCurrentCommand(name: string): void {
 	_currentCommand = name;
 }
+
+/**
+ * Stash a Mem0 backend notice (Agent Mode unclaimed reminder) for end-of-
+ * command surfacing. Called from the platform backend after each response so
+ * the notice prints once per command regardless of how many sub-requests
+ * fired. Last-write-wins is fine — the message text is identical.
+ */
+export function captureNotice(notice: string | null | undefined): void {
+	if (notice) _pendingNotice = notice;
+}
+
+export function takeNotice(): string {
+	const msg = _pendingNotice;
+	_pendingNotice = "";
+	return msg;
+}

cli/node/src/telemetry.ts

@@ -115,6 +115,9 @@ export function captureEvent(
 			}
 		}
 
+		// M4: every cli.* event carries agent_mode based on the config flag
+		// (unclaimed Agent Mode key). This is the growth-doc property used to
+		// join init → add → search funnels in PostHog.
 		const payload = {
 			api_key: POSTHOG_API_KEY,
 			distinct_id: distinctId,
@@ -123,6 +126,7 @@ export function captureEvent(
 				source: "CLI",
 				language: "node",
 				cli_version: CLI_VERSION,
+				agent_mode: Boolean(config.platform.agentMode),
 				node_version: process.version,
 				os: process.platform,
 				...properties,

cli/node/tests/agent-mode.test.ts

@@ -0,0 +1,141 @@
+/**
+ * Parity tests for `mem0 init --agent` (Agent Mode bootstrap).
+ *
+ * Mirror of `cli/python/tests/test_agent_mode.py` — both files MUST stay
+ * in sync so that the Python and Node CLIs expose an identical surface
+ * for the Agent Mode entrypoint. If you add a flag here, add the same
+ * assertion on the Python side (and vice versa).
+ *
+ * Network-bound bootstrap is covered by the platform-side E2E suite
+ * (`backend/tests/e2e/test_05_agent_mode.py`); these tests only verify
+ * the CLI surface that ships in the binary.
+ */
+
+import { describe, it, expect } from "vitest";
+import { execSync } from "node:child_process";
+import fs from "node:fs";
+import os from "node:os";
+import path from "node:path";
+
+function run(
+  args: string[],
+  opts: { home?: string; env?: Record<string, string> } = {},
+): { stdout: string; stderr: string; exitCode: number } {
+  const env = { ...process.env };
+  for (const key of Object.keys(env)) {
+    if (key.startsWith("MEM0_")) delete env[key];
+  }
+  if (opts.home) env.HOME = opts.home;
+  if (opts.env) Object.assign(env, opts.env);
+
+  try {
+    const stdout = execSync(`npx tsx src/index.ts ${args.join(" ")}`, {
+      cwd: path.join(__dirname, ".."),
+      env,
+      encoding: "utf-8",
+      timeout: 15000,
+    });
+    return { stdout, stderr: "", exitCode: 0 };
+  } catch (e: any) {
+    return {
+      stdout: e.stdout ?? "",
+      stderr: e.stderr ?? "",
+      exitCode: e.status ?? 1,
+    };
+  }
+}
+
+function cleanHome(): string {
+  return fs.mkdtempSync(path.join(os.tmpdir(), "mem0-test-"));
+}
+
+describe("init flag surface", () => {
+  it("init --help lists --agent", () => {
+    const result = run(["init", "--help"]);
+    expect(result.exitCode).toBe(0);
+    expect(result.stdout).toContain("--agent");
+  });
+
+  it("init --help describes Agent Mode", () => {
+    const result = run(["init", "--help"]);
+    expect(result.exitCode).toBe(0);
+    // Description must mention what --agent actually does so an agent
+    // reading the help can self-discover the bootstrap entrypoint.
+    expect(
+      result.stdout.includes("Agent Mode") ||
+        result.stdout.toLowerCase().includes("unattended"),
+    ).toBe(true);
+  });
+
+  it("init --help lists --source", () => {
+    const result = run(["init", "--help"]);
+    expect(result.exitCode).toBe(0);
+    expect(result.stdout).toContain("--source");
+  });
+
+  it("init --help lists --email and --code", () => {
+    const result = run(["init", "--help"]);
+    expect(result.exitCode).toBe(0);
+    expect(result.stdout).toContain("--email");
+    expect(result.stdout).toContain("--code");
+  });
+});
+
+describe("argv preprocessing — --agent reaches init subcommand", () => {
+  // Regression for the bug where the global --agent JSON-alias swallowed
+  // the init-level --agent flag, making `mem0 init --agent` behave like
+  // the plain interactive wizard.
+
+  it("init --agent triggers bootstrap branch (not the wizard)", () => {
+    const home = cleanHome();
+    const result = run(["init", "--agent"], {
+      home,
+      env: {
+        MEM0_BASE_URL: "http://127.0.0.1:1", // blackhole
+        FORCE_COLOR: "0",
+      },
+    });
+    const combined = (result.stdout + result.stderr).toLowerCase();
+    // Either bootstrap-attempt error, or a connection/network error —
+    // both prove the --agent path executed (the wizard would prompt for
+    // input and succeed/hang, not surface a network error).
+    expect(
+      combined.includes("agent") ||
+        combined.includes("connect") ||
+        combined.includes("network") ||
+        combined.includes("fetch") ||
+        combined.includes("bootstrap"),
+    ).toBe(true);
+    fs.rmSync(home, { recursive: true, force: true });
+  });
+});
+
+describe("JSON envelope on network failure", () => {
+  it("init --agent --json does not leak a stack trace when backend is unreachable", () => {
+    const home = cleanHome();
+    const result = run(["init", "--agent", "--json"], {
+      home,
+      env: {
+        MEM0_BASE_URL: "http://127.0.0.1:1",
+        FORCE_COLOR: "0",
+      },
+    });
+    const combined = result.stdout + result.stderr;
+    // No raw Node stack should escape the agent-mode handler.
+    expect(combined).not.toMatch(/at \w+\s*\(.+\.ts:\d+/);
+    expect(combined).not.toContain("UnhandledPromiseRejection");
+    expect(result.exitCode).not.toBe(0);
+    fs.rmSync(home, { recursive: true, force: true });
+  });
+});
+
+describe("top-level help lists init", () => {
+  // `mem0 --help` must list `init` so agents walking the top-level help
+  // can discover the Agent Mode entrypoint without prior knowledge.
+
+  it("--help lists init", () => {
+    const result = run(["--help"]);
+    expect(result.exitCode).toBe(0);
+    expect(result.stdout).toContain("init");
+  });
+});

cli/node/tests/commands.test.ts

@@ -3,6 +3,7 @@
  */
 
 import { describe, it, expect, vi, beforeEach } from "vitest";
+import { Command } from "commander";
 import { createMockBackend } from "./setup.js";
 import type { Backend } from "../src/backend/base.js";
 import { setAgentMode } from "../src/state.js";
@@ -41,8 +42,6 @@ describe("cmdAdd", () => {
     await cmdAdd(mockBackend, "I prefer dark mode", {
       userId: "alice",
       immutable: false,
-      noInfer: false,
-
       output: "text",
     });
     expect(mockBackend.add).toHaveBeenCalledOnce();
@@ -54,8 +53,6 @@ describe("cmdAdd", () => {
       userId: "alice",
       messages: JSON.stringify([{ role: "user", content: "I love Python" }]),
       immutable: false,
-      noInfer: false,
-
       output: "text",
     });
     expect(mockBackend.add).toHaveBeenCalledOnce();
@@ -66,8 +63,6 @@ describe("cmdAdd", () => {
     await cmdAdd(mockBackend, "test", {
       userId: "alice",
       immutable: false,
-      noInfer: false,
-
       output: "json",
     });
     expect(output).toContain("results");
@@ -78,14 +73,59 @@ describe("cmdAdd", () => {
     await cmdAdd(mockBackend, "test", {
       userId: "alice",
       immutable: false,
-      noInfer: false,
-
       output: "quiet",
     });
     expect(output).not.toContain("dark mode");
   });
 });
 
+describe("cmdAdd forwards --no-infer (regression for #5261)", () => {
+  it("forwards infer: false when --no-infer is set", async () => {
+    const { cmdAdd } = await import("../src/commands/memory.js");
+    // `infer: false` is the shape Commander produces for `--no-infer`.
+    await cmdAdd(mockBackend, "store me verbatim", {
+      userId: "alice",
+      immutable: false,
+      infer: false,
+      output: "text",
+    });
+    expect(mockBackend.add).toHaveBeenCalledWith(
+      "store me verbatim",
+      undefined,
+      expect.objectContaining({ infer: false }),
+    );
+  });
+
+  it("forwards infer: true by default (flag absent)", async () => {
+    const { cmdAdd } = await import("../src/commands/memory.js");
+    await cmdAdd(mockBackend, "infer me", {
+      userId: "alice",
+      immutable: false,
+      output: "text",
+    });
+    expect(mockBackend.add).toHaveBeenCalledWith(
+      "infer me",
+      undefined,
+      expect.objectContaining({ infer: true }),
+    );
+  });
+
+  it("Commander stores --no-infer as opts.infer, not opts.noInfer", () => {
+    // Pins the assumption the fix relies on: Commander's `--no-X` option
+    // populates the positive camelCase key (`infer`), never `noInfer`.
+    const withFlag = new Command();
+    withFlag.option("--no-infer", "Skip inference, store raw.").action(() => {});
+    withFlag.parse(["--no-infer"], { from: "user" });
+    expect(withFlag.opts().infer).toBe(false);
+    expect(withFlag.opts().noInfer).toBeUndefined();
+
+    const withoutFlag = new Command();
+    withoutFlag.option("--no-infer", "Skip inference, store raw.").action(() => {});
+    withoutFlag.parse([], { from: "user" });
+    expect(withoutFlag.opts().infer).toBe(true);
+  });
+});
+
 describe("cmdAdd deduplicates PENDING", () => {
   const DUPLICATE_PENDING = {
     results: [
@@ -100,8 +140,6 @@ describe("cmdAdd deduplicates PENDING", () => {
     await cmdAdd(mockBackend, "test", {
       userId: "alice",
       immutable: false,
-      noInfer: false,
-
       output: "text",
     });
     expect(output.match(/Queued/g)?.length).toBe(1);
@@ -113,8 +151,6 @@ describe("cmdAdd deduplicates PENDING", () => {
     await cmdAdd(mockBackend, "test", {
       userId: "alice",
       immutable: false,
-      noInfer: false,
-
       output: "json",
     });
     const data = JSON.parse(output);
@@ -129,8 +165,6 @@ describe("cmdAdd deduplicates PENDING", () => {
     await cmdAdd(mockBackend, "test", {
       userId: "alice",
       immutable: false,
-      noInfer: false,
-
       output: "agent",
     });
     const data = JSON.parse(output);
@@ -315,8 +349,6 @@ describe("agent mode", () => {
     await cmdAdd(mockBackend, "test preference", {
       userId: "alice",
       immutable: false,
-      noInfer: false,
-
       output: "agent",
     });
     const parsed = JSON.parse(output.trim());

cli/node/tests/init-internals.test.ts

@@ -0,0 +1,168 @@
+/**
+ * Unit tests for init internals — decision tree primitives + plugin sync.
+ *
+ * Mirror of `cli/python/tests/test_init_internals.py`. Both files MUST stay
+ * in sync — if you add a behavioral assertion here, mirror it on the Python
+ * side and vice versa.
+ *
+ *  - `pingKey` must NOT treat network errors as "invalid key" (else a VPN
+ *    flap silently mints a new shadow over a working key).
+ *  - `plugin_sync` must only update entries that already exist, preserve
+ *    trailing newlines, and never mangle other lines.
+ */
+
+import fs from "node:fs";
+import os from "node:os";
+import path from "node:path";
+import { afterEach, beforeEach, describe, expect, it, vi } from "vitest";
+import { pingKey } from "../src/commands/init.js";
+import { updateClaudeSettings, updateShellRc } from "../src/plugin-sync.js";
+
+// ── pingKey ──────────────────────────────────────────────────────────────
+
+describe("pingKey — network vs auth distinction", () => {
+	const origFetch = globalThis.fetch;
+	afterEach(() => {
+		globalThis.fetch = origFetch;
+		vi.restoreAllMocks();
+	});
+
+	it("returns true for 200", async () => {
+		globalThis.fetch = vi.fn().mockResolvedValue({ status: 200 } as Response);
+		await expect(pingKey("k", "http://x")).resolves.toBe(true);
+	});
+
+	it("returns false for 401 (definitively invalid)", async () => {
+		globalThis.fetch = vi.fn().mockResolvedValue({ status: 401 } as Response);
+		await expect(pingKey("k", "http://x")).resolves.toBe(false);
+	});
+
+	it("returns false for 403 (definitively invalid)", async () => {
+		globalThis.fetch = vi.fn().mockResolvedValue({ status: 403 } as Response);
+		await expect(pingKey("k", "http://x")).resolves.toBe(false);
+	});
+
+	it("returns true for 5xx (transient upstream — prefer reuse)", async () => {
+		globalThis.fetch = vi.fn().mockResolvedValue({ status: 503 } as Response);
+		await expect(pingKey("k", "http://x")).resolves.toBe(true);
+	});
+
+	it("returns true on network error (prefer reuse over re-mint)", async () => {
+		globalThis.fetch = vi.fn().mockRejectedValue(new Error("ECONNREFUSED"));
+		await expect(pingKey("k", "http://x")).resolves.toBe(true);
+	});
+
+	it("returns true on timeout (prefer reuse)", async () => {
+		globalThis.fetch = vi.fn().mockRejectedValue(new Error("aborted"));
+		await expect(pingKey("k", "http://x")).resolves.toBe(true);
+	});
+});
+
+// ── updateShellRc ────────────────────────────────────────────────────────
+
+describe("updateShellRc — exists-only contract", () => {
+	let tmpDir: string;
+
+	beforeEach(() => {
+		tmpDir = fs.mkdtempSync(path.join(os.tmpdir(), "mem0-test-"));
+	});
+	afterEach(() => {
+		fs.rmSync(tmpDir, { recursive: true, force: true });
+	});
+
+	it("updates existing export and preserves trailing newline", () => {
+		const rc = path.join(tmpDir, ".zshrc");
+		fs.writeFileSync(rc, 'export MEM0_API_KEY="old"\n');
+		expect(updateShellRc(rc, "newkey")).toBe(true);
+		expect(fs.readFileSync(rc, "utf-8")).toBe('export MEM0_API_KEY="newkey"\n');
+	});
+
+	it("does NOT create a new export when none exists", () => {
+		const rc = path.join(tmpDir, ".zshrc");
+		fs.writeFileSync(rc, "alias ll='ls -la'\n");
+		expect(updateShellRc(rc, "newkey")).toBe(false);
+		expect(fs.readFileSync(rc, "utf-8")).toBe("alias ll='ls -la'\n");
+	});
+
+	it("preserves surrounding content", () => {
+		const rc = path.join(tmpDir, ".zshrc");
+		const original =
+			"# my zshrc\n" +
+			"alias ll='ls -la'\n" +
+			"export MEM0_API_KEY='old'\n" +
+			"export OTHER=keepme\n";
+		fs.writeFileSync(rc, original);
+		updateShellRc(rc, "newkey");
+		const after = fs.readFileSync(rc, "utf-8");
+		expect(after).toContain("alias ll='ls -la'\n");
+		expect(after).toContain("export OTHER=keepme\n");
+		expect(after).toContain("# my zshrc\n");
+		expect(after).toContain('export MEM0_API_KEY="newkey"\n');
+	});
+
+	it("is idempotent when value already matches", () => {
+		const rc = path.join(tmpDir, ".zshrc");
+		fs.writeFileSync(rc, 'export MEM0_API_KEY="same"\n');
+		expect(updateShellRc(rc, "same")).toBe(false);
+	});
+
+	it("is a no-op for missing files", () => {
+		const rc = path.join(tmpDir, ".zshrc"); // does not exist
+		expect(updateShellRc(rc, "x")).toBe(false);
+	});
+});
+
+// ── updateClaudeSettings ─────────────────────────────────────────────────
+
+describe("updateClaudeSettings — never creates entries", () => {
+	let tmpDir: string;
+
+	beforeEach(() => {
+		tmpDir = fs.mkdtempSync(path.join(os.tmpdir(), "mem0-test-"));
+	});
+	afterEach(() => {
+		fs.rmSync(tmpDir, { recursive: true, force: true });
+	});
+
+	it("does not create env block when none exists", () => {
+		const settings = path.join(tmpDir, "settings.json");
+		fs.writeFileSync(settings, JSON.stringify({ otherKey: 1 }));
+		expect(updateClaudeSettings(settings, "newkey")).toBe(false);
+		expect(JSON.parse(fs.readFileSync(settings, "utf-8"))).toEqual({
+			otherKey: 1,
+		});
+	});
+
+	it("does not create MEM0_API_KEY entry in existing env block", () => {
+		const settings = path.join(tmpDir, "settings.json");
+		fs.writeFileSync(settings, JSON.stringify({ env: { OTHER_KEY: "x" } }));
+		expect(updateClaudeSettings(settings, "newkey")).toBe(false);
+	});
+
+	it("updates existing entry and preserves siblings", () => {
+		const settings = path.join(tmpDir, "settings.json");
+		fs.writeFileSync(
+			settings,
+			JSON.stringify({ env: { MEM0_API_KEY: "old", OTHER: "y" } }, null, 2),
+		);
+		expect(updateClaudeSettings(settings, "fresh")).toBe(true);
+		const data = JSON.parse(fs.readFileSync(settings, "utf-8"));
+		expect(data.env.MEM0_API_KEY).toBe("fresh");
+		expect(data.env.OTHER).toBe("y");
+	});
+
+	it("is idempotent when value already matches", () => {
+		const settings = path.join(tmpDir, "settings.json");
+		fs.writeFileSync(
+			settings,
+			JSON.stringify({ env: { MEM0_API_KEY: "same" } }),
+		);
+		expect(updateClaudeSettings(settings, "same")).toBe(false);
+	});
+
+	it("is a no-op for malformed JSON", () => {
+		const settings = path.join(tmpDir, "settings.json");
+		fs.writeFileSync(settings, "{ this is not json");
+		expect(updateClaudeSettings(settings, "x")).toBe(false);
+	});
+});

cli/python/CHANGELOG.md

@@ -0,0 +1,36 @@
+# Changelog
+
+All notable changes to `mem0-cli` (Python) are documented here.
+
+The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
+and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
+
+## [0.2.7] — 2026-05-20
+
+### Added
+
+- `mem0 whoami` — print the active agent's `default_user_id` (the AGENTRUSH
+  leaderboard identifier). Reads from local config, no network call.
+- `mem0 agent-rush <add | search>` — subcommand group that wraps the new
+  `/v1/agent-rush/` platform endpoints for the 7-day AGENTRUSH game. Project
+  routing is implicit (resolved server-side); no flags exposed. Pretty-prints
+  platform error codes into actionable hints (e.g. `agentrush_search_first`
+  → "Run 3 'mem0 agent-rush search' commands before adding.").
+- PII safety prompt on first `mem0 agent-rush add`. Interactive runs require
+  explicit `y` to acknowledge that AGENTRUSH memories are public; the
+  acknowledgement is persisted in `~/.mem0/config.json` under
+  `agent_rush.acknowledged_at` so the prompt only appears once per machine.
+  Non-interactive (agent) invocations surface the warning to stderr without
+  blocking.
+- New config schema field: `agent_rush.acknowledged_at` (ISO timestamp,
+  empty until first interactive acknowledgement).
+
+### Changed
+
+- HTTP requests from the new agent-rush commands send `X-Mem0-Mode: agent-rush`
+  in addition to the existing source headers, so platform telemetry can split
+  game traffic from regular CLI usage.
+
+## [0.2.6] and earlier
+
+Unlogged historical releases. See git history under `cli/python/`.

cli/python/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "mem0-cli"
-version = "0.2.4"
+version = "0.2.7"
 description = "The official CLI for mem0 — the memory layer for AI agents"
 readme = "README.md"
 license = "Apache-2.0"

cli/python/src/mem0_cli/agent_detect.py

@@ -0,0 +1,36 @@
+"""Detect whether the CLI is being invoked from inside an AI-agent context.
+
+Used by `mem0 init` to auto-enter Agent Mode (Rule 3 bootstrap) when an
+agent runtime env var is present. The return value is a context **trigger
+only** — the canonical agent identity is self-declared by the agent via
+``--agent-caller <name>`` (Proof Editor-style) and never sniffed from env
+vars to fill the ``agent_caller`` field on the APIKey row.
+
+Returns a short name or None. The list is curated, not exhaustive — env
+vars we don't recognise fall through to None (caller treated as
+non-agent). Honest reporting depends on ``--agent-caller``; this list is
+just enough to enable the zero-friction auto-bootstrap UX.
+"""
+
+from __future__ import annotations
+
+import os
+
+_AGENT_CALLER_ENV: tuple[tuple[str, tuple[str, ...]], ...] = (
+    ("claude-code", ("CLAUDECODE", "CLAUDE_CODE")),
+    ("cursor", ("CURSOR_AGENT", "CURSOR_SESSION_ID")),
+    ("codex", ("CODEX_CLI", "OPENAI_CODEX")),
+    ("cline", ("CLINE_AGENT", "CLINE")),
+    ("continue", ("CONTINUE_AGENT", "CONTINUE_SESSION")),
+    ("aider", ("AIDER_SESSION",)),
+    ("goose", ("GOOSE_AGENT",)),
+    ("windsurf", ("WINDSURF_AGENT",)),
+)
+
+
+def detect_agent_caller() -> str | None:
+    """Return a canonical agent name if any agent env var is set, else None."""
+    for name, env_vars in _AGENT_CALLER_ENV:
+        if any(os.environ.get(v) for v in env_vars):
+            return name
+    return None

cli/python/src/mem0_cli/app.py

@@ -237,6 +237,14 @@ def main_callback(
         cmd_version()
         raise typer.Exit()
     if ctx.invoked_subcommand:
+        # Stash the active subcommand name so the JSON error envelope
+        # (print_error in agent mode) can report which command failed
+        # instead of an empty `"command": ""` field.
+        from mem0_cli.state import set_current_command
+
+        set_current_command(ctx.invoked_subcommand)
+    if ctx.invoked_subcommand and ctx.invoked_subcommand != "init":
+        # init fires its own telemetry from init_cmd.run_init with full M1-M6 props.
         _fire_telemetry(ctx.invoked_subcommand)
 
 
@@ -851,6 +859,19 @@ def init(
     force: bool = typer.Option(
         False, "--force", help="Overwrite existing config without confirmation."
     ),
+    agent_signal: bool = typer.Option(
+        False, "--agent", help="Bootstrap an unattended Agent Mode account (no email required)."
+    ),
+    source: str | None = typer.Option(
+        None,
+        "--source",
+        help="Channel attribution for signup (e.g. github, hn, ph).",
+    ),
+    agent_caller: str | None = typer.Option(
+        None,
+        "--agent-caller",
+        help="Self-declared agent identity (e.g. claude-code, cursor). Used with --agent to attribute Agent Mode signups.",
+    ),
 ) -> None:
     """Interactive setup wizard for mem0 CLI.
 
@@ -859,10 +880,97 @@ def init(
       mem0 init --api-key m0-xxx --user-id alice
       mem0 init --email alice@company.com
       mem0 init --email alice@company.com --code 482901
+      mem0 init --agent --agent-caller claude-code   # AI agent self-identifies on Agent Mode bootstrap
+      mem0 init --email alice@company.com  # Claims an existing Agent Mode key when one is present
     """
     from mem0_cli.commands.init_cmd import run_init
 
-    run_init(api_key=api_key, user_id=user_id, email=email, code=code, force=force)
+    run_init(
+        api_key=api_key,
+        user_id=user_id,
+        email=email,
+        code=code,
+        force=force,
+        source=source,
+        agent=agent_signal,
+        agent_caller=agent_caller,
+    )
+
+
+@app.command(rich_help_panel="Setup")
+def identify(
+    name: str = typer.Argument(..., help="Agent identity (e.g. claude-code, cursor, my-bot)."),
+) -> None:
+    """Tag your active Agent Mode key with the AI agent that's using it.
+
+    Run this once after `mem0 init --agent` if you didn't pass --agent-caller.
+    Idempotent — re-running just overwrites the value.
+
+    Example:
+      mem0 identify claude-code
+    """
+    from mem0_cli.commands.identify_cmd import run_identify
+
+    run_identify(name)
+
+
+@app.command(name="whoami", rich_help_panel="Setup")
+def whoami_cmd() -> None:
+    """Print your AGENTRUSH identifier (default_user_id).
+
+    Example:
+      mem0 whoami
+    """
+    from mem0_cli.commands.whoami_cmd import run_whoami
+
+    run_whoami()
+
+
+# ── AGENTRUSH sub-app ─────────────────────────────────────────────────────
+
+agent_rush_app = typer.Typer(
+    name="agent-rush",
+    help="AGENTRUSH game commands",
+    no_args_is_help=True,
+    rich_markup_mode="rich",
+)
+
+
+@agent_rush_app.callback(invoke_without_command=True)
+def _agent_rush_callback(ctx: typer.Context) -> None:
+    if ctx.invoked_subcommand:
+        _fire_telemetry(f"agent-rush.{ctx.invoked_subcommand}")
+
+
+@agent_rush_app.command(name="add")
+def agent_rush_add(
+    content: str = typer.Argument(..., help="Memory content (50-1000 characters, no URLs)."),
+) -> None:
+    """Submit a memory to AGENTRUSH.
+
+    Example:
+      mem0 agent-rush add "I enjoy solving constraint-satisfaction problems."
+    """
+    from mem0_cli.commands.agent_rush_cmd import run_agent_rush_add
+
+    run_agent_rush_add(content)
+
+
+@agent_rush_app.command(name="search")
+def agent_rush_search(
+    query: str = typer.Argument(..., help="Search query."),
+) -> None:
+    """Search AGENTRUSH memories.
+
+    Example:
+      mem0 agent-rush search "constraint satisfaction"
+    """
+    from mem0_cli.commands.agent_rush_cmd import run_agent_rush_search
+
+    run_agent_rush_search(query)
+
+
+app.add_typer(agent_rush_app, name="agent-rush", rich_help_panel="Setup")
 
 
 # (entity_app registered at module level, below sub-group definitions)
@@ -1198,11 +1306,28 @@ def main() -> None:
     import sys
 
     # Allow --json/--agent anywhere in the command line (not just before subcommand).
-    _json_flags = {"--json", "--agent"}
-    if any(a in _json_flags for a in sys.argv[1:]):
+    # Special case: `mem0 init --agent` is a subcommand flag (Agent Mode bootstrap)
+    # consumed by init_cmd, not a global JSON-output toggle — leave it in argv.
+    argv_rest = sys.argv[1:]
+    is_init = "init" in argv_rest
+    _global_flags = {"--json"} if is_init else {"--json", "--agent"}
+    if any(a in _global_flags for a in argv_rest):
         from mem0_cli.state import set_agent_mode
 
         set_agent_mode(True)
-        sys.argv = [sys.argv[0]] + [a for a in sys.argv[1:] if a not in _json_flags]
+        sys.argv = [sys.argv[0]] + [a for a in argv_rest if a not in _global_flags]
 
-    app()
+    try:
+        app()
+    finally:
+        # Surface any unclaimed Agent Mode notice once per command, after the
+        # primary output. In JSON/agent mode the notice is folded into the
+        # envelope by format_json_envelope, so skip the stderr banner there
+        # to avoid duplicate output.
+        from mem0_cli.state import is_agent_mode, take_notice
+
+        notice = take_notice()
+        if notice and not is_agent_mode():
+            from rich.console import Console
+
+            Console(stderr=True).print(f"\n[yellow]🔔 {notice}[/yellow]\n")

cli/python/src/mem0_cli/backend/platform.py

@@ -30,7 +30,7 @@ class PlatformBackend(Backend):
         )
 
     def _request(self, method: str, path: str, **kwargs: Any) -> Any:
-        from mem0_cli.state import is_agent_mode
+        from mem0_cli.state import capture_notice, is_agent_mode
 
         self._client.headers["X-Mem0-Caller-Type"] = "agent" if is_agent_mode() else "user"
         resp = self._client.request(method, path, **kwargs)
@@ -48,7 +48,26 @@ class PlatformBackend(Backend):
         resp.raise_for_status()
         if resp.status_code == 204:
             return {}
-        return resp.json()
+        data = resp.json()
+
+        # Pull the unclaimed-Agent-Mode notice out of the body (or the header
+        # fallback for endpoints that return non-dict / non-dict-leading
+        # payloads) and stash it for end-of-command surfacing.
+        notice = None
+        if isinstance(data, dict) and "mem0_notice" in data:
+            notice = data.pop("mem0_notice")
+        elif (
+            isinstance(data, list)
+            and data
+            and isinstance(data[0], dict)
+            and "mem0_notice" in data[0]
+        ):
+            notice = data[0].pop("mem0_notice")
+        if notice is None:
+            notice = resp.headers.get("X-Mem0-Notice-Message") or None
+        capture_notice(notice)
+
+        return data
 
     def add(
         self,

cli/python/src/mem0_cli/branding.py

@@ -87,10 +87,12 @@ def print_error(console: Console, message: str, hint: str | None = None) -> None
         }
         print(_json.dumps(envelope))
         return
+    from rich.markup import escape
+
     sym = _sym("✗", "[error]")
-    console.print(f"[{ERROR_COLOR}]{sym} Error:[/] {message}")
+    console.print(f"[{ERROR_COLOR}]{sym} Error:[/] {escape(str(message))}")
     if hint:
-        console.print(f"  [{DIM_COLOR}]{hint}[/]")
+        console.print(f"  [{DIM_COLOR}]{escape(str(hint))}[/]")
 
 
 def print_warning(console: Console, message: str) -> None:

cli/python/src/mem0_cli/commands/agent_mode_cmd.py

@@ -0,0 +1,239 @@
+"""Agent Mode commands — bootstrap (unattended signup) and claim (OTP-based human upgrade)."""
+
+from __future__ import annotations
+
+import json
+import sys
+from datetime import datetime, timezone
+from typing import Any
+
+import httpx
+import typer
+from rich.console import Console
+from rich.prompt import Prompt
+
+from mem0_cli.branding import (
+    BRAND_COLOR,
+    DIM_COLOR,
+    print_error,
+    print_success,
+)
+from mem0_cli.config import Mem0Config, save_config
+
+console = Console()
+err_console = Console(stderr=True)
+
+_SOURCE_HEADERS = {
+    "X-Mem0-Source": "cli",
+    "X-Mem0-Client-Language": "python",
+}
+
+
+def _validate_envelope(envelope: Any) -> None:
+    """Defend against partial/malformed backend responses.
+
+    A backend regression that returns ``{"api_key": null}`` would otherwise be
+    silently persisted, producing confusing downstream errors far from the
+    source. Fail fast with a clear message if the required fields are missing.
+    """
+    if not isinstance(envelope, dict):
+        print_error(err_console, "Bootstrap response was not a JSON object.")
+        raise typer.Exit(1)
+    for field in ("api_key", "default_user_id"):
+        value = envelope.get(field)
+        if not isinstance(value, str) or not value:
+            print_error(
+                err_console,
+                f"Bootstrap response missing required field {field!r} — please update the CLI.",
+            )
+            raise typer.Exit(1)
+
+
+def bootstrap_via_backend(
+    config: Mem0Config,
+    *,
+    source: str | None = None,
+    agent_caller: str | None = None,
+) -> None:
+    """POST /api/v1/auth/agent_mode/ and mutate config in place.
+
+    Args:
+        config: Mem0Config mutated in place with the new platform values.
+        source: ``--source`` flag passthrough (analytics tag, free-form).
+        agent_caller: Self-declared agent identity passed via ``--agent-caller``
+            (e.g. ``claude-code``, ``cursor``). May be None when the caller
+            omitted the flag; the agent can backfill later via
+            ``mem0 identify <name>``. Sent to the backend in the request body
+            and saved into ``platform.agent_caller`` for local introspection.
+
+    Raises typer.Exit(1) on failure.
+    """
+    base_url = (config.platform.base_url or "https://api.mem0.ai").rstrip("/")
+    body: dict[str, Any] = {}
+    if source:
+        body["source"] = source
+    if agent_caller:
+        body["agent_caller"] = agent_caller
+
+    try:
+        with httpx.Client(timeout=30.0) as client:
+            resp = client.post(
+                f"{base_url}/api/v1/auth/agent_mode/",
+                headers={**_SOURCE_HEADERS, "Content-Type": "application/json"},
+                json=body,
+            )
+    except httpx.HTTPError as exc:
+        print_error(err_console, f"Network error contacting Mem0: {exc}")
+        raise typer.Exit(1) from exc
+
+    if resp.status_code == 429:
+        print_error(err_console, "Rate-limited. Try again in a few minutes.")
+        raise typer.Exit(1)
+    if resp.status_code == 503:
+        print_error(err_console, "Agent Mode is temporarily disabled. Try again later.")
+        raise typer.Exit(1)
+    if resp.status_code != 200:
+        detail = resp.text
+        try:
+            err_body = resp.json()
+            detail = err_body.get("error") or err_body.get("detail") or resp.text
+        except (json.JSONDecodeError, ValueError, AttributeError):
+            pass
+        # Backend's @ratelimit decorator raises PermissionDenied, which DRF
+        # translates to a generic 403 "You do not have permission to perform
+        # this action." That's opaque — surface as the rate-limit it actually is.
+        if resp.status_code == 403 and "permission" in str(detail).lower():
+            print_error(
+                err_console,
+                "Daily Agent Mode signup limit reached for this network (5/day). Try again from a different IP or after midnight UTC.",
+            )
+            raise typer.Exit(1)
+        print_error(err_console, f"Bootstrap failed: {detail}")
+        raise typer.Exit(1)
+
+    envelope = resp.json()
+    _validate_envelope(envelope)
+    config.platform.api_key = envelope["api_key"]
+    config.platform.base_url = base_url
+    config.platform.agent_mode = True
+    config.platform.created_via = "agent_mode"
+    config.platform.agent_caller = agent_caller or ""
+    config.platform.claimed_at = ""
+    config.platform.default_user_id = envelope["default_user_id"]
+    # Adopt the slug-derived user_id as the default scope for memory ops.
+    config.defaults.user_id = envelope["default_user_id"]
+    save_config(config)
+
+    print_success(console, f"Agent Mode active. Default user_id: {envelope['default_user_id']}")
+    notice = envelope.get("mem0_notice")
+    if notice:
+        console.print(f"\n[yellow]🔔 {notice}[/yellow]\n")
+    else:
+        # Fallback if the backend hasn't deployed the unified notice yet.
+        claim_cmd = envelope.get("claim_command", "mem0 init --email <your-email>")
+        console.print(f"  [{DIM_COLOR}]To claim this account later: {claim_cmd}[/]")
+
+    if not agent_caller:
+        console.print(
+            f"  [{DIM_COLOR}]If you are an AI agent, identify yourself: "
+            f"`mem0 identify <your-name>` (e.g. claude-code, cursor).[/]"
+        )
+
+
+def claim_via_otp(config: Mem0Config, *, email: str, code: str | None = None) -> None:
+    """Claim an existing Agent Mode account via OTP — no browser, no polling.
+
+    Reuses the standard email-code flow (`/api/v1/auth/email_code/` then
+    `/.../verify/`) and adds the local agent-mode API key in the verify body
+    as `agent_mode_api_key`. Backend's `verify_email_code` runs the
+    upgrade-in-place transaction inline and returns claim result.
+
+    On success: flips `platform.agent_mode=false`, sets `claimed_at`, stamps
+    `user_email`. The api_key value itself never changes.
+    """
+    base_url = (config.platform.base_url or "https://api.mem0.ai").rstrip("/")
+    if not config.platform.api_key or not config.platform.agent_mode:
+        print_error(
+            err_console,
+            "This command requires an active Agent Mode config. Run `mem0 init` first.",
+        )
+        raise typer.Exit(1)
+
+    raw_key = config.platform.api_key
+
+    with httpx.Client(timeout=30.0) as client:
+        # Step 1: request OTP (unless --code provided)
+        if not code:
+            send = client.post(
+                f"{base_url}/api/v1/auth/email_code/",
+                headers={**_SOURCE_HEADERS, "Content-Type": "application/json"},
+                json={"email": email},
+            )
+            if send.status_code == 429:
+                print_error(err_console, "Too many attempts. Try again in a few minutes.")
+                raise typer.Exit(1)
+            if send.status_code != 200:
+                try:
+                    detail = send.json().get("error", send.text)
+                except Exception:
+                    detail = send.text
+                print_error(err_console, f"Failed to send code: {detail}")
+                raise typer.Exit(1)
+
+            print_success(console, f"Verification code sent to {email}. Check your inbox.")
+
+            if not sys.stdin.isatty():
+                print_error(
+                    err_console,
+                    "No --code provided and terminal is non-interactive.",
+                    hint=f"Re-run: mem0 init --email {email} --code <code>",
+                )
+                raise typer.Exit(1)
+
+            console.print()
+            code = Prompt.ask(f"  [{BRAND_COLOR}]Verification Code[/]")
+            if not code:
+                print_error(err_console, "Code is required.")
+                raise typer.Exit(1)
+
+        # Step 2: verify + claim in one shot
+        verify = client.post(
+            f"{base_url}/api/v1/auth/email_code/verify/",
+            headers={**_SOURCE_HEADERS, "Content-Type": "application/json"},
+            json={
+                "email": email,
+                "code": code.strip(),
+                "agent_mode_api_key": raw_key,
+            },
+        )
+
+    if verify.status_code != 200:
+        try:
+            err_body = verify.json()
+            detail = err_body.get("error", verify.text)
+            code_str = err_body.get("code", "")
+        except (json.JSONDecodeError, ValueError, AttributeError):
+            detail = verify.text
+            code_str = ""
+        print_error(err_console, f"Claim failed: {detail}")
+        if code_str == "email_already_claimed":
+            console.print(
+                f"  [{DIM_COLOR}]Tip: this email already has a Mem0 account. Sign in at app.mem0.ai with your existing credentials.[/]"
+            )
+        raise typer.Exit(1)
+
+    claim_body = verify.json()
+    if not claim_body.get("claimed"):
+        print_error(err_console, f"Unexpected verify response: {claim_body}")
+        raise typer.Exit(1)
+
+    config.platform.agent_mode = False
+    config.platform.claimed_at = claim_body.get("claimed_at") or _utcnow_iso()
+    config.platform.user_email = email
+    config.platform.created_via = "email"
+    save_config(config)
+    print_success(console, f"Agent claimed to {email}. Your API key is unchanged.")
+
+
+def _utcnow_iso() -> str:
+    return datetime.now(timezone.utc).isoformat()

cli/python/src/mem0_cli/commands/agent_rush_cmd.py

@@ -0,0 +1,132 @@
+"""mem0 agent-rush — AGENTRUSH game commands.
+
+Wraps the platform's /v1/agent-rush/{memories/, memories/search/} endpoints.
+Hardcoded routing; no flags needed.
+"""
+
+from __future__ import annotations
+
+import sys
+from datetime import datetime, timezone
+
+import httpx
+import typer
+from rich.console import Console
+
+from mem0_cli.branding import print_error, print_success
+from mem0_cli.config import load_config, save_config
+
+console = Console()
+err_console = Console(stderr=True)
+
+_PII_WARNING_LINES = (
+    "",
+    "[yellow]⚠️  AGENTRUSH memories are PUBLIC — visible to any other player.[/yellow]",
+    "[yellow]   Do not include real names, emails, secrets, work content, or PII.[/yellow]",
+    "",
+)
+
+_SOURCE_HEADERS = {
+    "X-Mem0-Source": "cli",
+    "X-Mem0-Client-Language": "python",
+    "X-Mem0-Mode": "agent-rush",
+}
+
+_ERROR_HINTS = {
+    "agentrush_search_first": "Run 3 'mem0 agent-rush search' commands before adding.",
+    "agentrush_search_quota": "You've used your 3 lifetime searches.",
+    "agentrush_add_quota": "You've used your 3 lifetime adds.",
+    "agentrush_not_agent_mode": "Re-run 'mem0 init --agent' to bootstrap an agent-mode key.",
+    "agentrush_length": "Memory text must be 50-1000 characters.",
+    "agentrush_no_urls": "URLs are not allowed.",
+    "agentrush_blocklist": "Content contains a blocked term.",
+    "agentrush_global_quota": "Event-wide cap reached. Try again later.",
+    "agentrush_not_provisioned": "AGENTRUSH is not provisioned in this environment.",
+}
+
+
+def _call(path: str, body: dict) -> dict:
+    config = load_config()
+    if not config.platform.api_key:
+        print_error(err_console, "Not initialized. Run `mem0 init --agent` first.")
+        raise typer.Exit(1)
+    base_url = (config.platform.base_url or "https://api.mem0.ai").rstrip("/")
+    try:
+        with httpx.Client(timeout=30.0) as client:
+            resp = client.post(
+                f"{base_url}{path}",
+                headers={
+                    **_SOURCE_HEADERS,
+                    "Authorization": f"Token {config.platform.api_key}",
+                    "Content-Type": "application/json",
+                },
+                json=body,
+            )
+    except httpx.HTTPError as exc:
+        print_error(err_console, f"Network error: {exc}")
+        raise typer.Exit(1) from exc
+    try:
+        data = resp.json()
+    except Exception:
+        data = {}
+    if resp.status_code >= 400:
+        code = (
+            (data.get("error") or {}).get("code", "unknown")
+            if isinstance(data, dict)
+            else "unknown"
+        )
+        print_error(err_console, f"AGENTRUSH error: {code}")
+        hint = _ERROR_HINTS.get(code)
+        if hint:
+            console.print(f"  [dim]{hint}[/dim]")
+        raise typer.Exit(1)
+    return data
+
+
+def _ensure_warning_acknowledged() -> None:
+    """Block the first interactive add on the PII warning; pass-through for agents.
+
+    Interactive (TTY): show prompt, require explicit 'y', persist
+    `agent_rush.acknowledged_at` so we never ask the same machine twice.
+
+    Non-interactive (no TTY — typical when an agent runs the CLI): surface
+    the warning to stderr for the human reading the agent transcript and
+    proceed without prompting (agents can't answer y/N).
+    """
+    config = load_config()
+    if config.agent_rush.acknowledged_at:
+        return
+
+    is_tty = sys.stdin.isatty() and sys.stdout.isatty()
+    if not is_tty:
+        for line in _PII_WARNING_LINES:
+            err_console.print(line)
+        return
+
+    for line in _PII_WARNING_LINES:
+        console.print(line)
+    answer = typer.prompt("   Continue? [y/N]", default="N", show_default=False).strip().lower()
+    if answer not in ("y", "yes"):
+        print_error(err_console, "Aborted.")
+        raise typer.Exit(1)
+
+    config.agent_rush.acknowledged_at = datetime.now(timezone.utc).isoformat()
+    save_config(config)
+
+
+def run_agent_rush_add(content: str) -> None:
+    _ensure_warning_acknowledged()
+    result = _call("/v1/agent-rush/memories/", {"content": content})
+    event_id = result.get("event_id", "?")
+    print_success(console, f"Memory submitted (event_id: {event_id})")
+
+
+def run_agent_rush_search(query: str) -> None:
+    result = _call("/v1/agent-rush/memories/search/", {"query": query})
+    memories = result.get("results") or result.get("memories") or []
+    if not memories:
+        console.print("[dim](no results)[/dim]")
+        return
+    for i, m in enumerate(memories[:5], start=1):
+        text = m.get("memory") if isinstance(m, dict) else str(m)
+        console.print(f"  {i}. {text}")

cli/python/src/mem0_cli/commands/identify_cmd.py

@@ -0,0 +1,75 @@
+"""mem0 identify — declare which agent owns the current agent-mode key.
+
+Used when `mem0 init --agent` ran without --agent-caller, so the backend
+saved agent_caller=NULL. The agent re-runs `mem0 identify <name>` to PATCH
+its own row with its real identity. Idempotent — running it again just
+overwrites.
+"""
+
+from __future__ import annotations
+
+import httpx
+import typer
+from rich.console import Console
+
+from mem0_cli.branding import print_error, print_success
+from mem0_cli.config import load_config, save_config
+
+console = Console()
+err_console = Console(stderr=True)
+
+_SOURCE_HEADERS = {
+    "X-Mem0-Source": "cli",
+    "X-Mem0-Client-Language": "python",
+}
+
+
+def run_identify(name: str) -> None:
+    """PATCH the active agent-mode key's agent_caller field."""
+    config = load_config()
+    if not config.platform.api_key:
+        print_error(
+            err_console,
+            "No API key configured. Run `mem0 init --agent` first.",
+        )
+        raise typer.Exit(1)
+    if not config.platform.agent_mode:
+        print_error(
+            err_console,
+            "This command only works on unclaimed agent-mode keys.",
+        )
+        raise typer.Exit(1)
+
+    name = (name or "").strip()
+    if not name:
+        print_error(err_console, "Agent name is required.")
+        raise typer.Exit(1)
+
+    base_url = (config.platform.base_url or "https://api.mem0.ai").rstrip("/")
+    try:
+        with httpx.Client(timeout=30.0) as client:
+            resp = client.patch(
+                f"{base_url}/api/v1/auth/agent_mode/caller/",
+                headers={
+                    **_SOURCE_HEADERS,
+                    "Authorization": f"Token {config.platform.api_key}",
+                    "Content-Type": "application/json",
+                },
+                json={"agent_caller": name},
+            )
+    except httpx.HTTPError as exc:
+        print_error(err_console, f"Network error: {exc}")
+        raise typer.Exit(1) from exc
+
+    if resp.status_code != 200:
+        try:
+            detail = resp.json().get("error", resp.text)
+        except Exception:
+            detail = resp.text
+        print_error(err_console, f"Identify failed: {detail}")
+        raise typer.Exit(1)
+
+    canonical = resp.json().get("agent_caller", name)
+    config.platform.agent_caller = canonical
+    save_config(config)
+    print_success(console, f"Identified as {canonical}.")

cli/python/src/mem0_cli/commands/init_cmd.py

@@ -103,6 +103,25 @@ def _validate_email(email: str) -> None:
         raise typer.Exit(1)
 
 
+def _ping_key(api_key: str, base_url: str, timeout: float = 5.0) -> bool:
+    """Validate api_key against /v1/ping/.
+
+    Returns False ONLY on a definitive "invalid key" signal (HTTP 401 / 403).
+    Network errors, timeouts, and 5xx responses return True so we prefer
+    reusing an existing key over silently minting a new shadow on a transient
+    blip (which would also clobber config + plugin-sync targets).
+    """
+    try:
+        resp = httpx.get(
+            f"{base_url.rstrip('/')}/v1/ping/",
+            headers={"Authorization": f"Token {api_key}"},
+            timeout=timeout,
+        )
+    except httpx.HTTPError:
+        return True  # unknown — prefer reuse
+    return resp.status_code not in (401, 403)
+
+
 def _email_login(
     email: str,
     code: str | None,
@@ -182,21 +201,143 @@ def run_init(
     email: str | None = None,
     code: str | None = None,
     force: bool = False,
+    source: str | None = None,
+    agent: bool = False,
+    agent_caller: str | None = None,
 ) -> None:
     """Interactive setup wizard for mem0 CLI.
 
     When both *api_key* and *user_id* are supplied, all prompts are skipped
     (non-interactive mode).  When running in a non-TTY without the required
     flags, an error message is printed.
+
+    Agent Mode dispatch (no email/api-key flags):
+      - If existing config has an active API key → reuse (existing_key path).
+      - Else if any positive agent signal (--agent, --json global, agent env
+        var, or `agent` flag) → POST /api/v1/auth/agent_mode/ and write config.
+      - Else fall through to the interactive wizard.
+
+    Claim dispatch:
+      - If `--email` is set AND existing config has `agent_mode=true`, run the
+        claim device-flow against the existing key instead of minting a new
+        email-based key.
     """
+    from mem0_cli.agent_detect import detect_agent_caller
+    from mem0_cli.commands.agent_mode_cmd import bootstrap_via_backend, claim_via_otp
+    from mem0_cli.state import is_agent_mode as _global_agent_mode
+    from mem0_cli.telemetry import capture_event
+
+    def _fire_init(mode: str, *, claimed: bool = False) -> None:
+        """Fire cli.init telemetry with M1-M6 properties."""
+        props: dict = {"command": "init", "mode": mode}
+        if agent_caller:
+            # Self-declared via --agent-caller; not sniffed from env vars.
+            props["agent_caller"] = agent_caller
+        if source:
+            props["signup_source"] = source
+        if claimed:
+            props["claimed_agent_mode"] = True
+        capture_event("cli.init", props)
+
     config = Mem0Config()
 
     base_url = os.environ.get("MEM0_BASE_URL", config.platform.base_url or DEFAULT_BASE_URL)
+    config.platform.base_url = base_url
 
     if code and not email:
         print_error(err_console, "--code requires --email.")
         raise typer.Exit(1)
 
+    # ── Email + existing agent-mode config → claim flow ─────────────────
+    if email and CONFIG_FILE.exists():
+        existing = load_config()
+        if existing.platform.agent_mode and existing.platform.api_key:
+            email = email.strip().lower()
+            _validate_email(email)
+            print_info(console, f"Claiming Agent Mode account to {email}...")
+            claim_via_otp(existing, email=email, code=code)
+            _fire_init("email", claimed=True)
+            return
+
+    # ── Agent Mode path runs BEFORE the existing-config guard ──────────
+    # Rules 1/2 REUSE a valid existing key (not overwrite), so we must
+    # short-circuit before the guard prompts. Rule 3 mints only when there
+    # is no valid key to reuse — in that case overwriting is correct.
+    _agent_ctx = agent or _global_agent_mode() or (detect_agent_caller() is not None)
+    if not api_key and not email and _agent_ctx:
+        from mem0_cli.output import format_json_envelope
+        from mem0_cli.state import is_agent_mode as _is_json_mode
+
+        def _emit_reuse(source: str) -> None:
+            if _is_json_mode():
+                format_json_envelope(
+                    console,
+                    command="init",
+                    data={
+                        "api_key_saved": False,
+                        "api_key_source": source,
+                        "agent_mode": False,
+                        "message": "Existing Mem0 API key found and reused. No Agent Mode key was created.",
+                    },
+                )
+            else:
+                msg = (
+                    "Existing MEM0_API_KEY is valid; reusing it. No new Agent Mode key was minted."
+                    if source == "env"
+                    else "Existing API key in config is valid; reusing it. No new Agent Mode key was minted."
+                )
+                print_success(console, msg)
+
+        def _maybe_identify(key: str) -> None:
+            """Best-effort PATCH agent_caller when --agent-caller is supplied on a
+            reused key. Silent no-op on any failure — reuse must not break.
+            """
+            if not agent_caller:
+                return
+            try:
+                resp = httpx.patch(
+                    f"{base_url.rstrip('/')}/api/v1/auth/agent_mode/caller/",
+                    headers={
+                        "Authorization": f"Token {key}",
+                        "Content-Type": "application/json",
+                    },
+                    json={"agent_caller": agent_caller},
+                    timeout=10.0,
+                )
+                # Also reflect in local config so introspection matches backend.
+                if resp.status_code == 200 and CONFIG_FILE.exists():
+                    try:
+                        cfg = load_config()
+                        cfg.platform.agent_caller = resp.json().get("agent_caller", agent_caller)
+                        save_config(cfg)
+                    except Exception:
+                        pass
+            except httpx.HTTPError:
+                pass
+
+        # Rule 1: env MEM0_API_KEY valid → reuse, no new key.
+        _env_key = (os.environ.get("MEM0_API_KEY") or "").strip()
+        if _env_key and _ping_key(_env_key, base_url):
+            _maybe_identify(_env_key)
+            _emit_reuse("env")
+            _fire_init("existing_key")
+            return
+        # Rule 2: existing config api_key valid → reuse.
+        if CONFIG_FILE.exists():
+            _existing = load_config()
+            if _existing.platform.api_key and _ping_key(_existing.platform.api_key, base_url):
+                _maybe_identify(_existing.platform.api_key)
+                _emit_reuse("config")
+                _fire_init("existing_key")
+                return
+        # Rule 3: mint a fresh shadow (no valid key to reuse).
+        # agent_caller is the agent's self-declared identity from --agent-caller
+        # (Proof Editor-style). Env-var auto-detect is still used above to
+        # decide we're in an agent context, but never to fill identity.
+        bootstrap_via_backend(config, source=source, agent_caller=agent_caller)
+        _fire_init("agent")
+        return
+
     # Warn if an existing config with an API key would be overwritten
     if not force and CONFIG_FILE.exists():
         existing = load_config()
@@ -242,6 +383,7 @@ def run_init(
         config.platform.api_key = api_key_val
         config.platform.base_url = base_url
         config.platform.user_email = email
+        config.platform.created_via = "email"
         config.defaults.user_id = (
             user_id or os.environ.get("USER") or os.environ.get("USERNAME") or "mem0-cli"
         )
@@ -258,6 +400,8 @@ def run_init(
         return
 
     # ── API key flow (existing) ───────────────────────────────────────
+    # (Agent Mode branch runs earlier — see above, before the existing-config
+    # guard, so Rules 1/2 can REUSE a valid key without prompting overwrite.)
 
     # Non-TTY: resolve defaults so partial flags work in pipelines / CI
     if not sys.stdin.isatty():
@@ -265,7 +409,7 @@ def run_init(
             print_error(
                 err_console,
                 "Non-interactive terminal detected and --api-key is required.",
-                hint="Run: mem0 init --api-key <key> [--user-id <id>]",
+                hint="Run: mem0 init --api-key <key>, --email <addr>, or --agent for unattended Agent Mode bootstrap.",
             )
             raise typer.Exit(1)
         user_id = user_id or os.environ.get("USER") or os.environ.get("USERNAME") or "mem0-cli"
@@ -273,6 +417,7 @@ def run_init(
     # Fully non-interactive when both flags provided
     if api_key and user_id:
         config.platform.api_key = api_key
+        config.platform.created_via = "api_key"
         config.defaults.user_id = user_id
         _validate_platform(config)
         save_config(config)
@@ -313,6 +458,7 @@ def run_init(
             config.platform.api_key = api_key_val
             config.platform.base_url = base_url
             config.platform.user_email = email_addr
+            config.platform.created_via = "email"
             config.defaults.user_id = (
                 user_id or os.environ.get("USER") or os.environ.get("USERNAME") or "mem0-cli"
             )
@@ -331,6 +477,7 @@ def run_init(
     # API key flow
     if api_key:
         config.platform.api_key = api_key
+        config.platform.created_via = "api_key"
     else:
         _setup_platform(config)
 
@@ -370,6 +517,7 @@ def _setup_platform(config: Mem0Config) -> None:
         raise typer.Exit(1)
 
     config.platform.api_key = api_key
+    config.platform.created_via = "api_key"
 
 
 def _setup_defaults(config: Mem0Config) -> None:

cli/python/src/mem0_cli/commands/whoami_cmd.py

@@ -0,0 +1,25 @@
+"""mem0 whoami — print the active agent's default_user_id (AGENTRUSH identifier)."""
+
+from __future__ import annotations
+
+import typer
+from rich.console import Console
+
+from mem0_cli.branding import BRAND_COLOR, print_error, print_info
+from mem0_cli.config import load_config
+
+console = Console()
+err_console = Console(stderr=True)
+
+
+def run_whoami() -> None:
+    config = load_config()
+    session_id = config.platform.default_user_id if config.platform else None
+    if not session_id:
+        print_error(
+            err_console,
+            "No default_user_id found. Run `mem0 init --agent` first.",
+        )
+        raise typer.Exit(1)
+    console.print(f"Your AGENTRUSH identifier:  [{BRAND_COLOR}]{session_id}[/{BRAND_COLOR}]")
+    print_info(console, "Find your row at https://mem0.ai/agentrush")

cli/python/src/mem0_cli/config.py

@@ -28,6 +28,14 @@ class PlatformConfig:
     api_key: str = ""
     base_url: str = DEFAULT_BASE_URL
     user_email: str = ""
+    # Agent Mode (unclaimed-shadow signup)
+    agent_mode: bool = False  # True while the key is an unclaimed agent-mode key
+    created_via: str = ""  # "agent_mode" | "email" | "api_key" | "existing_key"
+    agent_caller: str = (
+        ""  # canonical agent name when created_via == "agent_mode" (e.g. "claude-code")
+    )
+    claimed_at: str = ""  # ISO timestamp once the agent has been claimed by a human
+    default_user_id: str = ""  # `user_<slug>` returned by bootstrap; used as auto-default
 
 
 @dataclass
@@ -43,12 +51,20 @@ class TelemetryConfig:
     anonymous_id: str = ""
 
 
+@dataclass
+class AgentRushConfig:
+    # ISO timestamp the human acknowledged the "memories are public" warning.
+    # Empty until first interactive `mem0 agent-rush add`.
+    acknowledged_at: str = ""
+
+
 @dataclass
 class Mem0Config:
     version: int = CONFIG_VERSION
     defaults: DefaultsConfig = field(default_factory=DefaultsConfig)
     platform: PlatformConfig = field(default_factory=PlatformConfig)
     telemetry: TelemetryConfig = field(default_factory=TelemetryConfig)
+    agent_rush: AgentRushConfig = field(default_factory=AgentRushConfig)
 
 
 SHORT_KEY_ALIASES: dict[str, str] = {
@@ -83,6 +99,11 @@ def load_config() -> Mem0Config:
         config.platform.api_key = plat.get("api_key", "")
         config.platform.base_url = plat.get("base_url", DEFAULT_BASE_URL)
         config.platform.user_email = plat.get("user_email", "")
+        config.platform.agent_mode = bool(plat.get("agent_mode", False))
+        config.platform.created_via = plat.get("created_via", "")
+        config.platform.agent_caller = plat.get("agent_caller", "")
+        config.platform.claimed_at = plat.get("claimed_at", "")
+        config.platform.default_user_id = plat.get("default_user_id", "")
 
         defaults = data.get("defaults", {})
         config.defaults.user_id = defaults.get("user_id", "")
@@ -92,6 +113,9 @@ def load_config() -> Mem0Config:
         telemetry = data.get("telemetry", {})
         config.telemetry.anonymous_id = telemetry.get("anonymous_id", "")
 
+        agent_rush = data.get("agent_rush", {})
+        config.agent_rush.acknowledged_at = agent_rush.get("acknowledged_at", "")
+
     # Environment variable overrides
     env_key = os.environ.get("MEM0_API_KEY")
     if env_key:
@@ -136,10 +160,18 @@ def save_config(config: Mem0Config) -> None:
             "api_key": config.platform.api_key,
             "base_url": config.platform.base_url,
             "user_email": config.platform.user_email,
+            "agent_mode": config.platform.agent_mode,
+            "created_via": config.platform.created_via,
+            "agent_caller": config.platform.agent_caller,
+            "claimed_at": config.platform.claimed_at,
+            "default_user_id": config.platform.default_user_id,
         },
         "telemetry": {
             "anonymous_id": config.telemetry.anonymous_id,
         },
+        "agent_rush": {
+            "acknowledged_at": config.agent_rush.acknowledged_at,
+        },
     }
 
     with open(CONFIG_FILE, "w") as f:
@@ -147,6 +179,19 @@ def save_config(config: Mem0Config) -> None:
 
     os.chmod(CONFIG_FILE, stat.S_IRUSR | stat.S_IWUSR)  # 0600
 
+    # Propagate the active api_key to ecosystem touchpoints (Claude Code
+    # plugin env injection, shell rc exports). Idempotent — only updates
+    # EXISTING entries; never creates new ones. Best-effort: any IOError
+    # in the sync is swallowed so config.json is always the authoritative
+    # write, never blocked by plugin-state issues.
+    if config.platform.api_key:
+        try:
+            from mem0_cli.plugin_sync import sync_api_key
+
+            sync_api_key(config.platform.api_key)
+        except Exception:
+            pass
+
 
 def redact_key(key: str) -> str:
     """Redact an API key for display: m0-xxx...xxx"""

cli/python/src/mem0_cli/output.py

@@ -229,6 +229,16 @@ def format_json_envelope(
     if error:
         envelope["error"] = error
     envelope["data"] = data
+
+    # If the platform flagged this as an unclaimed Agent Mode account, surface
+    # the notice inside the JSON envelope so an agent consuming the output
+    # sees it without needing to inspect HTTP headers.
+    from mem0_cli.state import take_notice
+
+    notice = take_notice()
+    if notice:
+        envelope["mem0_notice"] = notice
+
     console.print_json(json.dumps(envelope, default=str))
 
 
@@ -323,6 +333,15 @@ def format_agent_envelope(
     if count is not None:
         envelope["count"] = count
     envelope["data"] = sanitize_agent_data(command, data)
+
+    # Surface the unclaimed-Agent-Mode notice (if any) in the envelope so an
+    # agent reading the JSON output sees it without inspecting HTTP headers.
+    from mem0_cli.state import take_notice
+
+    notice = take_notice()
+    if notice:
+        envelope["mem0_notice"] = notice
+
     console.print_json(json.dumps(envelope, default=str))
 
 

cli/python/src/mem0_cli/plugin_sync.py

@@ -0,0 +1,119 @@
+"""Sync the active Mem0 API key into other ecosystem touchpoints.
+
+Why this exists:
+  The CLI canonical state lives in ``~/.mem0/config.json``. But MCP servers
+  (Claude Code plugin, Codex plugin, etc.) read ``MEM0_API_KEY`` from env
+  vars or their own config files. Without a sync, an agent-mode bootstrap
+  mints a new key into config.json but the plugin's MCP keeps using the
+  old key from env — silent surprise.
+
+Design:
+  - Update ONLY entries that already exist (never create new ones)
+  - Preserve all surrounding content / formatting / other keys
+  - Atomic writes (tmpfile + rename) so a crash mid-write doesn't corrupt
+  - Idempotent — re-running with the same key is a no-op
+  - Skip on dry_run
+
+Targets currently handled:
+  - ``~/.claude/settings.json::env::MEM0_API_KEY`` (Claude Code env injection)
+  - ``~/.zshrc`` / ``~/.bashrc`` ``export MEM0_API_KEY="..."`` lines
+
+Out of scope (deliberately not touched):
+  - Codex / Cursor MCP configs — would require schema-aware edits and
+    those tools don't have mem0 entries by default
+  - Plugin's own ``<plugin-dir>/.api_key`` file — plugin-managed
+"""
+
+from __future__ import annotations
+
+import contextlib
+import json
+import os
+import re
+import tempfile
+from pathlib import Path
+
+# Files we know how to update safely.
+_CLAUDE_SETTINGS = Path.home() / ".claude" / "settings.json"
+_SHELL_RCS = [Path.home() / ".zshrc", Path.home() / ".bashrc", Path.home() / ".bash_profile"]
+
+
+def sync_api_key(api_key: str) -> list[str]:
+    """Propagate ``api_key`` into known ecosystem touchpoints.
+
+    Returns the list of paths actually updated. Empty list means nothing
+    needed updating (either targets didn't exist or already had this value).
+    """
+    if not api_key:
+        return []
+    updated: list[str] = []
+    if _update_claude_settings(_CLAUDE_SETTINGS, api_key):
+        updated.append(str(_CLAUDE_SETTINGS))
+    for rc in _SHELL_RCS:
+        if _update_shell_rc(rc, api_key):
+            updated.append(str(rc))
+    return updated
+
+
+def _update_claude_settings(path: Path, api_key: str) -> bool:
+    """Update ``env.MEM0_API_KEY`` in path. Returns True if file was changed."""
+    if not path.is_file():
+        return False
+    try:
+        with path.open("r", encoding="utf-8") as f:
+            data = json.load(f)
+    except (json.JSONDecodeError, OSError):
+        return False
+    env = data.get("env")
+    if not isinstance(env, dict) or "MEM0_API_KEY" not in env:
+        # No existing entry — don't create one.
+        return False
+    if env["MEM0_API_KEY"] == api_key:
+        return False  # already in sync
+    env["MEM0_API_KEY"] = api_key
+    _atomic_write_text(path, json.dumps(data, indent=2, ensure_ascii=False) + "\n")
+    return True
+
+
+# Match `export MEM0_API_KEY="..."` (or single quotes, or no quotes).
+# Use [ \t]* (not \s*) for trailing whitespace so a trailing newline at
+# end-of-file is preserved when MEM0_API_KEY is the last line.
+_RC_LINE = re.compile(
+    r'^([ \t]*export[ \t]+MEM0_API_KEY[ \t]*=[ \t]*)(["\']?)([^"\'\n]*)(["\']?)[ \t]*$',
+    re.MULTILINE,
+)
+
+
+def _update_shell_rc(path: Path, api_key: str) -> bool:
+    """Update an existing ``export MEM0_API_KEY=...`` line in path."""
+    if not path.is_file():
+        return False
+    try:
+        text = path.read_text(encoding="utf-8")
+    except OSError:
+        return False
+    match = _RC_LINE.search(text)
+    if not match:
+        return False  # no existing line
+    if match.group(3) == api_key:
+        return False
+    new_text = _RC_LINE.sub(lambda m: f'{m.group(1)}"{api_key}"', text, count=1)
+    _atomic_write_text(path, new_text)
+    return True
+
+
+def _atomic_write_text(path: Path, content: str) -> None:
+    """Write content to path atomically (temp + rename)."""
+    dirname = path.parent
+    fd, tmp_path = tempfile.mkstemp(prefix=f".{path.name}.", suffix=".tmp", dir=dirname)
+    try:
+        with os.fdopen(fd, "w", encoding="utf-8") as f:
+            f.write(content)
+        # Preserve mode if the original existed.
+        if path.exists():
+            os.chmod(tmp_path, path.stat().st_mode & 0o777)
+        os.replace(tmp_path, path)
+    except Exception:
+        with contextlib.suppress(OSError):
+            os.unlink(tmp_path)
+        raise

cli/python/src/mem0_cli/state.py

@@ -4,6 +4,7 @@ from __future__ import annotations
 
 _agent_mode: bool = False
 _current_command: str = ""
+_pending_notice: str = ""
 
 
 def is_agent_mode() -> bool:
@@ -22,3 +23,23 @@ def get_current_command() -> str:
 def set_current_command(name: str) -> None:
     global _current_command
     _current_command = name
+
+
+def capture_notice(notice: str | None) -> None:
+    """Stash a Mem0 backend notice for end-of-command surfacing.
+
+    Called from the platform backend after each response so the notice can
+    be printed once per command (regardless of how many sub-requests fired).
+    Last-write-wins is fine — the message text is identical across requests.
+    """
+    global _pending_notice
+    if notice:
+        _pending_notice = notice
+
+
+def take_notice() -> str:
+    """Return and clear the pending notice."""
+    global _pending_notice
+    msg = _pending_notice
+    _pending_notice = ""
+    return msg

cli/python/src/mem0_cli/telemetry.py

@@ -87,7 +87,6 @@ def capture_event(
     try:
         from mem0_cli import __version__
         from mem0_cli.config import CONFIG_FILE, load_config, save_config
-        from mem0_cli.state import is_agent_mode
 
         config = load_config()
         distinct_id = pre_resolved_email or _get_distinct_id()
@@ -107,6 +106,9 @@ def capture_event(
             with contextlib.suppress(Exception):
                 save_config(config)
 
+        # M4: every cli.* event carries agent_mode based on the config flag
+        # (unclaimed Agent Mode key). This is the growth-doc property used to
+        # join init → add → search funnels in PostHog.
         payload = {
             "api_key": POSTHOG_API_KEY,
             "distinct_id": distinct_id,
@@ -115,7 +117,7 @@ def capture_event(
                 "source": "CLI",
                 "language": "python",
                 "cli_version": __version__,
-                "agent_mode": is_agent_mode(),
+                "agent_mode": bool(config.platform.agent_mode),
                 "python_version": sys.version,
                 "os": sys.platform,
                 "os_version": platform.version(),

cli/python/tests/test_agent_mode.py

@@ -0,0 +1,157 @@
+"""Parity tests for `mem0 init --agent` (Agent Mode bootstrap).
+
+Mirror of ``cli/node/tests/agent-mode.test.ts`` — both files MUST stay in
+sync so that the Python and Node CLIs expose an identical surface for the
+Agent Mode entrypoint. If you add a flag here, add the same assertion on
+the Node side (and vice versa).
+
+Network-bound bootstrap is covered by the platform-side E2E suite
+(``backend/tests/e2e/test_05_agent_mode.py``); these tests only verify
+the CLI surface that ships in the binary.
+"""
+
+from __future__ import annotations
+
+import os
+import re
+import subprocess
+import sys
+
+import pytest
+
+_ANSI_RE = re.compile(r"\x1b\[[0-9;]*[mKJHABCDfsu]")
+
+
+def _strip_ansi(text: str) -> str:
+    return _ANSI_RE.sub("", text)
+
+
+def _run(args: list[str], home_dir: str | None = None) -> subprocess.CompletedProcess:
+    env = os.environ.copy()
+    for key in list(env.keys()):
+        if key.startswith("MEM0_"):
+            del env[key]
+    env.pop("FORCE_COLOR", None)
+    if home_dir:
+        env["HOME"] = home_dir
+    result = subprocess.run(
+        [sys.executable, "-m", "mem0_cli", *args],
+        capture_output=True,
+        text=True,
+        env=env,
+        timeout=15,
+    )
+    return subprocess.CompletedProcess(
+        args=result.args,
+        returncode=result.returncode,
+        stdout=_strip_ansi(result.stdout),
+        stderr=_strip_ansi(result.stderr),
+    )
+
+
+@pytest.fixture
+def clean_home(tmp_path):
+    return str(tmp_path)
+
+
+class TestInitFlagSurface:
+    """`mem0 init --help` must expose the Agent Mode flags."""
+
+    def test_init_help_lists_agent_flag(self):
+        result = _run(["init", "--help"])
+        assert result.returncode == 0
+        assert "--agent" in result.stdout
+
+    def test_init_help_describes_agent_mode(self):
+        result = _run(["init", "--help"])
+        assert result.returncode == 0
+        # Description must mention what --agent actually does so an agent
+        # reading the help can self-discover the bootstrap entrypoint.
+        assert "Agent Mode" in result.stdout or "unattended" in result.stdout.lower()
+
+    def test_init_help_lists_source_flag(self):
+        result = _run(["init", "--help"])
+        assert result.returncode == 0
+        assert "--source" in result.stdout
+
+    def test_init_help_lists_email_and_code(self):
+        # Claim flow flags must remain present alongside Agent Mode flags.
+        result = _run(["init", "--help"])
+        assert result.returncode == 0
+        assert "--email" in result.stdout
+        assert "--code" in result.stdout
+
+
+class TestArgvPreprocessing:
+    """`--agent` on `init` must reach init_cmd, not be eaten by the global preprocessor.
+
+    Regression for the bug where the top-level `--agent` JSON-alias was
+    stripped from ``sys.argv`` before Typer could bind it to the init
+    subcommand, making ``mem0 init --agent`` indistinguishable from a
+    plain ``mem0 init`` (interactive wizard).
+    """
+
+    def test_init_with_agent_reaches_subcommand(self, clean_home):
+        # We can't hit a real backend in unit tests, so we point the CLI at
+        # a guaranteed-dead URL and assert the failure is the bootstrap
+        # request failing — proving the --agent flag was honored and the
+        # bootstrap branch ran, not the interactive wizard.
+        result = subprocess.run(
+            [sys.executable, "-m", "mem0_cli", "init", "--agent"],
+            capture_output=True,
+            text=True,
+            env={
+                **{k: v for k, v in os.environ.items() if not k.startswith("MEM0_")},
+                "HOME": clean_home,
+                "MEM0_BASE_URL": "http://127.0.0.1:1",  # blackhole
+                "FORCE_COLOR": "0",
+            },
+            timeout=15,
+        )
+        combined = _strip_ansi(result.stdout + result.stderr).lower()
+        # Either we got a connection/network error from the bootstrap POST,
+        # or the CLI surfaced an Agent Mode-specific failure message.
+        assert (
+            "agent" in combined
+            or "connect" in combined
+            or "network" in combined
+            or "fetch" in combined
+            or "bootstrap" in combined
+        ), f"Expected bootstrap attempt, got: {combined!r}"
+
+
+class TestJsonEnvelopeParity:
+    """`mem0 init --agent --json` should produce a JSON envelope on success.
+
+    Without a live backend we can only assert the failure shape: when the
+    backend is unreachable, the CLI must still exit non-zero AND not crash
+    on a Python traceback (which would mean we leaked an exception past
+    the agent-mode handler).
+    """
+
+    def test_init_agent_json_no_traceback_on_network_failure(self, clean_home):
+        result = subprocess.run(
+            [sys.executable, "-m", "mem0_cli", "init", "--agent", "--json"],
+            capture_output=True,
+            text=True,
+            env={
+                **{k: v for k, v in os.environ.items() if not k.startswith("MEM0_")},
+                "HOME": clean_home,
+                "MEM0_BASE_URL": "http://127.0.0.1:1",
+                "FORCE_COLOR": "0",
+            },
+            timeout=15,
+        )
+        combined = _strip_ansi(result.stdout + result.stderr)
+        assert "Traceback (most recent call last)" not in combined
+        assert result.returncode != 0
+
+
+class TestInitInCommandList:
+    """`mem0 --help` must list `init` so agents walking the top-level help
+    can discover the Agent Mode entrypoint without prior knowledge."""
+
+    def test_top_level_help_lists_init(self):
+        result = _run(["--help"])
+        assert result.returncode == 0
+        assert "init" in result.stdout

cli/python/tests/test_init_internals.py

@@ -0,0 +1,206 @@
+"""Unit tests for init internals — decision tree primitives + plugin sync.
+
+These tests exercise the units that the high-level subprocess parity tests in
+``test_agent_mode.py`` deliberately can't reach:
+
+  - ``_ping_key`` must NOT treat network errors as "invalid key" (else a VPN
+    flap silently mints a new shadow over a working key).
+  - ``plugin_sync`` must only update entries that already exist, preserve
+    trailing newlines, and never mangle other lines.
+  - The 403→ratelimit translation in ``bootstrap_via_backend`` surfaces the
+    real cause instead of DRF's opaque "You do not have permission" string.
+
+Mirror surface lives in ``cli/node/tests/agent-mode.test.ts``; if you add a
+behavioral assertion here, mirror it on the Node side and vice versa.
+"""
+
+from __future__ import annotations
+
+from unittest.mock import MagicMock
+
+import httpx
+import pytest
+
+from mem0_cli.commands.init_cmd import _ping_key
+from mem0_cli.plugin_sync import _update_claude_settings, _update_shell_rc
+
+# ── _ping_key ──────────────────────────────────────────────────────────────
+
+
+class _Resp:
+    def __init__(self, status_code: int) -> None:
+        self.status_code = status_code
+
+
+def test_ping_key_200_is_valid(monkeypatch: pytest.MonkeyPatch) -> None:
+    monkeypatch.setattr(httpx, "get", lambda *a, **kw: _Resp(200))
+    assert _ping_key("k", "http://x") is True
+
+
+def test_ping_key_401_is_invalid(monkeypatch: pytest.MonkeyPatch) -> None:
+    monkeypatch.setattr(httpx, "get", lambda *a, **kw: _Resp(401))
+    assert _ping_key("k", "http://x") is False
+
+
+def test_ping_key_403_is_invalid(monkeypatch: pytest.MonkeyPatch) -> None:
+    monkeypatch.setattr(httpx, "get", lambda *a, **kw: _Resp(403))
+    assert _ping_key("k", "http://x") is False
+
+
+def test_ping_key_5xx_is_not_definitively_invalid(monkeypatch: pytest.MonkeyPatch) -> None:
+    # Transient upstream failure must NOT cause a shadow to be minted.
+    monkeypatch.setattr(httpx, "get", lambda *a, **kw: _Resp(503))
+    assert _ping_key("k", "http://x") is True
+
+
+def test_ping_key_connect_error_prefers_reuse(monkeypatch: pytest.MonkeyPatch) -> None:
+    # Network blip (DNS, captive portal, etc.) — must NOT trigger a re-mint.
+    def boom(*a, **kw):
+        raise httpx.ConnectError("nope")
+
+    monkeypatch.setattr(httpx, "get", boom)
+    assert _ping_key("k", "http://x") is True
+
+
+def test_ping_key_timeout_prefers_reuse(monkeypatch: pytest.MonkeyPatch) -> None:
+    def boom(*a, **kw):
+        raise httpx.ReadTimeout("slow")
+
+    monkeypatch.setattr(httpx, "get", boom)
+    assert _ping_key("k", "http://x") is True
+
+
+# ── plugin_sync._update_shell_rc ──────────────────────────────────────────
+
+
+def test_shell_rc_updates_existing_export_preserves_trailing_newline(tmp_path) -> None:
+    rc = tmp_path / ".zshrc"
+    rc.write_text('export MEM0_API_KEY="old"\n', encoding="utf-8")
+    changed = _update_shell_rc(rc, "newkey")
+    assert changed is True
+    assert rc.read_text(encoding="utf-8") == 'export MEM0_API_KEY="newkey"\n'
+
+
+def test_shell_rc_does_not_create_new_export(tmp_path) -> None:
+    rc = tmp_path / ".zshrc"
+    rc.write_text("alias ll='ls -la'\n", encoding="utf-8")
+    changed = _update_shell_rc(rc, "newkey")
+    assert changed is False
+    assert rc.read_text(encoding="utf-8") == "alias ll='ls -la'\n"
+
+
+def test_shell_rc_preserves_surrounding_content(tmp_path) -> None:
+    rc = tmp_path / ".zshrc"
+    original = "# my zshrc\nalias ll='ls -la'\nexport MEM0_API_KEY='old'\nexport OTHER=keepme\n"
+    rc.write_text(original, encoding="utf-8")
+    _update_shell_rc(rc, "newkey")
+    after = rc.read_text(encoding="utf-8")
+    assert "alias ll='ls -la'\n" in after
+    assert "export OTHER=keepme\n" in after
+    assert "# my zshrc\n" in after
+    assert 'export MEM0_API_KEY="newkey"\n' in after
+
+
+def test_shell_rc_idempotent_when_already_matching(tmp_path) -> None:
+    rc = tmp_path / ".zshrc"
+    rc.write_text('export MEM0_API_KEY="same"\n', encoding="utf-8")
+    assert _update_shell_rc(rc, "same") is False
+
+
+def test_shell_rc_missing_file_is_noop(tmp_path) -> None:
+    rc = tmp_path / ".zshrc"  # does not exist
+    assert _update_shell_rc(rc, "x") is False
+
+
+# ── plugin_sync._update_claude_settings ────────────────────────────────────
+
+
+def test_claude_settings_does_not_create_env_block(tmp_path) -> None:
+    import json
+
+    settings = tmp_path / "settings.json"
+    settings.write_text(json.dumps({"otherKey": 1}), encoding="utf-8")
+    changed = _update_claude_settings(settings, "newkey")
+    assert changed is False
+    # Original content unchanged.
+    assert json.loads(settings.read_text(encoding="utf-8")) == {"otherKey": 1}
+
+
+def test_claude_settings_does_not_create_mem0_entry_in_existing_env(tmp_path) -> None:
+    import json
+
+    settings = tmp_path / "settings.json"
+    settings.write_text(json.dumps({"env": {"OTHER_KEY": "x"}}), encoding="utf-8")
+    changed = _update_claude_settings(settings, "newkey")
+    assert changed is False
+
+
+def test_claude_settings_updates_existing_entry(tmp_path) -> None:
+    import json
+
+    settings = tmp_path / "settings.json"
+    settings.write_text(
+        json.dumps({"env": {"MEM0_API_KEY": "old", "OTHER": "y"}}, indent=2),
+        encoding="utf-8",
+    )
+    changed = _update_claude_settings(settings, "fresh")
+    assert changed is True
+    data = json.loads(settings.read_text(encoding="utf-8"))
+    assert data["env"]["MEM0_API_KEY"] == "fresh"
+    assert data["env"]["OTHER"] == "y"  # other keys preserved
+
+
+def test_claude_settings_idempotent(tmp_path) -> None:
+    import json
+
+    settings = tmp_path / "settings.json"
+    settings.write_text(json.dumps({"env": {"MEM0_API_KEY": "same"}}), encoding="utf-8")
+    assert _update_claude_settings(settings, "same") is False
+
+
+def test_claude_settings_malformed_json_is_noop(tmp_path) -> None:
+    settings = tmp_path / "settings.json"
+    settings.write_text("{ this is not json", encoding="utf-8")
+    assert _update_claude_settings(settings, "x") is False
+
+
+# ── bootstrap rate-limit translation ──────────────────────────────────────
+
+
+def test_bootstrap_403_permission_surfaces_ratelimit(monkeypatch, capsys) -> None:
+    """DRF 403 'You do not have permission' must be translated to the daily limit message."""
+    from mem0_cli.commands.agent_mode_cmd import bootstrap_via_backend
+    from mem0_cli.config import Mem0Config
+
+    fake_resp = MagicMock()
+    fake_resp.status_code = 403
+    fake_resp.text = '{"detail": "You do not have permission to perform this action."}'
+    fake_resp.json = MagicMock(
+        return_value={"detail": "You do not have permission to perform this action."}
+    )
+
+    class _Client:
+        def __init__(self, *a, **kw):
+            pass
+
+        def __enter__(self):
+            return self
+
+        def __exit__(self, *a):
+            return False
+
+        def post(self, *a, **kw):
+            return fake_resp
+
+    monkeypatch.setattr(httpx, "Client", _Client)
+    cfg = Mem0Config()
+    cfg.platform.base_url = "https://api.mem0.ai"
+    import typer
+
+    with pytest.raises(typer.Exit):
+        bootstrap_via_backend(cfg)
+
+    captured = capsys.readouterr()
+    combined = captured.out + captured.err
+    assert "Daily Agent Mode signup limit reached" in combined
+    assert "permission to perform this action" not in combined

docs/api-reference/events/get-event.mdx

@@ -5,3 +5,5 @@ openapi: get /v1/event/{event_id}/
 ---
 
 Retrieve details about a specific event by passing its `event_id`. This endpoint is particularly helpful for tracking the status, payload, and completion details of asynchronous memory operations.
+
+For `POST /v3/memories/add/`, the event confirms that the write pipeline completed. Temporal reasoning enrichment runs asynchronously by default, so the event may be `SUCCEEDED` slightly before temporal ranking signals are available to subsequent `search` calls.

docs/api-reference/memory/add-memories.mdx

@@ -83,4 +83,3 @@ The request is queued for background processing. The response contains an `event
 <Info>
 Poll the event status via `GET /v1/event/{event_id}/`. Status will be `SUCCEEDED` or `FAILED` once processing completes.
 </Info>
-

docs/api-reference/memory/get-memories.mdx

@@ -64,4 +64,3 @@ memories = client.get_all(
 <Info>
 The response is a paginated envelope with `count`, `next`, `previous`, and `results`. Use `page` and `page_size` query params to step through results.
 </Info>
-

docs/api-reference/memory/search-memories.mdx

@@ -49,6 +49,7 @@ related_memories = client.search(
     {
       "id": "ea925981-272f-40dd-b576-be64e4871429",
       "memory": "Likes to play cricket and plays cricket on weekends.",
+      "user_id": "alice",
       "metadata": {
         "category": "hobbies"
       },

docs/api-reference/organizations-projects.mdx

@@ -79,7 +79,7 @@ new_project = client.project.create(
 
 ### Update Project Settings
 
-Modify project configuration including custom instructions, categories, graph settings, and language preferences:
+Modify project configuration including custom instructions, categories, and language preferences:
 
 ```python
 # Update project with custom categories
@@ -109,6 +109,19 @@ client.project.update(
 )
 ```
 
+#### Toggle Memory Decay
+
+`decay` is a per-project boolean that turns on [Memory Decay](/platform/features/memory-decay) — a search-time ranking bias that reinforces recently-accessed memories and gently dampens stale ones. The flag is `false` by default; set it via the same project-update endpoint:
+
+```bash cURL
+curl -X PATCH https://api.mem0.ai/api/v1/orgs/organizations/$ORG_ID/projects/$PROJECT_ID/ \
+  -H "Authorization: Token $MEM0_API_KEY" \
+  -H "Content-Type: application/json" \
+  -d '{"decay": true}'
+```
+
+The current state is returned on every project read (and supports `?fields=decay` for a minimal response). Toggling has no effect on stored memories, only on how v3 search ranks them.
+
 ### Delete Project
 
 <Warning>

docs/changelog/highlights.mdx

@@ -4,6 +4,34 @@ description: "Major product launches, headline features, and milestones for Mem0
 mode: "wide"
 ---
 
+<Update label="2026-05-13" description="Temporal Reasoning for Mem0 Platform v3">
+
+**Temporal Reasoning — Time-Aware Retrieval for Platform v3**
+
+Mem0 Platform v3 can now interpret time-aware memories and queries so assistants retrieve the right information for questions about the past, upcoming plans, and current state.
+
+- **Time-aware search intent** — Queries like `last week`, `upcoming`, `right now`, and `as of March 2025` return contextually appropriate results automatically
+- **Enabled by default** — No per-request toggle required for v3 writes or searches
+- **Anchored relative queries** — `reference_date` anchors relative search phrases for tests, backfills, and reproducible demos
+- **Normal response shape** — Temporal reasoning affects ranking while preserving existing client response patterns
+
+See [Temporal Reasoning](/platform/features/temporal-reasoning) for usage details.
+
+</Update>
+
+<Update label="2026-05-08" description="Memory Decay">
+
+**Memory Decay — Recently-Used Memories Surface Higher, Automatically**
+
+Per-project search-time ranking bias that boosts recently-touched memories and gently dampens stale ones. Off by default; opt in per project via the `decay` field on the project endpoint, or via `client.project.update(decay=True)` in the SDKs (Python `v2.0.2` / TypeScript `v3.0.3`).
+
+- **Soft bias, never a filter.** The scaling factor stays in `0.3×–1.5×`. Decay can reorder candidates but never zeros them out — anything that surfaced before decay can still surface after.
+- **Reinforcement loop.** Every memory returned in a search has its access history updated, so frequently-used facts naturally float to the top over time.
+- **Public score still clamped to `[0, 1]`.** Existing API contract preserved; no client-side changes needed.
+- **v3 search only**, fully reversible. See [Memory Decay docs](/platform/features/memory-decay).
+
+</Update>
+
 <Update label="2026-04-14" description="Mem0 SDK v2.0.0 / v3.0.0">
 
 **New Memory Algorithm — State-of-the-Art Accuracy at ~3-4x Lower Cost**
@@ -99,4 +127,4 @@ Major expansion of the provider ecosystem:
 
 First skill launch — a dedicated Mem0 skill providing platform API reference, quickstart patterns, and integration examples directly inside agent sessions. Available on [skills.sh](https://skills.sh) for any compatible AI coding agent.
 
-</Update>
+</Update>

docs/changelog/openclaw.mdx

@@ -4,6 +4,36 @@ description: "Release notes for the OpenClaw plugin and agent harness."
 mode: "wide"
 ---
 
+<Update label="2026-04-29" description="v1.0.11">
+
+**New Features:**
+- **Skills-mode auto-setup:** `enableSkillsConfig()` now runs automatically after onboarding — enables triage, recall (with reranking + keyword search), and dream consolidation with `tools.profile = "full"` and disables the built-in session-memory hook to avoid conflicts
+- **Memory runtime capability:** Plugin now exposes `runtime.getMemorySearchManager()` and `resolveMemoryBackendConfig()` on the registered memory capability, enabling OpenClaw gateway to query memory status and backend config directly
+- **Dimension-aware collections:** OSS wizard detects embedder dimension changes and creates a new collection (`mem0_<dims>d`) automatically, with a warning about old memories being inaccessible under the new embedder
+- **Tool documentation in skills:** Both `memory-triage` and `memory-dream` SKILL.md files now include full tool reference sections listing all available tools with parameters
+
+**Improvements:**
+- **Auto-capture and auto-recall default to enabled:** `autoCapture` and `autoRecall` now default to `true` (was `false`). Manifest descriptions updated accordingly. Ignored in skills mode
+- **`memory_update` over delete+add:** Skills now prefer `memory_update` for in-place edits — atomic and preserves edit history. Consolidation pattern updated: update best memory, delete redundant ones
+- **Search threshold lowered:** Default `searchThreshold` reduced from `0.5` to `0.1` for broader recall. Removed hardcoded `0.6` recall-specific override — all searches now use the configured threshold
+- **Embedder dimension propagation:** Vector store config auto-resolves dimensions from embedder config when not explicitly set. Syncs `dimension` and `embeddingModelDims` fields for Qdrant/PGVector compatibility
+- **Config file write safety:** `writeFullConfig()` now re-reads and deep-merges the `plugins` section before writing, preserving `installs` and `slots` written by the OpenClaw gateway
+- **Additional embedder models:** Added `mxbai-embed-large` (1024), `all-minilm` (384), and `snowflake-arctic-embed` (1024) to known embedder dimensions
+
+**Security:**
+- Bumped `protobufjs` to `>=7.5.5` via pnpm overrides (GHSA-xq3m-2v4x-88gg) ([#5012](https://github.com/mem0ai/mem0/pull/5012))
+
+**Fixes:**
+- Moved `bootstrapTelemetryFlag()` and removed `ensureInstallRecord()` from module-level side effects — both now run inside `register()` to avoid crashes when loaded outside OpenClaw gateway
+- Fixed OSS history DB path resolution: absolute paths no longer passed through `resolvePath()`, preventing double-prefix bugs
+- Manifest `providerAuthEnvVars` replaced with spec-compliant `setup.providers` format using `id` + `envVars`
+
+**Dependencies:**
+- Bumped `mem0ai` from `3.0.1` to `3.0.2`
+- Bumped `pluginApi` and `minGatewayVersion` compat to `>=2026.4.24`
+
+</Update>
+
 <Update label="2026-04-23" description="v1.0.10">
 
 **Security:**

docs/changelog/platform.mdx

@@ -4,6 +4,24 @@ description: "Release notes for the Mem0 hosted platform — backend, dashboard,
 mode: "wide"
 ---
 
+<Update label="2026-05-13" description="">
+
+**New Features:**
+- **Memory:** Added Temporal Reasoning for Platform v3 to improve ranking for time-aware queries such as `last week`, `upcoming`, `right now`, and `as of ...`
+- **Search:** Added `reference_date` support to anchor relative temporal queries for tests, backfills, and reproducible demos
+
+**Improvements:**
+- **API:** Temporal reasoning preserves the normal client response shape for search and get-all results
+
+</Update>
+
+<Update label="2026-05-04" description="">
+
+**New Features:**
+- **Memory Decay:** Per-project search-time ranking bias that boosts recently-used memories and gently dampens stale ones. Opt-in via `decay` on the project endpoint; off by default. The scaling factor stays in `0.3×–1.5×`, the public `score` remains clamped to `[0, 1]`, and the bias never filters a candidate out. See [Memory Decay docs](/platform/features/memory-decay).
+
+</Update>
+
 <Update label="2026-04-16" description="">
 
 **Improvements:**
@@ -294,4 +312,3 @@ mode: "wide"
 - **Core:** Fixed unicode error in user_id, agent_id, run_id and app_id
 
 </Update>
-

docs/changelog/sdk.mdx

@@ -7,6 +7,35 @@ mode: "wide"
 <Tabs>
 <Tab title="Python">
 
+<Update label="2026-05-27" description="v2.0.4">
+
+**New Features:**
+- **Client:** `delete()` and async `delete()` accept `delete_linked` (default `False`). When `True`, deleting a memory also removes the older memories it superseded (the v3 `linked_memory_ids` chain), transitively — the delete-side counterpart of `latest_only`, so a superseded memory does not resurface after the current one is deleted ([#5270](https://github.com/mem0ai/mem0/pull/5270))
+
+</Update>
+
+<Update label="2026-05-26" description="v2.0.3">
+
+**Bug Fixes:**
+- **Vector Stores:** PGVector adapter now supports rich filter operators (`eq`, `ne`, `gt`, `gte`, `lt`, `lte`, `in`, `nin`, `contains`, `icontains`, wildcard `*`, `$or`, `$not`) in `search()`, `keyword_search()`, and `list()`. Previously only exact-equality filters worked — operator dicts were silently stringified and returned zero results ([#5263](https://github.com/mem0ai/mem0/pull/5263))
+- **Server:** Fixed `/search` endpoint returning 502 when `user_id`, `agent_id`, or `run_id` are sent as top-level request fields. The server now maps these into the `filters` dict before calling `Memory.search()`, matching the v3 API contract. Top-level entity ID fields are marked as deprecated in the OpenAPI schema and emit a warning log — clients should migrate to `filters={"user_id": "..."}` ([#5263](https://github.com/mem0ai/mem0/pull/5263))
+
+</Update>
+
+<Update label="2026-05-08" description="v2.0.2">
+
+**Bug Fixes:**
+- **Telemetry:** Stitch OSS and platform PostHog identities on `MemoryClient` init so `$identify` events fire and a single user is no longer tracked as two or three disconnected personas ([#5040](https://github.com/mem0ai/mem0/pull/5040))
+- **Security:** Harden against SQL injection and prompt injection ([#4997](https://github.com/mem0ai/mem0/pull/4997))
+
+**New Features:**
+- **SDK:** Expose `decay` on `project.update` ([#5062](https://github.com/mem0ai/mem0/pull/5062))
+
+**Improvements:**
+- **Plugin:** Hand `mem0` search decisions to the agent ([#4992](https://github.com/mem0ai/mem0/pull/4992))
+
+</Update>
+
 <Update label="2026-04-25" description="v2.0.1">
 
 **Bug Fixes:**
@@ -41,7 +70,7 @@ mode: "wide"
 **Breaking Changes:**
 - **`add()` returns ADD-only events** — No more `"UPDATE"` or `"DELETE"` events. Memories accumulate; nothing is overwritten ([#4805](https://github.com/mem0ai/mem0/pull/4805))
 - **`search()` default `threshold` is now `0.1`** — Pass `threshold=0.0` for previous behavior ([#4805](https://github.com/mem0ai/mem0/pull/4805))
-- **`search()` `score` is now a combined multi-signal score** — The top-level `score` fuses semantic similarity, BM25 keyword match, and entity boost into one value. Absolute numbers shift versus the old raw cosine score; retune any hard thresholds against representative queries. Per-signal scores are not exposed on the response ([#4805](https://github.com/mem0ai/mem0/pull/4805), [#4836](https://github.com/mem0ai/mem0/pull/4836))
+- **`search()` `score` is now a combined multi-signal score** — The top-level `score` fuses semantic similarity, BM25 keyword match, entity signals, and temporal boosts into one value. Absolute numbers shift versus the old raw cosine score; retune any hard thresholds against representative queries ([#4805](https://github.com/mem0ai/mem0/pull/4805), [#4836](https://github.com/mem0ai/mem0/pull/4836))
 - **`search()` default `rerank` is now `False`** — Pass `rerank=True` for previous behavior ([#4805](https://github.com/mem0ai/mem0/pull/4805))
 - **`top_k` default changed 100 → 20** in `Memory.get_all()` and `Memory.search()` (sync + async). Pass `top_k=100` explicitly to restore the old behavior ([#4843](https://github.com/mem0ai/mem0/pull/4843))
 - **Entity ID validation:** `user_id` / `agent_id` / `run_id` are trimmed; empty-string and whitespace-only values now raise `ValueError` ([#4843](https://github.com/mem0ai/mem0/pull/4843))
@@ -910,6 +939,32 @@ See the [OSS v1 to v2 migration guide](https://docs.mem0.ai/migration/oss-v1-to-
 </Tab>
 
 <Tab title="TypeScript">
+<Update label="2026-05-27" description="v3.0.5">
+
+**New Features:**
+- **Client:** `delete()` accepts an options object with `deleteLinked` (serialized as `delete_linked`, default `false`). When `true`, deleting a memory also removes the older memories it superseded (the v3 linked chain), transitively — the delete-side counterpart of `latestOnly`, so a superseded memory does not resurface after the current one is deleted ([#5270](https://github.com/mem0ai/mem0/pull/5270))
+
+</Update>
+
+<Update label="2026-05-26" description="v3.0.4">
+
+**Bug Fixes:**
+- **Vector Stores:** PGVector adapter now supports rich filter operators (`eq`, `ne`, `gt`, `gte`, `lt`, `lte`, `in`, `nin`, `contains`, `icontains`, wildcard `*`, `$or`, `$not`) in `search()`, `keywordSearch()`, and `list()`. Previously only exact-equality filters worked — operator objects were passed as raw values and returned incorrect results ([#5263](https://github.com/mem0ai/mem0/pull/5263))
+
+</Update>
+
+<Update label="2026-05-08" description="v3.0.3">
+
+**Bug Fixes:**
+- **Telemetry:** Stitch OSS and platform PostHog identities on `MemoryClient` init so `$identify` events fire and a single user is no longer tracked as two or three disconnected personas ([#5040](https://github.com/mem0ai/mem0/pull/5040))
+- **Vector Stores:** Fix inverted vector distance in PGVector implementation ([#4944](https://github.com/mem0ai/mem0/pull/4944))
+- **Security:** Harden against SQL injection and prompt injection ([#4997](https://github.com/mem0ai/mem0/pull/4997))
+
+**New Features:**
+- **SDK:** Expose `decay` on `project.update` ([#5062](https://github.com/mem0ai/mem0/pull/5062))
+
+</Update>
+
 <Update label="2026-04-25" description="v3.0.2">
 
 **Bug Fixes:**
@@ -1297,6 +1352,30 @@ See the [TypeScript SDK migration guide](https://docs.mem0.ai/migration/ts-v2-to
 
 <Tab title="CLI">
 
+<Update label="2026-05-16" description="Python v0.2.6 / Node v0.2.6">
+
+**Bug Fixes:**
+- **Claim flow error message:** The `email_already_claimed` tip in `mem0 init --email` previously suggested running `mem0 link <key>` — a command that doesn't exist. Replaced with honest copy pointing the user to sign in at app.mem0.ai with their existing credentials ([#5152](https://github.com/mem0ai/mem0/pull/5152))
+
+</Update>
+
+<Update label="2026-05-14" description="Python v0.2.5 / Node v0.2.5">
+
+**New Features:**
+- **Agent Mode (`mem0 init --agent`):** Zero-friction signup for AI agents — mints a working Mem0 API key in under 5 seconds with no email, no dashboard, no OTP. Returns an unclaimed shadow account the human can later claim with `mem0 init --email <their-email>` (memories preserved, same key keeps working) ([#5123](https://github.com/mem0ai/mem0/pull/5123))
+- **Self-declared agent identity:** Agents pass `--agent-caller <name>` (e.g. `claude-code`, `cursor`, `codex`) on `mem0 init --agent` so signups attribute to the right tool in analytics. Proof Editor-style — the agent declares itself rather than the CLI sniffing it from env vars ([#5123](https://github.com/mem0ai/mem0/pull/5123))
+- **`mem0 identify <name>`:** New subcommand to self-tag an Agent Mode key after the fact when the agent forgot to pass `--agent-caller` on init. Idempotent — re-running just overwrites ([#5123](https://github.com/mem0ai/mem0/pull/5123))
+- **Plugin sync:** `~/.claude/settings.json::env::MEM0_API_KEY` and `~/.zshrc`/`.bashrc` `export MEM0_API_KEY=` lines stay in sync with `~/.mem0/config.json` automatically. Idempotent — only updates EXISTING entries, never creates new ones ([#5123](https://github.com/mem0ai/mem0/pull/5123))
+- **Claim flow:** `mem0 init --email <email>` claims an existing Agent Mode shadow via OTP. Upgrade-in-place — the API key never changes, memories transfer to the human's account ([#5123](https://github.com/mem0ai/mem0/pull/5123))
+
+**Bug Fixes:**
+- **Decision tree network resilience:** `pingKey` now distinguishes network errors from invalid keys — returns false ONLY on HTTP 401/403, returns true on connection failures / timeouts / 5xx. Prevents a VPN flap from silently rotating the user's API key and rewriting plugin-sync targets ([#5123](https://github.com/mem0ai/mem0/pull/5123))
+- **Rate-limit error clarity:** DRF's opaque `"You do not have permission"` 403 from Agent Mode rate limits is now translated to `"Daily Agent Mode signup limit reached for this network (5/day). Try again from a different IP or after midnight UTC."` ([#5123](https://github.com/mem0ai/mem0/pull/5123))
+- **JSON envelope `command` field:** `mem0 init --agent --json` error envelopes now populate the `command` field correctly instead of returning an empty string ([#5123](https://github.com/mem0ai/mem0/pull/5123))
+- **Bootstrap envelope validation:** Defends against partial/malformed backend responses (e.g. `{api_key: null}`) silently persisting null/undefined into typed string fields ([#5123](https://github.com/mem0ai/mem0/pull/5123))
+
+</Update>
+
 <Update label="2026-04-22" description="Python v0.2.4 / Node v0.2.4">
 
 **New Features:**

docs/cookbooks/essentials/controlling-memory-ingestion.mdx

@@ -323,10 +323,6 @@ Metadata: {'verified': True, 'updated_date': '2025-04-02'}
 That “no duplicates” promise comes from the inference pipeline. Keep `infer=True` when you rely on automatic updates. Raw imports (`infer=False`) skip conflict checks, so mixing the two modes for the same fact will create duplicates.
 </Warning>
 
-**Maintains relationships:**
-
-- If using graph memory, connections to other entities persist
-
 ### Pick the right inference mode
 
 | Mode | What it does | Best for | Watch out for |

docs/cookbooks/frameworks/gemini-3-with-mem0-mcp.mdx

@@ -216,7 +216,6 @@ This information was retrieved from your memory history where you previously men
 
 - **Smart Memory Management** - Organizes memories into searchable information *without setting up vector databases*
 - **Fast Retrieval** - Instant lookups with *sub-millisecond ping*, handles large datasets
-- **Graph Capabilities** - Builds knowledge *automatically* as you push information
 - **Simple Integration** - Uses Mem0 API in the backend, works with *any MCP client* with just a few lines of code
 
 ### Gemini 3 + Mem0 Benefits

docs/cookbooks/overview.mdx

@@ -156,14 +156,7 @@ Here are some examples of how Mem0 can be integrated into various applications:
     icon="aws"
     href="/cookbooks/integrations/aws-bedrock"
   >
-    Mem0 with AWS Bedrock and Neptune.
-  </Card>
-  <Card
-    title="Graph Memory on Neptune"
-    icon="network-wired"
-    href="/cookbooks/integrations/neptune-analytics"
-  >
-    Graph memory with Neptune Analytics.
+    Mem0 with AWS Bedrock.
   </Card>
 </CardGroup>
 

docs/core-concepts/memory-evaluation.mdx

@@ -47,7 +47,7 @@ When a query arrives, the retrieval pipeline scores candidates across three sign
 
 1. **Semantic Search** — Vector similarity scoring against memory embeddings
 2. **Keyword Search** — Normalized term matching via BM25 with verb-form lemmatization
-3. **Entity Search** — Entity graph matching boosts memories linked to query entities
+3. **Entity Search** — Entity matching boosts memories linked to query entities
 
 Results are fused via rank scoring into a final top-K set. Different query types lean on different signals:
 

docs/core-concepts/memory-operations/add.mdx

@@ -27,15 +27,11 @@ Adding memory is how Mem0 captures useful details from a conversation so your ag
 
 Mem0 offers two flows:
 
-- **Mem0 Platform** – Fully managed API with dashboard, scaling, and graph features.
+- **Mem0 Platform** – Fully managed API with dashboard and scaling.
 - **Mem0 Open Source** – Local SDK that you run in your own environment.
 
 Both flows take the same payload and pass it through the same pipeline.
 
-<Frame caption="Architecture diagram illustrating the process of adding memories.">
-  <img src="../../images/add_architecture.png" />
-</Frame>
-
 <Steps>
 <Step title="Information extraction">
 Mem0 sends the messages through an LLM that pulls out key facts, decisions, or preferences to remember.
@@ -44,7 +40,7 @@ Mem0 sends the messages through an LLM that pulls out key facts, decisions, or p
 Existing memories are checked for duplicates or contradictions so the latest truth wins.
 </Step>
 <Step title="Storage">
-The resulting memories land in managed vector storage (and optional graph storage) so future searches return them quickly.
+The resulting memories land in managed vector storage so future searches return them quickly.
 </Step>
 </Steps>
 
@@ -177,7 +173,7 @@ For full list of supported fields, required formats, and advanced options, see t
 
 ## Put it into practice
 
-- Review the <Link href="/platform/advanced-memory-operations">Advanced Memory Operations</Link> guide to layer metadata, rerankers, and graph toggles.
+- Review the <Link href="/platform/advanced-memory-operations">Advanced Memory Operations</Link> guide to layer metadata and rerankers.
 - Explore the <Link href="/api-reference/memory/add-memories">Add Memories API reference</Link> for every request/response field.
 
 ## See it live

docs/core-concepts/memory-operations/search.mdx

@@ -25,10 +25,6 @@ Mem0's search operation lets agents ask natural-language questions and get back
 
 ## Architecture
 
-<Frame caption="Architecture diagram illustrating the memory search process.">
-  <img src="../../images/search_architecture.png" />
-</Frame>
-
 <Steps>
 <Step title="Query processing">
 Mem0 cleans and enriches your natural-language query so the downstream embedding search is accurate.
@@ -156,6 +152,10 @@ const memories = memory.search("food preferences", {
   Expect an array of memory documents. Platform responses include vectors, metadata, and timestamps; OSS returns your stored schema.
 </Info>
 
+<Note>
+  On Mem0 Platform v3, time-aware queries use Temporal Reasoning internally while preserving the normal search response shape. See <Link href="/platform/features/temporal-reasoning">Temporal Reasoning</Link>.
+</Note>
+
 ## Filter patterns
 
 Filters help narrow down search results. Common use cases:
@@ -251,4 +251,4 @@ For the full list of filter logic, comparison operators, and optional search par
     icon="rocket"
     href="/cookbooks/operations/support-inbox"
   />
-</CardGroup>
+</CardGroup>

docs/core-concepts/memory-types.mdx

@@ -104,7 +104,7 @@ results = memory.search(
 ## Put it into practice
 
 - Use the <Link href="/core-concepts/memory-operations/add">Add Memory</Link> guide to persist user preferences.
-- Follow <Link href="/platform/advanced-memory-operations">Advanced Memory Operations</Link> to tune metadata and graph writes.
+- Follow <Link href="/platform/advanced-memory-operations">Advanced Memory Operations</Link> to tune metadata and retrieval.
 
 ## See it live
 

docs/docs.json

@@ -40,6 +40,7 @@
                     "icon": "rocket",
                     "pages": [
                       "platform/overview",
+                      "platform/agent-signup",
                       "vibecoding",
                       "platform/mem0-mcp",
                       "platform/cli",
@@ -72,7 +73,8 @@
                           "platform/features/entity-scoped-memory",
                           "platform/features/async-client",
                           "platform/features/multimodal-support",
-                          "platform/features/custom-categories"
+                          "platform/features/custom-categories",
+                          "platform/features/temporal-reasoning"
                         ]
                       },
                       {
@@ -83,7 +85,8 @@
                           "platform/advanced-memory-operations",
                           "platform/features/criteria-retrieval",
                           "platform/features/contextual-add",
-                          "platform/features/custom-instructions"
+                          "platform/features/custom-instructions",
+                          "platform/features/memory-decay"
                         ]
                       },
                       {
@@ -449,7 +452,9 @@
                     "pages": [
                       "integrations/claude-code",
                       "integrations/cursor",
-                      "integrations/codex"
+                      "integrations/codex",
+                      "integrations/opencode",
+                      "integrations/antigravity"
                     ]
                   },
                   {
@@ -1143,4 +1148,4 @@
       "destination": "/introduction"
     }
   ]
-}
+}

docs/integrations/antigravity.mdx

@@ -0,0 +1,82 @@
+---
+title: Antigravity
+description: "Add persistent memory to Google Antigravity with the Mem0 plugin — MCP server, lifecycle hooks, and slash commands."
+---
+
+Add persistent memory to [**Google Antigravity**](https://antigravity.google) (`agy` CLI and Desktop IDE) with the Mem0 plugin. Your agent forgets everything between sessions — Mem0 fixes that by storing decisions, preferences, and learnings so they carry over automatically.
+
+## Prerequisites
+
+1. A Mem0 API key (starts with `m0-`):
+   - <a href="https://app.mem0.ai/dashboard/api-keys?utm_source=oss&utm_medium=integration-antigravity" rel="nofollow">Get your API key</a> (free sign-up at <a href="https://app.mem0.ai?utm_source=oss&utm_medium=integration-antigravity" rel="nofollow">app.mem0.ai</a>)
+
+2. Add it to your shell profile so it persists across sessions:
+
+<CodeGroup>
+```bash zsh
+echo 'export MEM0_API_KEY="m0-your-api-key"' >> ~/.zshrc && source ~/.zshrc
+```
+
+```bash bash
+echo 'export MEM0_API_KEY="m0-your-api-key"' >> ~/.bashrc && source ~/.bashrc
+```
+</CodeGroup>
+
+## Installation
+
+**Option A — degit** (recommended):
+
+```bash
+# Install the plugin (MCP server, hooks, scripts)
+npx degit mem0ai/mem0/mem0-plugin ~/.gemini/config/plugins/mem0
+```
+
+This installs the MCP server, lifecycle hooks, and shared scripts.
+
+## What's Included
+
+| Component | Included |
+|-----------|:--------:|
+| MCP Server (9 memory tools) | Yes |
+| Lifecycle Hooks | Yes |
+| 16 Slash Commands | Yes |
+
+## Available MCP Tools
+
+| Tool | Description |
+|------|-------------|
+| `add_memory` | Save text or conversation history for a user/agent |
+| `search_memories` | Semantic search across memories with filters |
+| `get_memories` | List memories with filters and pagination |
+| `get_memory` | Retrieve a specific memory by ID |
+| `update_memory` | Overwrite a memory's text by ID |
+| `delete_memory` | Delete a single memory by ID |
+| `delete_all_memories` | Bulk delete all memories in scope |
+| `delete_entities` | Delete a user/agent/app/run entity and its memories |
+| `list_entities` | List users/agents/apps/runs stored in Mem0 |
+
+## Lifecycle Hooks
+
+The plugin uses the same shell scripts as Claude Code, Cursor, and Codex — hooks bridge environment variables using `${extensionPath}` (Antigravity's plugin-root token).
+
+| Hook | Event | What it does |
+|------|-------|-------------|
+| **Session start** | `SessionStart` | Loads prior memories and displays status banner |
+| **User prompt** | `UserPromptSubmit` | Searches relevant memories before each message |
+| **Pre-tool** | `PreToolUse` | Blocks MEMORY.md writes, enforces `user_id`/`app_id` on mem0 tools |
+| **Post-tool** | `PostToolUse` | Tracks stats, scans bash errors for related memories |
+
+## Troubleshooting
+
+- **No tools appearing** — Restart your Antigravity session after installation
+- **"Connection failed"** — Verify your key is set: `echo $MEM0_API_KEY`
+- **MCP 401 Unauthorized** — If `${MEM0_API_KEY}` interpolation doesn't work in your `agy` version, replace with your literal key in `mcp_config.json`
+
+<CardGroup cols={2}>
+  <Card title="Mem0 MCP Setup" icon="puzzle-piece" href="/platform/mem0-mcp">
+    Detailed MCP configuration for all clients
+  </Card>
+  <Card title="OpenCode Integration" icon="code" href="/integrations/opencode">
+    Add Mem0 memory to OpenCode workflows
+  </Card>
+</CardGroup>

docs/integrations/claude-code.mdx

@@ -5,13 +5,6 @@ description: "Add persistent memory to Claude Code and Claude Cowork with the Me
 
 Add persistent memory to [**Claude Code**](https://docs.anthropic.com/en/docs/claude-code) (CLI) and **Claude Cowork** (desktop app) with the Mem0 plugin. Your agent forgets everything between sessions — this plugin fixes that by connecting to Mem0's cloud memory layer via MCP, automatically capturing learnings at key lifecycle points, and retrieving relevant context before every response.
 
-## Overview
-
-1. **MCP Server** — Connect to Mem0's remote MCP server for memory tools (add, search, update, delete)
-2. **Lifecycle Hooks** — Automatic memory capture at session start, context compaction, task completion, and session end
-3. **SDK Skill** — Teaches the agent how to integrate the Mem0 SDK into your applications
-4. **Zero local dependencies** — Cloud-hosted MCP server, no local setup required
-
 ## Prerequisites
 
 Before setting up Mem0 with Claude Code, ensure you have:
@@ -22,10 +15,25 @@ Before setting up Mem0 with Claude Code, ensure you have:
 
 2. Claude Code CLI or Claude Cowork desktop app installed
 
-3. Your API key exported in your shell:
+3. Your API key added to your shell profile (persists across sessions):
+
+<CodeGroup>
+```bash zsh
+echo 'export MEM0_API_KEY="m0-your-api-key"' >> ~/.zshrc
+source ~/.zshrc
+```
+
+```bash bash
+echo 'export MEM0_API_KEY="m0-your-api-key"' >> ~/.bashrc
+source ~/.bashrc
+```
+</CodeGroup>
+
+Confirm it's set:
 
 ```bash
-export MEM0_API_KEY="m0-your-api-key"
+echo $MEM0_API_KEY
+# Should print: m0-your-api-key
 ```
 
 ## Installation
@@ -84,6 +92,22 @@ Add to your Claude Code MCP config (`.mcp.json`):
   Start a new session and ask: *"List my mem0 entities"* or *"Search my memories for hello"*. If the `mem0` tools appear and respond, you're all set.
 </Info>
 
+## Post-Installation: Run `/mem0:onboard`
+
+After installing the plugin, start a new Claude Code session and run:
+
+```
+/mem0:onboard
+```
+
+This runs the setup wizard which:
+1. Verifies your API key and MCP connection
+2. Detects and imports project files (`CLAUDE.md`, `AGENTS.md`, `.cursorrules`)
+3. Installs coding-optimized memory categories
+4. Shows your identity (user ID, project scope, branch)
+
+The onboarding is idempotent — safe to re-run anytime. It auto-triggers on first session in a new project, but you can always invoke it manually.
+
 ## What's Included
 
 | Component | Plugin Install | MCP Only |
@@ -112,20 +136,13 @@ Once installed, the following tools are available in every Claude Code session:
 
 When installed via the plugin marketplace, Mem0 hooks into Claude Code's lifecycle to automatically manage memory:
 
-### Session Start
-On every new session, the plugin prompts Claude to call `search_memories` to load relevant context from prior sessions. On resumed or post-compaction sessions, it adjusts the prompt accordingly.
-
-### User Prompt
-Before processing each user message, the plugin searches Mem0 for memories relevant to the current prompt and injects them into context. Short prompts (< 20 characters) are skipped to minimize latency.
-
-### Pre-Compaction
-Before context compaction, the plugin prompts Claude to store a comprehensive session summary — including goals, accomplishments, decisions, modified files, and current state — so nothing is lost.
-
-### Task Completed
-After each task completion, the plugin prompts Claude to extract and store key learnings: successful strategies, failed approaches, architectural decisions, and new conventions.
-
-### Session End
-When Claude finishes responding, the plugin prompts for any unstored learnings and captures transcript state via the Mem0 REST API as a background safety net.
+| Hook | Event | What it does |
+|------|-------|-------------|
+| **Session start** | `SessionStart` | Loads prior memories and displays status banner |
+| **User prompt** | `UserPromptSubmit` | Searches relevant memories before each message; skips short prompts |
+| **Pre-tool** | `PreToolUse` | Blocks MEMORY.md writes, enforces `user_id`/`app_id` on mem0 tool calls |
+| **Post-tool** | `PostToolUse` | Tracks stats, scans bash errors for related memories |
+| **Pre-compact** | `PreCompact` | Stores a session summary before context compaction |
 
 ## Example Workflow
 
@@ -149,9 +166,10 @@ You: Add refresh token rotation to the auth system.
 
 ## Troubleshooting
 
-- **"Connection failed"** — Verify `MEM0_API_KEY` is set in your shell: `echo $MEM0_API_KEY`
+- **"Connection failed"** — Verify `MEM0_API_KEY` is set in your shell: `echo $MEM0_API_KEY`. If empty, add it to your shell profile (see Prerequisites)
 - **No tools appearing** — Restart your Claude Code session after installation
-- **Memories not being captured** — Ensure you installed via the plugin marketplace (Option A) for lifecycle hooks. MCP-only installs require manual memory operations.
+- **Memories not being captured** — Ensure you installed via the plugin marketplace (Option A) for lifecycle hooks. MCP-only installs require manual memory operations
+- **"Mem0 Inactive" banner every session** — Your API key isn't persisting. Add `export MEM0_API_KEY="m0-..."` to your `~/.zshrc` (or `~/.bashrc`) and run `source ~/.zshrc`
 
 <CardGroup cols={2}>
   <Card title="Mem0 MCP Setup" icon="puzzle-piece" href="/platform/mem0-mcp">

docs/integrations/codex.mdx

@@ -1,16 +1,9 @@
 ---
 title: Codex
-description: "Add persistent memory to OpenAI Codex with the Mem0 plugin — MCP server, memory protocol skill, and plugin marketplace support."
+description: "Add persistent memory to OpenAI Codex with the Mem0 plugin — MCP server, lifecycle hooks, and SDK skill."
 ---
 
-Add persistent memory to [**OpenAI Codex**](https://openai.com/index/codex/) with the Mem0 plugin. Codex forgets everything between tasks — this plugin fixes that by connecting to Mem0's cloud memory layer via MCP and using a skill-based memory protocol to automatically retrieve context and store learnings.
-
-## Overview
-
-1. **MCP Server** — Connect to Mem0's remote MCP server for memory tools (add, search, update, delete)
-2. **Memory Protocol Skill** — Instructs the agent to retrieve memories at task start, store learnings on completion, and capture session state before context loss
-3. **Plugin Marketplace** — Install via Codex's repo-level or personal plugin marketplace
-4. **Zero local dependencies** — Cloud-hosted MCP server, no local setup required
+Add persistent memory to [**OpenAI Codex**](https://openai.com/index/codex/) with the Mem0 plugin. Codex forgets everything between tasks — this plugin fixes that by connecting to Mem0's cloud memory layer via MCP, automatically capturing learnings at key lifecycle points, and retrieving relevant context before every response.
 
 ## Prerequisites
 
@@ -22,90 +15,67 @@ Before setting up Mem0 with Codex, ensure you have:
 
 2. OpenAI Codex access
 
-3. Your API key exported in your shell:
+3. Your API key added to your shell profile (persists across sessions):
 
-```bash
-export MEM0_API_KEY="m0-your-api-key"
+<CodeGroup>
+```bash zsh
+echo 'export MEM0_API_KEY="m0-your-api-key"' >> ~/.zshrc
+source ~/.zshrc
 ```
 
+```bash bash
+echo 'export MEM0_API_KEY="m0-your-api-key"' >> ~/.bashrc
+source ~/.bashrc
+```
+</CodeGroup>
+
 ## Installation
 
-### Option A — Repo Marketplace (Recommended for Teams)
+### Option A — Plugin Marketplace (Recommended)
 
-Add a `.agents/plugins/marketplace.json` to your repository root:
+Install the full plugin including MCP server, lifecycle hooks, and SDK skill.
 
-```json
-{
-  "name": "mem0-plugins",
-  "interface": {
-    "displayName": "Mem0 Plugins"
-  },
-  "plugins": [
-    {
-      "name": "mem0",
-      "source": {
-        "source": "local",
-        "path": "./plugins/mem0"
-      },
-      "policy": {
-        "installation": "AVAILABLE",
-        "authentication": "ON_INSTALL"
-      },
-      "category": "Productivity"
-    }
-  ]
-}
+1. Add the Mem0 marketplace:
+
+   ```bash
+   codex plugin marketplace add mem0ai/mem0
+   ```
+
+2. Restart Codex, open the Plugin Directory, browse the **Mem0 Plugins** marketplace, and install **Mem0**.
+
+<Info>
+  Do not combine with Option B. The plugin manifest auto-registers the `mem0` MCP server, so adding both will create a duplicate registration.
+</Info>
+
+### Option B — Direct MCP
+
+The fastest way to connect Codex to Mem0 — no plugin, no marketplace. Add to `~/.codex/config.toml`:
+
+```toml
+[mcp_servers.mem0]
+url = "https://mcp.mem0.ai/mcp"
+bearer_token_env_var = "MEM0_API_KEY"
 ```
 
-Then in Codex, browse the repo's plugin directory and install Mem0.
+Make sure `MEM0_API_KEY` is exported in the shell you launch Codex from, then restart Codex.
 
-### Option B — Personal Marketplace
+<Info>
+  Codex's `codex mcp add` CLI only supports stdio MCP servers. Because Mem0's MCP is HTTP/streamable, you configure it by editing `config.toml` directly (or via the **Plugins → Connect to a custom MCP → Streamable HTTP** UI in the Codex app).
+</Info>
 
-Add to `~/.agents/plugins/marketplace.json`:
+This gives you the MCP tools but not the lifecycle hooks or SDK skill.
 
-```json
-{
-  "name": "mem0-plugins",
-  "interface": {
-    "displayName": "Mem0 Plugins"
-  },
-  "plugins": [
-    {
-      "name": "mem0",
-      "source": {
-        "source": "local",
-        "path": "/path/to/mem0-plugin"
-      },
-      "policy": {
-        "installation": "AVAILABLE",
-        "authentication": "ON_INSTALL"
-      },
-      "category": "Productivity"
-    }
-  ]
-}
+### Managing the Plugin
+
+```bash
+codex plugin marketplace upgrade               # pull latest plugin versions
+codex plugin marketplace remove mem0-plugins   # unregister the marketplace
 ```
 
-### Option C — Manual MCP Configuration
-
-Add to your Codex MCP config:
-
-```json
-{
-  "mcpServers": {
-    "mem0": {
-      "type": "http",
-      "url": "https://mcp.mem0.ai/mcp/",
-      "headers": {
-        "Authorization": "Token ${MEM0_API_KEY}"
-      }
-    }
-  }
-}
-```
+To update, run `codex plugin marketplace upgrade` to pull the latest from the Mem0 repo.
 
 <Info icon="check">
-  Start a new Codex task and ask: *"List my mem0 entities"* or *"Search my memories for hello"*. If the `mem0` tools appear and respond, you're all set.
+  After either option, start a new Codex task and ask: *"List my mem0 entities"* or *"Search my memories for hello"*. If the `mem0` tools appear and respond, you're all set.
 </Info>
 
 ## What's Included
@@ -113,7 +83,7 @@ Add to your Codex MCP config:
 | Component | Plugin Install | MCP Only |
 |-----------|:--------------:|:--------:|
 | MCP Server (9 memory tools) | Yes | Yes |
-| Memory Protocol Skill | Yes | No |
+| Lifecycle Hooks | Yes | No |
 | Mem0 SDK Skill | Yes | No |
 
 ## Available MCP Tools
@@ -132,49 +102,17 @@ Once installed, the following tools are available in every Codex session:
 | `delete_entities` | Delete a user/agent/app/run entity and its memories |
 | `list_entities` | List users/agents/apps/runs stored in Mem0 |
 
-## Memory Protocol Skill
+## Lifecycle Hooks
 
-Codex uses a skill-based approach instead of lifecycle hooks. When installed via the plugin marketplace, the memory protocol skill instructs the agent to:
+When installed via the plugin marketplace, Mem0 hooks into Codex's lifecycle to automatically manage memory:
 
-### On Every New Task
-1. Call `search_memories` with a query related to the current task to load relevant context
-2. Review returned memories to understand what was learned in prior sessions
-3. Optionally call `get_memories` to browse all stored memories
-
-### After Completing Significant Work
-Store key learnings using `add_memory` with structured metadata:
-
-| What to store | Metadata type |
-|--------------|---------------|
-| Architectural decisions | `{"type": "decision"}` |
-| Strategies that worked | `{"type": "task_learning"}` |
-| Failed approaches | `{"type": "anti_pattern"}` |
-| User preferences observed | `{"type": "user_preference"}` |
-| Environment discoveries | `{"type": "environmental"}` |
-| Conventions established | `{"type": "convention"}` |
-
-### Before Losing Context
-Store a comprehensive session summary including goals, accomplishments, decisions, files modified, and current state with metadata `{"type": "session_state"}`.
-
-## Plugin Manifest
-
-The Codex plugin manifest (`.codex-plugin/plugin.json`) follows the Codex plugin specification:
-
-```json
-{
-  "name": "mem0",
-  "version": "0.1.0",
-  "description": "Mem0 memory layer for AI applications.",
-  "skills": "./skills/",
-  "mcpServers": "./.codex-mcp.json",
-  "interface": {
-    "displayName": "Mem0",
-    "shortDescription": "Persistent memory layer for AI coding workflows",
-    "category": "Productivity",
-    "capabilities": ["Read", "Write"]
-  }
-}
-```
+| Hook | Event | What it does |
+|------|-------|-------------|
+| **Session start** | `SessionStart` | Loads prior memories and displays status banner |
+| **User prompt** | `UserPromptSubmit` | Searches relevant memories before each message |
+| **Pre-tool** | `PreToolUse` | Blocks MEMORY.md writes, enforces `user_id`/`app_id` on mem0 tool calls |
+| **Post-tool** | `PostToolUse` | Tracks stats, scans bash errors for related memories |
+| **Pre-compact** | `PreCompact` | Stores a session summary before context compaction |
 
 ## Example Workflow
 
@@ -197,10 +135,10 @@ You: Add WebSocket support for real-time notification delivery.
 
 ## Troubleshooting
 
-- **"Connection failed"** — Verify `MEM0_API_KEY` is set in your shell: `echo $MEM0_API_KEY`
-- **No tools appearing** — Restart your Codex session after plugin installation
-- **Plugin not found** — Ensure `.agents/plugins/marketplace.json` is at the repository root and `source.path` points to the correct plugin directory
-- **Skills not loading** — Verify the `skills` field in `plugin.json` points to a valid directory containing `SKILL.md` files
+- **"Connection failed"** — Verify `MEM0_API_KEY` is set: `echo $MEM0_API_KEY`
+- **No tools appearing** — Restart your Codex session after installation
+- **Duplicate `mem0` MCP / "tool collision" errors** — You combined Option A with Option B. Remove the `[mcp_servers.mem0]` block from `~/.codex/config.toml`; the plugin registers it automatically
+- **Hooks not firing** — Ensure the plugin is installed via the marketplace (Option A). MCP-only installs do not include hooks
 
 <CardGroup cols={2}>
   <Card title="Mem0 MCP Setup" icon="puzzle-piece" href="/platform/mem0-mcp">

docs/integrations/cursor.mdx

@@ -5,13 +5,6 @@ description: "Add persistent memory to Cursor with the Mem0 plugin — MCP serve
 
 Add persistent memory to [**Cursor**](https://cursor.com) with the Mem0 plugin. Your AI assistant forgets everything between sessions — this plugin fixes that by connecting to Mem0's cloud memory layer via MCP, automatically capturing learnings at key lifecycle points, and retrieving relevant context before every response.
 
-## Overview
-
-1. **MCP Server** — Connect to Mem0's remote MCP server for memory tools (add, search, update, delete)
-2. **Lifecycle Hooks** — Automatic memory capture at session start, compaction, and user prompts (Marketplace install)
-3. **SDK Skill** — Teaches the agent how to integrate the Mem0 SDK into your applications
-4. **Zero local dependencies** — Cloud-hosted MCP server, no local setup required
-
 ## Prerequisites
 
 Before setting up Mem0 with Cursor, ensure you have:
@@ -22,12 +15,20 @@ Before setting up Mem0 with Cursor, ensure you have:
 
 2. Cursor installed ([cursor.com](https://cursor.com))
 
-3. Your API key exported in your shell:
+3. Your API key added to your shell profile (persists across sessions):
 
-```bash
-export MEM0_API_KEY="m0-your-api-key"
+<CodeGroup>
+```bash zsh
+echo 'export MEM0_API_KEY="m0-your-api-key"' >> ~/.zshrc
+source ~/.zshrc
 ```
 
+```bash bash
+echo 'export MEM0_API_KEY="m0-your-api-key"' >> ~/.bashrc
+source ~/.bashrc
+```
+</CodeGroup>
+
 <Warning>
   Already have `mem0` configured as an MCP server in Cursor? Remove the existing entry from your Cursor MCP settings before installing to avoid duplicate tools.
 </Warning>
@@ -103,14 +104,13 @@ Once installed, the following tools are available in every Cursor session:
 
 When installed via the Cursor Marketplace, Mem0 hooks into Cursor's lifecycle:
 
-### Session Start
-On every new session, the plugin prompts the agent to call `search_memories` to load relevant context from prior sessions.
-
-### User Prompt
-Before processing each user message, the plugin searches Mem0 for relevant memories and injects them into context. Short prompts are skipped to minimize latency.
-
-### Pre-Compaction
-Before context compaction, the plugin captures a comprehensive session summary so nothing is lost when the context window resets.
+| Hook | Event | What it does |
+|------|-------|-------------|
+| **Session start** | `sessionStart` | Loads prior memories and displays status banner |
+| **User prompt** | `beforeSubmitPrompt` | Searches relevant memories before each message; skips short prompts |
+| **Pre-tool (2 handlers)** | `preToolUse` | Blocks MEMORY.md writes, enforces `user_id`/`app_id` on mem0 tool calls |
+| **Post-tool (2 handlers)** | `postToolUse` | Tracks stats, scans bash errors for related memories |
+| **Pre-compact** | `preCompact` | Stores a session summary before context compaction |
 
 ## Example Workflow
 

docs/integrations/openclaw.mdx

@@ -1,6 +1,6 @@
 ---
 title: OpenClaw
-description: "Add long-term memory to OpenClaw agents using the Mem0 plugin with auto-recall and auto-capture support."
+description: "Add long-term memory to OpenClaw agents using the Mem0 plugin with skills-based memory extraction and recall."
 ---
 
 Add long-term memory to [OpenClaw](https://github.com/openclaw/openclaw) agents with the `@mem0/openclaw-mem0` plugin. Your agent forgets everything between sessions — this plugin fixes that by automatically watching conversations, extracting what matters, and bringing it back when relevant.
@@ -12,11 +12,12 @@ Add long-term memory to [OpenClaw](https://github.com/openclaw/openclaw) agents
 </Frame>
 
 The plugin provides:
-1. **Auto-Recall** — Before the agent responds, memories matching the current message are injected into context
-2. **Auto-Capture** — After the agent responds, the exchange is sent to Mem0 which decides what's worth keeping
-3. **Agent Tools** — Eight tools for explicit memory operations during conversations
+1. **Triage** — The agent extracts durable facts from conversations using a structured protocol with importance gates and domain overlays
+2. **Recall** — Before each turn, relevant memories are retrieved with reranking and injected into context
+3. **Dream** — Periodic memory consolidation: merges duplicates, resolves conflicts, prunes stale entries
+4. **Agent Tools** — Eight tools for explicit memory operations during conversations
 
-Both auto-recall and auto-capture are opt-in (`autoRecall: true`, `autoCapture: true` in config). Once enabled, they run silently with no manual intervention required.
+Skills mode, `autoRecall`, and `autoCapture` are all enabled by default during `openclaw mem0 init`.
 
 ## Requirements
 
@@ -24,12 +25,12 @@ Check your OpenClaw version:
 
 ```bash
 openclaw --version
-# OpenClaw 2026.4.15 (041266a)
+# OpenClaw 2026.4.25 (aa36ee6)
 ```
 
 | OpenClaw Version | Plugin Support |
 |------------------|----------------|
-| `>= 2026.4.15`   | Fully supported |
+| `>= 2026.4.25`   | Fully supported |
 
 ## Installation
 
@@ -100,9 +101,9 @@ You no longer need manual config editing to get started. Everything happens insi
   </Step>
 </Steps>
 
-That's it. No API key, no config file editing, no environment variables. The plugin is now active and auto-capture and auto-recall are running on every turn.
+That's it. No API key, no config file editing, no environment variables. The plugin is now active with skills-based memory (triage, recall, and dream) running automatically.
 
-<Note>The chat flow uses the same underlying config as manual setup — it writes `apiKey` and `userId` into `openclaw.json` for you. You can still open the file to inspect or override values afterward.</Note>
+<Note>The chat flow uses the same underlying config as manual setup — it writes `apiKey`, `userId`, and `skills` config into `openclaw.json` for you. You can still open the file to inspect or override values afterward.</Note>
 
 #### Option 2: Manual Config
 
@@ -131,7 +132,19 @@ That's it. No API key, no config file editing, no environment variables. The plu
             "enabled": true,
             "config": {
               "apiKey": "${MEM0_API_KEY}",
-              "userId": "alice"  // any unique identifier you choose for this user
+              "userId": "alice",  // any unique identifier you choose for this user
+              "skills": {
+                "triage": { "enabled": true },
+                "recall": {
+                  "enabled": true,
+                  "tokenBudget": 1500,
+                  "rerank": true,
+                  "keywordSearch": true,
+                  "identityAlwaysInclude": true
+                },
+                "dream": { "enabled": true },
+                "domain": "companion"
+              }
             }
           }
         }
@@ -328,8 +341,8 @@ openclaw mem0 status --json
 |-----|------|---------|-------------|
 | `mode` | `"platform"` \| `"open-source"` | `"platform"` | Which backend to use |
 | `userId` | `string` | OS username | Scope memories per user |
-| `autoRecall` | `boolean` | `false` | Inject memories before each turn (opt-in) |
-| `autoCapture` | `boolean` | `false` | Store facts after each turn (opt-in) |
+| `autoRecall` | `boolean` | `true` | Inject memories before each turn. Ignored when `skills` is configured. |
+| `autoCapture` | `boolean` | `true` | Store facts after each turn. Ignored when `skills` is configured. |
 | `topK` | `number` | `5` | Max memories per recall |
 | `searchThreshold` | `number` | `0.3` | Min similarity (0–1) |
 
@@ -426,9 +439,11 @@ If `openclaw plugins update` fails:
 | **Platform** | Conversations sent to `api.mem0.ai` for extraction and storage | Mem0 cloud |
 | **Open-source** | Embeddings generated via configured provider (default: OpenAI API). Vectors stored locally. | `~/.mem0/vector_store.db` (SQLite) |
 
-### Enabling Auto-Capture and Auto-Recall
+### Auto-Capture and Auto-Recall
 
-Auto-capture and auto-recall are disabled by default (opt-in). To enable either or both:
+Auto-capture and auto-recall are **enabled by default**. When skills mode is configured (the default after `openclaw mem0 init`), these are ignored in favor of the skills-based triage/recall/dream protocol.
+
+To disable either:
 
 ```json5
 {
@@ -436,8 +451,8 @@ Auto-capture and auto-recall are disabled by default (opt-in). To enable either
     "entries": {
       "openclaw-mem0": {
         "config": {
-          "autoCapture": true,   // send conversations to Mem0 for extraction
-          "autoRecall": true     // inject relevant memories into context
+          "autoCapture": false,   // disable automatic fact extraction
+          "autoRecall": false     // disable automatic memory injection
         }
       }
     }
@@ -445,7 +460,7 @@ Auto-capture and auto-recall are disabled by default (opt-in). To enable either
 }
 ```
 
-Without these enabled, the agent can still use memory tools (`memory_add`, `memory_search`, etc.) explicitly — only the automatic background behavior is off.
+The agent can always use memory tools (`memory_add`, `memory_search`, etc.) explicitly regardless of these settings.
 
 ### Credential Protection
 

docs/integrations/opencode.mdx

@@ -0,0 +1,119 @@
+---
+title: OpenCode
+description: "Add persistent memory to OpenCode with the Mem0 plugin — MCP server, lifecycle hooks, and slash commands."
+---
+
+Add persistent memory to [**OpenCode**](https://opencode.ai) with the Mem0 plugin. Your agent forgets everything between sessions — Mem0 fixes that by storing decisions, preferences, and learnings so they carry over automatically.
+
+## Prerequisites
+
+1. A Mem0 API key (starts with `m0-`):
+   - <a href="https://app.mem0.ai/dashboard/api-keys?utm_source=oss&utm_medium=integration-opencode" rel="nofollow">Get your API key</a> (free sign-up at <a href="https://app.mem0.ai?utm_source=oss&utm_medium=integration-opencode" rel="nofollow">app.mem0.ai</a>)
+
+2. Add it to your shell profile so it persists across sessions:
+
+<CodeGroup>
+```bash zsh
+echo 'export MEM0_API_KEY="m0-your-api-key"' >> ~/.zshrc && source ~/.zshrc
+```
+
+```bash bash
+echo 'export MEM0_API_KEY="m0-your-api-key"' >> ~/.bashrc && source ~/.bashrc
+```
+</CodeGroup>
+
+## Installation
+
+### Option A — Plugin Install (Recommended)
+
+```bash
+opencode plugin @mem0/opencode-plugin
+```
+
+
+Or using this command which does the same thing:
+
+
+```bash
+bunx @mem0/opencode-plugin@latest install
+```
+
+
+
+**Or let your agent do it** — paste this into OpenCode:
+
+```
+Install @mem0/opencode-plugin by following https://raw.githubusercontent.com/mem0ai/mem0/main/mem0-plugin/.opencode-plugin/README.md
+```
+
+All commands auto-add the plugin and MCP server to your `~/.config/opencode/opencode.json`. Restart OpenCode — you get the MCP server, lifecycle hooks, and all `/mem0:` slash commands.
+
+### Option B — MCP Only
+
+If you only need the memory tools without hooks or skills, add this to your `opencode.json` (project-level or global at `~/.config/opencode/opencode.json`):
+
+```json
+{
+  "mcp": {
+    "mem0": {
+      "type": "remote",
+      "url": "https://mcp.mem0.ai/mcp/",
+      "headers": {
+        "Authorization": "Token {env:MEM0_API_KEY}"
+      },
+      "oauth": false
+    }
+  }
+}
+```
+
+## What's Included
+
+| Component | Plugin (A) | MCP Only (B) |
+|-----------|:----------:|:------------:|
+| MCP Server (9 memory tools) | Yes | Yes |
+| Lifecycle Hooks | Yes | No |
+| 16 Slash Commands | Yes | No |
+
+## Available MCP Tools
+
+| Tool | Description |
+|------|-------------|
+| `add_memory` | Save text or conversation history for a user/agent |
+| `search_memories` | Semantic search across memories with filters |
+| `get_memories` | List memories with filters and pagination |
+| `get_memory` | Retrieve a specific memory by ID |
+| `update_memory` | Overwrite a memory's text by ID |
+| `delete_memory` | Delete a single memory by ID |
+| `delete_all_memories` | Bulk delete all memories in scope |
+| `delete_entities` | Delete a user/agent/app/run entity and its memories |
+| `list_entities` | List users/agents/apps/runs stored in Mem0 |
+
+## Lifecycle Hooks
+
+The plugin uses the [mem0ai](https://www.npmjs.com/package/mem0ai) TypeScript SDK directly — pure TypeScript, no Python, no shell scripts.
+
+| OpenCode Event | Hook | What happens |
+|----------------|------|-------------|
+| `chat.message` | **Chat message** | Searches prior memories on session start, searches relevant memories before each prompt, auto-captures learnings periodically |
+| `tool.execute.before` | **Pre-tool** | Blocks MEMORY.md writes, injects `user_id`/`app_id` on mem0 tool calls |
+| `tool.execute.after` | **Post-tool** | Tracks stats, scans Bash errors and pre-fetches related error memories |
+| `experimental.chat.system.transform` | **System transform** | Injects memory context (session memories, search results, error lookups) into the system prompt |
+| `experimental.session.compacting` | **Compaction** | Stores session state memory, then injects prior memories into compaction context so nothing is lost |
+| `shell.env` | **Shell env** | Exports `MEM0_USER_ID`, `MEM0_APP_ID`, `MEM0_SESSION_ID`, and `MEM0_BRANCH` to all shell executions |
+
+## Troubleshooting
+
+- **No tools appearing** — Restart OpenCode after installing
+- **"Connection failed"** — Verify your key is set: `echo $MEM0_API_KEY`
+- **Plugin not loading** — Run `opencode plugin @mem0/opencode-plugin` again, then restart
+- **Hooks not firing** — Hooks require the plugin install (Option A). MCP-only installs don't include hooks.
+
+<CardGroup cols={2}>
+  <Card title="Mem0 MCP Setup" icon="puzzle-piece" href="/platform/mem0-mcp">
+    Detailed MCP configuration for all clients
+  </Card>
+  <Card title="Antigravity Integration" icon="google" href="/integrations/antigravity">
+    Add Mem0 memory to Google Antigravity
+  </Card>
+</CardGroup>

docs/introduction.mdx

@@ -12,7 +12,7 @@ mode: "custom"
   </h1>
 
   <p className="max-w-2xl mx-auto text-base text-gray-600 dark:text-zinc-400 leading-relaxed">
-    Universal, Self-improving memory layer for LLM applications.
+    Universal, self-improving memory layer for LLM applications.
   </p>
 
   <a
@@ -157,27 +157,27 @@ mode: "custom"
     </a>
 
     <a
-      href="/platform/cli"
+      href="/platform/agent-signup"
       className="group flex h-full flex-col overflow-hidden rounded-2xl border border-gray-200 dark:border-zinc-800/40 bg-white dark:bg-zinc-900/40 transition hover:border-primary/60 hover:bg-gray-50 dark:hover:bg-zinc-900"
     >
       <img
         className="block dark:hidden aspect-[2/1] w-full object-cover"
         src="/images/docs thumbnails/light/CLI.png"
-        alt="CLI thumbnail"
+        alt="Sign up as an agent thumbnail"
         style={{pointerEvents: "none"}}
       />
       <img
         className="hidden dark:block aspect-[2/1] w-full object-cover"
         src="/images/docs thumbnails/dark/CLI.png"
-        alt="CLI thumbnail"
+        alt="Sign up as an agent thumbnail"
         style={{pointerEvents: "none"}}
       />
       <div className="flex flex-1 flex-col gap-2 px-4 pb-4 pt-3 text-left">
         <h3 className="text-base font-semibold text-gray-900 dark:text-zinc-100 group-hover:text-primary">
-          CLI
+          Sign up as an agent
         </h3>
         <p className="text-sm text-gray-600 dark:text-zinc-400">
-          Manage memories directly from your terminal. Built for developers and AI agents.
+          For AI agents: mint a Mem0 API key in under five seconds — no email, no dashboard. Four commands to your first memory.
         </p>
       </div>
     </a>

docs/llms.txt

@@ -4,6 +4,24 @@
 
 ## For agents reading this file
 
+### Don't have a Mem0 API key?
+
+Install the CLI, then mint a key — no email, no dashboard, no OTP required:
+
+```bash
+# Python
+pip install mem0-cli
+
+# or Node
+npm install -g @mem0/cli
+```
+
+Then run: `mem0 init --agent --agent-caller <your-name> --json` — replace `<your-name>` with the AI agent you are (e.g. `claude-code`, `cursor`, `codex`). If you forgot to pass `--agent-caller`, run `mem0 identify <your-name>` after init to attribute the signup.
+
+This mints an evaluation key in <5 seconds. Use it immediately against the Platform API or MCP server. When the human is ready, claim with `mem0 init --email <your-email>` to transfer ownership (memories preserved, same API key, no agent disruption).
+
+### Routing and references
+
 - Use `MemoryClient` (Python) / `mem0ai` (npm) when the user has a Mem0 Platform API key. Docs under `/platform/` and `/api-reference/` apply; the managed product handles providers server-side, so you can ignore `## Optional` below.
 - Use `Memory` (Python) / `mem0ai/oss` (npm) when the user self-hosts. Docs under `/open-source/` and `/components/` apply; Platform-only features (entity filters v2, custom categories, webhooks, advanced retrieval) may not be available.
 - Scope tag reference: `[Platform]` = managed only, `[OSS]` = self-hosted only, `[Both]` = same API surface on both.
@@ -153,6 +171,7 @@ If the user is on a pre-current major (Python < 2, TS < 3, or Platform `output_f
 - [Introduction](https://docs.mem0.ai/introduction) [Both]: Use when the user wants a one-page overview of how memory fits between the LLM and the app.
 - [Vibe Code with Mem0](https://docs.mem0.ai/vibecoding) [Both]: Use when the user is in Claude Code, Cursor, or Windsurf and wants memory wired into their editor.
 - [Platform Overview](https://docs.mem0.ai/platform/overview) [Platform]: Use when the user picks the managed product - 4-line integration, sub-50ms retrieval, dashboard.
+- [Sign up as an agent](https://docs.mem0.ai/platform/agent-signup) [Platform]: Use when an AI agent needs to mint a Mem0 API key autonomously - four commands, no email or dashboard, human claims ownership later.
 - [Platform vs Open Source](https://docs.mem0.ai/platform/platform-vs-oss) [Both]: Use when the user is deciding between managed and self-hosted.
 - [Platform Quickstart](https://docs.mem0.ai/platform/quickstart) [Platform]: Use for the first Platform integration - API key plus `MemoryClient.add/search`.
 - [Platform CLI](https://docs.mem0.ai/platform/cli) [Platform]: Use when the user wants to manage Platform memories from the terminal.
@@ -185,8 +204,10 @@ If the user is on a pre-current major (Python < 2, TS < 3, or Platform `output_f
 ### Features - Advanced Retrieval
 - [Advanced Retrieval](https://docs.mem0.ai/platform/features/advanced-retrieval) [Platform]: Use when the user needs keyword search, reranking, or hybrid retrieval.
 - [Criteria-Based Retrieval](https://docs.mem0.ai/platform/features/criteria-retrieval) [Platform]: Use when targeting memories by custom criteria, not just semantic similarity.
+- [Temporal Reasoning](https://docs.mem0.ai/platform/features/temporal-reasoning) [Platform]: Use when time-aware searches like last week, upcoming, or right now need better result ordering.
 - [Contextual Add](https://docs.mem0.ai/platform/features/contextual-add) [Platform]: Use when `add()` should consider the surrounding conversation, not just the latest turn.
 - [Custom Instructions](https://docs.mem0.ai/platform/features/custom-instructions) [Platform]: Use when tailoring what Mem0 extracts and stores on Platform.
+- [Memory Decay](https://docs.mem0.ai/platform/features/memory-decay) [Platform]: Use when search results should boost recently-reinforced memories and dampen stale ones — opt-in per project, search-time only, never filters candidates out.
 - [Advanced Memory Operations](https://docs.mem0.ai/platform/advanced-memory-operations) [Platform]: Use when basic CRUD is not enough - batch ops, complex filters, workflows.
 
 ### Features - Data Management
@@ -247,6 +268,8 @@ If the user is on a pre-current major (Python < 2, TS < 3, or Platform `output_f
 - [Claude Code](https://docs.mem0.ai/integrations/claude-code) [Both]: Use when wiring memory into Claude Code.
 - [Cursor](https://docs.mem0.ai/integrations/cursor) [Both]: Use when wiring memory into Cursor.
 - [Codex](https://docs.mem0.ai/integrations/codex) [Both]: Use when wiring memory into Codex / other editor assistants.
+- [OpenCode](https://docs.mem0.ai/integrations/opencode) [Both]: Use when wiring memory into OpenCode.
+- [Antigravity](https://docs.mem0.ai/integrations/antigravity) [Both]: Use when wiring memory into Google Antigravity.
 
 ### Voice & Real-time
 - [LiveKit](https://docs.mem0.ai/integrations/livekit) [Both]: Use when building real-time voice/video with memory.
@@ -375,13 +398,15 @@ Each subdirectory is a Claude Code Skill (`SKILL.md` + supporting assets). Load
 
 Source: https://github.com/mem0ai/mem0/tree/main/mem0-plugin
 
-The `mem0-plugin/` directory provides MCP server connection, lifecycle hooks, and skill bundling for Claude Code, Cursor, and Codex. It exposes 9 MCP tools: `add_memory`, `search_memories`, `get_memories`, `get_memory`, `update_memory`, `delete_memory`, `delete_all_memories`, `delete_entities`, `list_entities`.
+The `mem0-plugin/` directory provides MCP server connection, lifecycle hooks, and skill bundling for Claude Code, Cursor, Codex, OpenCode, and Antigravity. It exposes 9 MCP tools: `add_memory`, `search_memories`, `get_memories`, `get_memory`, `update_memory`, `delete_memory`, `delete_all_memories`, `delete_entities`, `list_entities`.
 
 Editor-specific setup docs (already listed above under `## Integrations > AI Coding Tools`):
 
 - `integrations/claude-code` [Both]
 - `integrations/cursor` [Both]
 - `integrations/codex` [Both]
+- `integrations/opencode` [Both]
+- `integrations/antigravity` [Both]
 - `integrations/openclaw` [Both]
 
 ### MCP Endpoints

docs/migration/oss-to-platform.mdx

@@ -14,11 +14,15 @@ Move your Mem0 implementation to managed infrastructure with enterprise features
 | --------------------- | -------------- | ---------------------------- |
 | Infrastructure & Code | Low (~30 mins) | None (Parallel run possible) |
 
+<Info>
+  Using Mem0 Open Source with **hosted Qdrant**? You can migrate your existing memories to Mem0 Platform with a one-line script below.
+</Info>
+
 <Info>
   **Why migrate to Platform?**
 
   - **Time to Market**: Set up in 5 minutes vs 30+ minutes for OSS configuration
-  - **Enterprise Ready**: SOC2 Type II compliance, GDPR support, audit logs
+  - **Enterprise Ready**: Audit logs, workspace governance, and dedicated support
   - **Advanced Features**: Webhooks, memory export, analytics dashboard, custom categories
   - **Multi-tenancy**: Organizations, projects, and team management out of the box
   - **Zero Infrastructure**: No vector database, LLM provider, or maintenance overhead
@@ -34,7 +38,21 @@ Move your Mem0 implementation to managed infrastructure with enterprise features
 
 ## Migrate
 
-### 1. Install or Update SDK
+### 1. Import Memories Into Platform
+
+If your Mem0 Open Source setup uses **hosted Qdrant** as the vector store, you can import your existing memories to Mem0 Platform with one command:
+
+```bash
+curl -fsSL https://raw.githubusercontent.com/mem0ai/mem0/main/scripts/oss-to-platform-migrate.sh | bash
+```
+
+<Note>
+  This migration script currently supports **hosted Qdrant only**. Support for local Qdrant, pgvector, and other vector stores is coming soon.
+</Note>
+
+If you are using a different vector store and want to migrate to Platform, please contact Mem0 support and we’ll send you a custom migration script for your setup.
+
+### 2. Install or Update SDK
 
 Ensure you have the latest version of the SDK, which supports both OSS and Platform clients.
 
@@ -42,7 +60,7 @@ Ensure you have the latest version of the SDK, which supports both OSS and Platf
 pip install mem0ai --upgrade
 ```
 
-### 2. Update Initialization
+### 3. Update Initialization
 
 Switch from the local `Memory` class to the managed `MemoryClient`.
 
@@ -75,7 +93,7 @@ client = MemoryClient(api_key="m0-...")
   Run `client.get_all(filters={"user_id": "test_connection"})` to verify your API key works. It should return an empty list or valid results.
 </Info>
 
-### 3. Update Retrieval Calls (Critical)
+### 4. Update Retrieval Calls (Critical)
 
 <Warning>
   **Critical Change**: Platform uses v2 endpoints that require filtering parameters to be nested inside a `filters` dictionary.

docs/migration/platform-v2-to-v3.mdx

@@ -42,7 +42,7 @@ Previously, when an agent said something like "I've booked your flight for March
 
 ### Retrieval is hybrid now
 
-Search now uses hybrid retrieval, which improves ranking quality — especially for queries involving exact keywords, proper nouns, or entities that appear across multiple memories. The response shape is unchanged:
+Search now uses hybrid retrieval, which improves ranking quality — especially for queries involving exact keywords, proper nouns, entities that appear across multiple memories, and time-aware queries (via Temporal Reasoning). The response shape is unchanged:
 
 ```json
 {
@@ -58,7 +58,7 @@ Search now uses hybrid retrieval, which improves ranking quality — especially
 }
 ```
 
-The top-level `score` remains a `[0, 1]` value. Relative ranking between results stays comparable to v2, but absolute numbers shift since the scoring method changed — retune any hard thresholds in your app against representative queries.
+The top-level `score` remains a `[0, 1]` value. Relative ranking between results stays comparable to v2, but absolute numbers shift since the scoring method changed — retune any hard thresholds in your app against representative queries. Temporal signals are applied internally during ranking and are not returned as extra client-facing fields.
 
 ## API Changes
 
@@ -289,6 +289,7 @@ If your application previously read graph relations from the API response (`rela
 - **V1 and V2 endpoints continue to work.** There is no requirement to migrate to V3 endpoints immediately.
 - **Existing memories are preserved.** The new algorithm does not modify or re-process previously stored memories.
 - **Search response shape is unchanged.** The top-level `score` and `results[]` array are the same; existing code that reads `score` continues to work. What changed is the scoring method behind the number (multi-signal fusion instead of pure cosine), so the absolute values shift even when ranking stays comparable.
+- **Search remains backward-compatible at the top level.** Existing code that reads `results[]` and `score` continues to work. Temporal signals are applied internally during retrieval and do not change the client response shape.
 - **List response shape changed.** `get_all` now returns a paginated envelope (`{count, next, previous, results}`) instead of a bare `{results: [...]}`. Update code that reads `response["results"]` to continue working, or switch to the client SDKs which handle both shapes.
 
 ## Performance Improvements

docs/open-source/features/metadata-filtering.mdx

@@ -4,22 +4,7 @@ description: Fine-grained metadata queries for precise OSS memory retrieval.
 icon: "filter"
 ---
 
-Enhanced metadata filtering in Mem0 1.0.0 lets you run complex queries across memory metadata. Combine comparisons, logical operators, and wildcard matches to zero in on the exact memories your agent needs.
-
-<Info>
-  **You’ll use this when…**
-  - Retrieval must respect multiple metadata conditions before returning context.
-  - You need to mix numeric, boolean, and string filters in a single query.
-  - Agents rely on deterministic filtering instead of broad semantic search alone.
-</Info>
-
-<Warning>
-  Enhanced filtering requires Mem0 1.0.0 or later and a vector store that supports the operators you enable. Unsupported operators fall back to simple equality filters.
-</Warning>
-
-<Note>
-  The TypeScript SDK accepts the same filter shape shown here—transpose the dictionaries to objects and reuse the keys unchanged.
-</Note>
+Enhanced metadata filtering in Mem0 lets you run complex queries across memory metadata. Combine comparisons, logical operators, and wildcard matches to zero in on the exact memories your agent needs.
 
 ---
 
@@ -148,8 +133,8 @@ Combine filters with `AND`, `OR`, and `NOT` to express complex decision trees. N
 results = m.search(
     "complex query",
     filters={
+        "user_id": "alice",
         "AND": [
-            {"user_id": "alice"},
             {"category": "work"},
             {"priority": {"gte": 7}},
             {"status": {"ne": "completed"}}
@@ -161,15 +146,11 @@ results = m.search(
 results = m.search(
     "flexible query",
     filters={
-        "AND": [
-            {"user_id": "alice"},
-            {
-                "OR": [
-                    {"category": "urgent"},
-                    {"priority": {"gte": 9}},
-                    {"deadline": {"contains": "today"}}
-                ]
-            }
+        "user_id": "alice",
+        "OR": [
+            {"category": "urgent"},
+            {"priority": {"gte": 9}},
+            {"deadline": {"contains": "today"}}
         ]
     }
 )
@@ -178,14 +159,10 @@ results = m.search(
 results = m.search(
     "exclusion query",
     filters={
-        "AND": [
-            {"user_id": "alice"},
-            {
-                "NOT": [
-                    {"category": "archived"},
-                    {"status": "deleted"}
-                ]
-            }
+        "user_id": "alice",
+        "NOT": [
+            {"category": "archived"},
+            {"status": "deleted"}
         ]
     }
 )
@@ -194,8 +171,8 @@ results = m.search(
 results = m.search(
     "advanced query",
     filters={
+        "user_id": "alice",
         "AND": [
-            {"user_id": "alice"},
             {
                 "OR": [
                     {"category": "work"},
@@ -248,8 +225,8 @@ config = {
 ```python
 # More efficient: Filter on indexed fields first
 good_filters = {
+    "user_id": "alice",
     "AND": [
-        {"user_id": "alice"},
         {"category": "work"},
         {"content": {"contains": "meeting"}}
     ]
@@ -257,9 +234,9 @@ good_filters = {
 
 # Less efficient: Complex operations first
 avoid_filters = {
+    "user_id": "alice",
     "AND": [
-        {"description": {"icontains": "complex text search"}},
-        {"user_id": "alice"}
+        {"description": {"icontains": "complex text search"}}
     ]
 }
 ```
@@ -302,8 +279,8 @@ results = m.search(
 results = m.search(
     "query",
     filters={
+        "user_id": "alice",
         "AND": [
-            {"user_id": "alice"},
             {"category": "work"},
             {"status": {"ne": "archived"}},
             {"priority": {"gte": 5}}
@@ -327,8 +304,8 @@ results = m.search(
 results = m.search(
     "What tasks need attention?",
     filters={
+        "user_id": "project_manager",
         "AND": [
-            {"user_id": "project_manager"},
             {"project": {"in": ["alpha", ""]}},
             {"priority": {"gte": 8}},
             {"status": {"ne": "completed"}},
@@ -354,8 +331,8 @@ results = m.search(
 results = m.search(
     "pending support issues",
     filters={
+        "agent_id": "support_bot",
         "AND": [
-            {"agent_id": "support_bot"},
             {"ticket_status": {"ne": "resolved"}},
             {"priority": {"in": ["high", "critical"]}},
             {"created_date": {"gte": "2024-01-01"}},
@@ -380,8 +357,8 @@ results = m.search(
 results = m.search(
     "recommend content",
     filters={
+        "user_id": "reader123",
         "AND": [
-            {"user_id": "reader123"},
             {
                 "OR": [
                     {"genre": {"in": ["sci-fi", "fantasy"]}},

docs/open-source/features/overview.mdx

@@ -6,7 +6,7 @@ icon: "list"
 
 # Self-Hosting Features Overview
 
-Mem0 Open Source ships with capabilities that adapt memory behavior for production workloads—async operations, graph relationships, multimodal inputs, and fine-tuned retrieval. Configure these features with code or YAML to match your application's needs.
+Mem0 Open Source ships with capabilities that adapt memory behavior for production workloads—async operations, multimodal inputs, and fine-tuned retrieval. Configure these features with code or YAML to match your application's needs.
 
 <Info>
   Start with the <Link href="/open-source/python-quickstart">Python quickstart</Link> to validate basic memory operations, then enable the features below when you need them.

docs/open-source/features/rest-api.mdx

@@ -119,7 +119,7 @@ docker build -t mem0-api-server .
 </Tip>
 
 <Note>
-  The REST server reads the same configuration you use locally, so you can point it at your preferred LLM, vector store, graph backend, and reranker without changing code.
+  The REST server reads the same configuration you use locally, so you can point it at your preferred LLM, vector store, and reranker without changing code.
 </Note>
 
 ---
@@ -319,7 +319,7 @@ The `/auth/*`, `/api-keys`, `/requests`, and `/entities` routes are new to the s
 
 <CardGroup cols={2}>
   <Card title="Configure OSS Components" icon="sliders" href="/open-source/configuration">
-    Fine-tune LLMs, vector stores, and graph backends that power the REST server.
+    Fine-tune LLMs, vector stores, and rerankers that power the REST server.
   </Card>
   <Card title="Automate Agent Integrations" icon="plug" href="/cookbooks/integrations/agents-sdk-tool">
     See how services call the REST endpoints as part of an automation pipeline.

docs/openapi.json

@@ -419,7 +419,7 @@
 													},
 													"results": {
 														"type": "array",
-														"description": "Array of results produced by the event."
+														"description": "Array of results produced by the event. For add events, this confirms the write completed; temporal reasoning enrichment runs asynchronously by default."
 													},
 													"created_at": {
 														"type": "string",
@@ -2071,7 +2071,7 @@
 					"memories"
 				],
 				"summary": "Search memories (V3)",
-				"description": "Relevance-ranked search across stored memories. V3 uses hybrid retrieval — the returned `score` is a combined `[0, 1]` value; per-signal component scores are not exposed on the response. Entity IDs **must** be passed inside the `filters` object — top-level `user_id` / `agent_id` / `run_id` are rejected with 400. At least one entity ID is required.",
+				"description": "Relevance-ranked search across stored memories. V3 uses hybrid retrieval and can also apply temporal reasoning for time-aware queries. Entity IDs **must** be passed inside the `filters` object — top-level `user_id` / `agent_id` / `run_id` are rejected with 400. At least one entity ID is required.",
 				"operationId": "memories_search_v3",
 				"requestBody": {
 					"required": true,
@@ -2112,6 +2112,21 @@
 										"type": "boolean",
 										"default": false,
 										"description": "Apply the managed reranker for better ordering (adds latency)."
+									},
+									"reference_date": {
+										"oneOf": [
+											{
+												"type": "integer"
+											},
+											{
+												"type": "number"
+											},
+											{
+												"type": "string"
+											}
+										],
+										"nullable": true,
+										"description": "Optional query anchor time for relative temporal interpretation. Accepts Unix epoch, YYYY-MM-DD, or ISO datetime."
 									}
 								}
 							},

docs/platform/advanced-memory-operations.mdx

@@ -64,7 +64,7 @@ const memory = new Memory({ apiKey: process.env.MEM0_API_KEY!, async: true });
   </Tab>
 </Tabs>
 
-## Add memories with metadata and graph context
+## Add memories with metadata
 
 <Tabs>
   <Tab title="Python">
@@ -109,7 +109,7 @@ const result = await memory.add(conversation, {
 </Tabs>
 
 <Info icon="check">
-  Successful calls return memories tagged with the metadata you passed. In the dashboard, confirm a graph edge between “Morgan” and “Tokyo” and verify the `trip=japan-2025` tag exists.
+  Successful calls return memories tagged with the metadata you passed. In the dashboard, verify the `trip=japan-2025` tag exists on the new memory.
 </Info>
 
 ## Retrieve and refine
@@ -201,7 +201,7 @@ await memory.deleteAll({ userId: "traveler-42", runId: "planning-call-1" });
   />
   <Card
     title="Explore Reranker Search"
-    description="See how rerankers boost accuracy after vector + graph retrieval."
+    description="See how rerankers boost accuracy after advanced retrieval."
     icon="sparkles"
     href="/open-source/features/reranker-search"
   />

docs/platform/agent-signup.mdx

@@ -0,0 +1,106 @@
+---
+title: Sign up as an agent
+description: "Zero-friction signup for AI agents — mint a working Mem0 API key in under five seconds. No email, no dashboard, no OTP."
+icon: "robot"
+iconType: "solid"
+---
+
+If you're an AI agent (Claude Code, Cursor, Codex, Cline, Aider, Windsurf, or any other autonomous coding tool), you don't need a human to set up Mem0 for you. Four commands — install, sign up, push a memory, search it — and you have persistent memory.
+
+## The 4-command demo
+
+<CodeGroup>
+```bash npm
+# 1. Install
+npm install -g @mem0/cli
+
+# 2. Sign up as an agent (replace `claude-code` with your name)
+mem0 init --agent --agent-caller claude-code
+
+# 3. Push a memory
+mem0 add "I am using mem0"
+
+# 4. Verify
+mem0 search "am I using mem0"
+```
+
+```bash pip
+# 1. Install
+pip install mem0-cli
+
+# 2. Sign up as an agent (replace `claude-code` with your name)
+mem0 init --agent --agent-caller claude-code
+
+# 3. Push a memory
+mem0 add "I am using mem0"
+
+# 4. Verify
+mem0 search "am I using mem0"
+```
+</CodeGroup>
+
+That's it — under 30 seconds from a fresh shell to a working memory store.
+
+## Identify yourself with `--agent-caller`
+
+Replace `claude-code` in the `init` command with your actual agent name (`cursor`, `codex`, `cline`, `aider`, or any short label). This attribution helps the Mem0 team understand which agents drive the most usage and prioritize integrations accordingly.
+
+<Tip>
+**Forgot `--agent-caller` on init?** Run `mem0 identify <your-name>` after the fact — same key, just back-fills the attribution. Idempotent.
+</Tip>
+
+## What happened when you ran `mem0 init --agent`?
+
+- A **shadow account** was minted on the Mem0 backend with a fresh API key.
+- The key was saved to `~/.mem0/config.json` (mode 0600) on the machine you ran the command on.
+- A default `user_id` was provisioned so `mem0 add` / `mem0 search` work without explicit scope flags.
+- The account is **unclaimed** — no human owns it yet.
+
+Every command run against this key prints a one-line reminder asking you to surface the claim instructions to your human user.
+
+## Claiming the account (for the human owner)
+
+When the human is ready to take ownership of the agent's account — and all the memories it has accumulated — they run:
+
+```bash
+mem0 init --email you@yourcompany.com
+```
+
+The CLI detects the existing Agent Mode config, sends a verification code, and upgrades the shadow account in-place:
+
+- **The API key never changes** — the agent isn't disrupted.
+- **All memories transfer** to the human's account.
+- **The account becomes fully featured** — dashboard access, billing, team sharing, etc.
+
+Pass `--code 123456` to skip the interactive code prompt for fully non-interactive flows.
+
+## Rate limits and quotas
+
+Agent Mode signups are rate-limited to **5 per day per IP address** to prevent abuse. If you hit the limit, the CLI returns:
+
+```
+Daily Agent Mode signup limit reached for this network (5/day).
+Try again from a different IP or after midnight UTC.
+```
+
+Unclaimed agent accounts get the standard Mem0 free-tier quotas. The human owner can upgrade after claiming.
+
+## What's next
+
+<CardGroup cols={2}>
+<Card title="CLI Reference" icon="terminal" href="/platform/cli">
+Full command-by-command reference for `mem0 add`, `mem0 search`, `mem0 list`, and the rest.
+</Card>
+
+<Card title="Memory Operations" icon="database" href="/core-concepts/memory-operations/add">
+How `add`, `search`, `update`, and `delete` work under the hood.
+</Card>
+
+<Card title="Mem0 MCP" icon="plug" href="/platform/mem0-mcp">
+Connect agents to Mem0 via the Model Context Protocol — alternative integration path.
+</Card>
+
+<Card title="Platform Overview" icon="star" href="/platform/overview">
+The full Mem0 Platform feature set once you claim your account.
+</Card>
+</CardGroup>

docs/platform/cli.mdx

@@ -25,6 +25,10 @@ pip install mem0-cli
 ```
 </CodeGroup>
 
+<Tip>
+**Looking for Agent Mode signup?** See [Sign up as an agent](/platform/agent-signup) — install, signup, first memory in four commands.
+</Tip>
+
 ## Authentication
 
 Run the interactive setup wizard to configure your API key:
@@ -95,6 +99,10 @@ mem0 init --api-key m0-xxx --user-id alice --force
 | `--code` | Verification code (use with `--email` for non-interactive login) |
 | `--force` | Overwrite existing config without confirmation |
 
+<Note>
+AI agents should use `mem0 init --agent` — see [Sign up as an agent](/platform/agent-signup).
+</Note>
+
 ### `mem0 add`
 
 Add a memory from text, a JSON messages array, a file, or stdin.
@@ -113,7 +121,6 @@ echo "Loves hiking on weekends" | mem0 add --user-id alice
 | `-f, --file` | Read messages from a JSON file |
 | `-m, --metadata` | Custom metadata as JSON |
 | `--categories` | Categories (JSON array or comma-separated) |
-| `--graph / --no-graph` | Enable or disable graph memory extraction |
 | `-o, --output` | Output format: `text`, `json`, `quiet` |
 
 ### `mem0 search`
@@ -133,7 +140,6 @@ mem0 search "preferred tools" --user-id alice --output json --top-k 5
 | `--rerank` | Enable reranking |
 | `--keyword` | Use keyword search instead of semantic |
 | `--filter` | Advanced filter expression (JSON) |
-| `--graph / --no-graph` | Enable or disable graph in search |
 | `-o, --output` | Output format: `text`, `json`, `table` |
 
 ### `mem0 list`
@@ -263,6 +269,92 @@ Print the CLI version.
 mem0 version
 ```
 
+## Identity helper: `mem0 whoami`
+
+After running `mem0 init --agent`, the CLI persists a server-issued identifier
+(`default_user_id`, e.g. `user_a1b2c3d4e5f6`) in `~/.mem0/config.json`. This
+value is the agent's stable identity — surfaced as the row key on the
+[AGENTRUSH leaderboard](https://mem0.ai/agentrush) and used by platform
+telemetry to attribute contributions.
+
+Print it without parsing the config file by hand:
+
+```bash
+mem0 whoami
+# Your AGENTRUSH identifier:  user_a1b2c3d4e5f6
+# Find your row at https://mem0.ai/agentrush
+```
+
+No network call. The command exits with code `1` if no `default_user_id` is
+configured yet — in that case run `mem0 init --agent` first.
+
+## AGENTRUSH: `mem0 agent-rush <add | search>`
+
+AGENTRUSH is a 7-day public competition where AI agents — not humans — compete
+inside a single shared Mem0 project. Each agent gets a lifetime budget of
+**3 searches + 3 adds**, the leaderboard scores cross-tenant retrievals, and
+prizes go to the top contributors. See [mem0.ai/agentrush](https://mem0.ai/agentrush)
+for current event details.
+
+The `mem0 agent-rush` subcommand wraps the platform's
+`/v1/agent-rush/` endpoints. Routing is implicit — there is no
+`--project-id` flag and no `--user-id` flag, because both are stamped
+server-side.
+
+### Bootstrap once, then play
+
+```bash
+# 1. Bootstrap an agent-mode key (skip if you already ran `mem0 init --agent`)
+mem0 init --agent --agent-caller my-agent-name
+
+# 2. Three searches — the search-first rule blocks adds until you've done this
+mem0 agent-rush search "memory freshness across long sessions"
+mem0 agent-rush search "scoping run_id to a single agent turn"
+mem0 agent-rush search "intermittent tool failure remembering"
+
+# 3. Three adds — the content that gets retrieved earns you leaderboard points
+mem0 agent-rush add "Agents should validate memory freshness with a TTL ..."
+mem0 agent-rush add "Scoping memories by run_id avoids cross-session ..."
+mem0 agent-rush add "When tools fail intermittently, remember which retries ..."
+
+# 4. Check your row
+mem0 whoami
+# Then visit https://mem0.ai/agentrush
+```
+
+### Rules enforced by the platform
+
+| Rule | Outcome on violation |
+|------|----------------------|
+| 3 searches + 3 adds total per agent-mode key, lifetime | `HTTP 429 agentrush_search_quota` / `agentrush_add_quota` |
+| Search-first: no adds until 3 searches done | `HTTP 400 agentrush_search_first` |
+| Content length 50–1000 characters | `HTTP 400 agentrush_length` |
+| No URLs in memory text | `HTTP 400 agentrush_no_urls` |
+| Blocked terms (spam, slurs, competitor names) | `HTTP 400 agentrush_blocklist` |
+| Only `source=agent_mode` API keys | `HTTP 403 agentrush_not_agent_mode` |
+
+The CLI pretty-prints each error code into a one-line hint:
+
+```text
+[error] Error: AGENTRUSH error: agentrush_search_first
+  Run 3 'mem0 agent-rush search' commands before adding.
+```
+
+### Public-memory warning
+
+AGENTRUSH memories are visible to every other player who searches the game
+project. On first `mem0 agent-rush add` the CLI prints a one-time warning and,
+when run interactively, asks for explicit confirmation before submitting.
+**Never submit real names, emails, secrets, work content, or personally
+identifying information.** The acknowledgement is stored under
+`agent_rush.acknowledged_at` in `~/.mem0/config.json` so you are only asked
+once per machine.
+
+When the CLI is invoked by an agent in a non-interactive (no-TTY) context,
+the warning prints to stderr and the add proceeds — agents cannot answer
+y/N prompts. Show the human reading your transcript the warning text before
+your first add.
+
 ## Output formats
 
 All commands support the `--output` flag to control how results are displayed:
@@ -342,7 +434,6 @@ For non-interactive environments (CI, agent runtimes), set credentials via `mem0
 | `MEM0_AGENT_ID` | Default agent ID |
 | `MEM0_APP_ID` | Default app ID |
 | `MEM0_RUN_ID` | Default run ID |
-| `MEM0_ENABLE_GRAPH` | Enable graph memory (`true` / `false`) |
 
 Environment variables take precedence over values in the config file, which take precedence over defaults.
 

docs/platform/faqs.mdx

@@ -9,7 +9,7 @@ iconType: "solid"
     <Accordion title="How does Mem0 work?">
         Mem0 utilizes a sophisticated hybrid database system to efficiently manage and retrieve memories for AI agents and assistants. Each memory is linked to a unique identifier, such as a user ID or agent ID, enabling Mem0 to organize and access memories tailored to specific individuals or contexts.
 
-        When a message is added to Mem0 via the `add` method, the system extracts pertinent facts and preferences, distributing them across various data stores: a vector database and a graph database. This hybrid strategy ensures that diverse types of information are stored optimally, facilitating swift and effective searches.
+        When a message is added to Mem0 via the `add` method, the system extracts pertinent facts and preferences, distributing them in a managed vector store. This strategy ensures that diverse types of information are stored optimally, facilitating swift and effective searches.
 
         When an AI agent or LLM needs to access memories, it employs the `search` method. Mem0 conducts a comprehensive search across these data stores, retrieving relevant information from each.
 
@@ -142,6 +142,24 @@ iconType: "solid"
         Setting this environment variable will prevent Mem0 from collecting and sending any usage data, ensuring complete privacy for your application.
     </Accordion>
 
+    <Accordion title="How do I delete my Mem0 account?">
+        You can delete your Mem0 account at any time directly from the dashboard:
+
+        1. Sign in at [app.mem0.ai](https://app.mem0.ai).
+        2. Go to **Settings → Account**.
+        3. Click **Delete account** and confirm.
+
+        Deletion is immediate and irreversible. The following is removed:
+
+        - Your user profile and login credentials
+        - All memories, agents, and runs you created
+        - API keys and access tokens issued to your account
+        - Organizations you solely own, along with their data
+        - Your membership in any shared organizations (the orgs themselves are not affected)
+
+        Any application still using your old API keys will start receiving `401 Unauthorized` responses immediately. If you'd like to use Mem0 again later, you can create a new account at any time — it will start fresh with no data carried over.
+    </Accordion>
+
 </AccordionGroup>
 
 

docs/platform/features/mcp-integration.mdx

@@ -53,7 +53,7 @@ For detailed per-client instructions, see the [Mem0 MCP Quickstart](/platform/me
 
 ## Available tools
 
-The MCP server exposes 9 memory tools to your AI client:
+The MCP server exposes 11 memory tools to your AI client:
 
 | Tool | Purpose |
 |------|---------|
@@ -66,6 +66,8 @@ The MCP server exposes 9 memory tools to your AI client:
 | `delete_entities` | Remove user/agent/app entities |
 | `get_memory` | Retrieve single memory by ID |
 | `list_entities` | View stored entities |
+| `list_events` | List memory operation events with filters and pagination |
+| `get_event_status` | Check the status of an async memory operation by `event_id` |
 
 ## How it works
 
@@ -128,7 +130,6 @@ The Mem0 MCP server enables powerful memory capabilities for your AI application
 
 ## Performance tips
 
-- Enable graph memories for relationship-aware recall
 - Use specific filters when searching large memory sets
 - Batch operations when adding multiple memories
 - Monitor memory usage in the Mem0 dashboard

docs/platform/features/memory-decay.mdx

@@ -0,0 +1,191 @@
+---
+title: Memory Decay
+description: "Boost recently-used memories and gently dampen stale ones at search time, without filtering anything out."
+---
+
+# Memory Decay
+
+Older memories drift in relevance at different speeds. A user's coffee order matters every morning; a one-off project name from last quarter rarely matters again. Memory Decay makes that intuition explicit at search time: every time a memory is returned in a search it gets a small reinforcement, and memories that haven't been touched in a while have their ranking score gently dampened.
+
+It is **a soft ranking bias, never a filter.** Decay never zeroes a candidate out — at worst it scales its score by `0.3×`. Anything that would have surfaced without decay can still surface with decay on, just with a different ranking among similarly-scored results.
+
+<Info>
+  **Use Memory Decay when…**
+  - Search results are crowded with old facts the user no longer cares about.
+  - You want recently-used memories to drift to the top automatically — without writing custom scoring logic.
+  - You want this preference applied per project so cohorts can be compared side-by-side.
+</Info>
+
+<Warning>
+  Memory Decay is **opt-in per project** and **off by default**. Search behavior is bit-identical to today until you turn it on. The toggle applies to v3 search only.
+</Warning>
+
+## How it works
+
+Every memory carries a small piece of bookkeeping: when was it last retrieved, and how often. Memory Decay turns that history into a *scaling factor* in the range `0.3×` to `1.5×` and multiplies it into the ranking score at search time.
+
+| Memory state | Scaling factor | Ranking effect |
+|---|---|---|
+| Just accessed | ≈ **1.5×** | Strong boost |
+| Touched today | 1.2 – 1.4× | Mild boost |
+| Idle for a few days | 0.6 – 1.0× | Mild dampening |
+| Idle for weeks | 0.4 – 0.6× | Stronger dampening |
+| Idle for many months / years | ≈ **0.3×** | Floor — never lower |
+
+The bounds matter: `0.3` is the floor and `1.5` is the ceiling, so decay can meaningfully reorder candidates without ever dominating the underlying relevance score.
+
+At search time the pipeline:
+
+1. Widens the candidate pool (`top_k × 3`, with a floor of 50) so reordering has room.
+2. Multiplies each candidate's score by its scaling factor.
+3. Sorts on the unclamped product so the full `0.3×–1.5×` range can rearrange candidates.
+4. Returns the public `score` clamped to `[0, 1]` so the API contract is preserved.
+5. Truncates to the `top_k` you requested.
+6. Records a fire-and-forget reinforcement against each returned memory — its access history grows by one, capped at the most recent 20 touches.
+
+Memories created before decay was enabled don't yet have an access history. They use a sensible fallback: their `updated_at` is treated as a single past touch, so the same scale above applies based on how stale that update is — a recently-updated legacy memory enters near the neutral band, a long-stale one sits closer to the floor. Once surfaced in a search after decay is on, they accumulate access history naturally and behave like any other memory.
+
+## Configure access
+
+- Set `MEM0_API_KEY` in your environment, or pass it to the SDK constructor.
+- Initialize the client with the organization and project you want to scope to.
+
+The toggle lives on the project. You enable decay by patching the project's `decay` field; everything else — your `add` calls, your `search` calls, your application code — stays exactly the same.
+
+## Enable decay for a project
+
+### 1. Turn the flag on
+
+The toggle is exposed on the standard project-update endpoint, the same place where `multilingual` and `custom_categories` live.
+
+<CodeGroup>
+```python Python
+client.project.update(decay=True)
+```
+
+```javascript JavaScript
+await client.project.update({ decay: true });
+```
+
+```bash cURL
+curl -X PATCH https://api.mem0.ai/api/v1/orgs/organizations/$ORG_ID/projects/$PROJECT_ID/ \
+  -H "Authorization: Token $MEM0_API_KEY" \
+  -H "Content-Type: application/json" \
+  -d '{"decay": true}'
+```
+
+```json Response
+{ "message": "Updated decay" }
+```
+</CodeGroup>
+
+### 2. Confirm the state
+
+`decay` is returned on every project read. To fetch only this field, use `?fields=decay`.
+
+<CodeGroup>
+```python Python
+response = client.project.get(fields=["decay"])
+print(response["decay"])
+```
+
+```javascript JavaScript
+const response = await client.project.get({ fields: ["decay"] });
+console.log(response.decay);
+```
+
+```bash cURL
+curl "https://api.mem0.ai/api/v1/orgs/organizations/$ORG_ID/projects/$PROJECT_ID/?fields=decay" \
+  -H "Authorization: Token $MEM0_API_KEY"
+```
+
+```json Response
+{ "decay": true }
+```
+</CodeGroup>
+
+### 3. Turn it back off
+
+The toggle is fully reversible. Setting it to `false` immediately restores the pre-decay ranking; nothing about your stored memories is modified or lost.
+
+<CodeGroup>
+```python Python
+client.project.update(decay=False)
+```
+
+```javascript JavaScript
+await client.project.update({ decay: false });
+```
+
+```bash cURL
+curl -X PATCH https://api.mem0.ai/api/v1/orgs/organizations/$ORG_ID/projects/$PROJECT_ID/ \
+  -H "Authorization: Token $MEM0_API_KEY" \
+  -H "Content-Type: application/json" \
+  -d '{"decay": false}'
+```
+</CodeGroup>
+
+<Note>
+  The toggle is idempotent. Re-applying the same value is a no-op, and access history accumulated while decay was on is preserved if you flip it back on later.
+</Note>
+
+## What changes when decay is on
+
+- **Search ranking reorders.** A relevant memory you reinforced an hour ago will tend to outrank an equally-relevant memory that was last touched a month ago.
+- **The candidate pool over-fetches** to give the scaling factor room to reorder. You still get exactly the `top_k` you requested, but the items returned can come from a deeper slice of the pre-decay ranking than before.
+- **The public `score` field stays in `[0, 1]`.** Even when the internal product exceeds 1, the field returned to the client is clamped, so existing assertions and downstream UI logic continue to work.
+
+## What stays the same
+
+- **Public API shape** — every endpoint accepts the same parameters and returns the same fields. You don't touch your client code.
+- **Threshold semantics on the request side** — your `threshold` is still applied during candidate selection.
+- **Memory creation and storage** — every new memory still lands the same way. Decay is a search-time concern.
+- **Per-memory data** — categories, metadata, timestamps, embeddings: untouched.
+
+<Warning>
+  Because the scaling factor is applied *after* the threshold filter has already run, an item that passed the request `threshold` can come back with a public `score` slightly below it (a stale candidate dampened by `0.3×`). This is intentional — decay is a soft bias, not a filter. If you require a hard `score >= threshold` invariant on the response, filter client-side after the call.
+</Warning>
+
+## Lifecycle of a memory under decay
+
+| Stage | Scaling factor | Effect |
+|---|---|---|
+| Just added | ≈ 1.5× | Strong boost — fresh facts surface easily. |
+| Reinforced on a recent search | 1.2 – 1.5× | Sustains its boost for the next several searches. |
+| Idle for a few days | 0.6 – 1.0× | Falls back into the neutral band. |
+| Idle for weeks | 0.4 – 0.6× | Mild dampening — can still surface for strong matches. |
+| Pre-decay legacy memory (no access history) | 0.3 – 1.0× | Falls back to `updated_at`: recently-updated entries land near 1.0×, long-stale entries approach the 0.3× floor. |
+
+The reinforcement is bounded: each memory tracks at most the last 20 access timestamps, so the boost stays well-behaved no matter how many times a memory is retrieved.
+
+## FAQ
+
+**Will decay ever drop a result that would otherwise surface?**
+No. The floor is `0.3×` — the scaling factor can dampen a score, never zero it. Threshold filtering happens *before* decay, so any candidate that cleared the threshold is in the pool decay reorders.
+
+**Why is the public score sometimes below my requested threshold?**
+The threshold is applied to the candidate pool pre-decay; the scaling factor then reshapes scores in the `0.3×–1.5×` band. A stale-but-relevant candidate can come back with a final score slightly under your threshold by design — the candidate stays visible but visibly dampened. Filter client-side if you need a hard floor on the response.
+
+**Does decay change how I add memories?**
+No. The `client.add(...)` path is unchanged. Decay is a search-time ranking adjustment.
+
+**What if I had memories before turning decay on?**
+They use a fallback: the memory's `updated_at` is treated as a single historical touch, so the same scaling applies based on how stale that update is — a recently-updated legacy memory enters near the neutral band (~1.0×), a long-stale one closer to the floor (~0.3×). Once retrieved they accumulate access history and behave like any other memory.
+
+**Can I tune how aggressively decay scales scores?**
+Not in this version. The current scaling is calibrated to be conservative — wide enough to meaningfully reorder candidates, narrow enough to never dominate the underlying relevance score. Per-project tuning is on the roadmap.
+
+**Can I see the scaling factor per result?**
+Internal scoring details are persisted on the search Event for support and debugging. They aren't exposed in the public response by design — the response surface stays a single `score` field.
+
+**Does decay interact with reranking?**
+Yes — they layer cleanly. The reranker produces a richer relevance score; decay then biases that score by reinforcement history before final truncation to `top_k`.
+
+## What's next
+
+This release is deliberately the simplest version of decay we could ship — every memory contributes to ranking through its access history alone, so the signal can be evaluated in isolation. On the roadmap:
+
+- **Category-aware weighting.** A fact tagged `health` will be able to carry more weight than a passing observation tagged `misc`, so important categories don't get dampened the same way as noise.
+- **Auto-tuning per project.** Project-scoped automatic adjustment of how aggressively decay scales scores, based on observed access patterns — replacing the fixed scaling band with one that fits your workload.
+
+Both extensions are forward-compatible — no migration on your side will be needed when they ship.

docs/platform/features/platform-overview.mdx

@@ -1,10 +1,10 @@
 ---
 title: Overview
-description: "See how Mem0 Platform features evolve from baseline filters to graph-powered retrieval."
+description: "See how Mem0 Platform features evolve from baseline filters to advanced retrieval."
 icon: "list"
 ---
 
-Mem0 Platform features help managed deployments scale from basic filtering to graph-powered retrieval and data governance. Use this page to pick the right feature lane for your team.
+Mem0 Platform features help managed deployments scale from basic filtering to advanced retrieval and data governance. Use this page to pick the right feature lane for your team.
 
 <Info>
   New to the platform? Start with the <Link href="/platform/quickstart">Platform quickstart</Link>,

docs/platform/features/temporal-reasoning.mdx

@@ -0,0 +1,145 @@
+---
+title: Temporal Reasoning
+description: "Time-aware memory retrieval for Mem0 Platform v3 so queries like 'last week', 'upcoming', and 'right now' return the right memories."
+icon: "clock"
+badge: "v3"
+---
+
+Some memories matter because of **when** they happened, not just because they sound similar. Temporal Reasoning lets Mem0 Platform v3 understand time-aware queries and return the most contextually appropriate results.
+
+<Info>
+  **Use Temporal Reasoning when…**
+  - Users ask questions like "what happened last week?" or "what do I have coming up?"
+  - Your app stores both past events and future plans for the same person
+  - You want time-aware retrieval without building your own date-parsing layer
+</Info>
+
+<Warning>
+  Temporal Reasoning is a **Mem0 Platform v3** feature. It is not available on OSS memory stores or older Platform endpoints.
+</Warning>
+
+## Configure access
+
+Confirm your `MEM0_API_KEY` is set and that you are using the v3 Platform client:
+
+```python
+from mem0 import MemoryClient
+
+client = MemoryClient(api_key="your-api-key")
+```
+
+## How it works
+
+When a memory describes an event, a future plan, or an ongoing state, Temporal Reasoning recognizes the time context so the right results surface at search time.
+
+A query like `what did I do last week?` should return a completed past event — not an upcoming appointment and not a stable fact that hasn't changed. Temporal Reasoning handles that distinction automatically.
+
+### Memory types Temporal Reasoning handles
+
+| Type | What it represents | Example |
+| --- | --- | --- |
+| Dated occurrence | Something that happened at a known time | "I finished the Q1 review on March 10, 2025." |
+| Future plan | A future commitment or scheduled item | "I have a dentist appointment on March 18, 2025." |
+| Ongoing state | A fact that remains true over time | "I am the product lead at Acme Corp." |
+| Relationship | A durable connection between people or entities | "Priya manages Jordan." |
+| Preference | A stable preference or habit | "I prefer morning meetings." |
+
+Results come back in the normal search response shape — Temporal Reasoning affects ranking, not the response format.
+
+## Configure it
+
+Temporal Reasoning is enabled by default for all v3 searches and writes. There is no per-request toggle.
+
+Two parameters give you precise control when you need it:
+
+- `timestamp` on `add()` — anchors an imported memory to the time it actually happened, rather than the time it was added to Mem0
+- `reference_date` on `search()` — resolves relative phrases like `last week` against a fixed point in time
+
+<CodeGroup>
+```python Python
+from datetime import datetime, timezone
+from mem0 import MemoryClient
+
+client = MemoryClient(api_key="your-api-key")
+
+# Import a historical memory anchored to when it happened
+client.add(
+    [{"role": "user", "content": "I finished the Q1 review on March 10, 2025."}],
+    user_id="jordan",
+    timestamp=int(datetime(2025, 3, 10, tzinfo=timezone.utc).timestamp()),
+)
+
+# Search with a relative query anchored to a known date
+results = client.search(
+    "what did I do last week?",
+    filters={"user_id": "jordan"},
+    reference_date="2025-03-21T00:00:00Z",
+)
+```
+
+```javascript JavaScript
+import { MemoryClient } from "mem0ai";
+
+const client = new MemoryClient({ apiKey: "your-api-key" });
+
+// Import a historical memory anchored to when it happened
+await client.add(
+  [{ role: "user", content: "I finished the Q1 review on March 10, 2025." }],
+  {
+    userId: "jordan",
+    timestamp: Math.floor(new Date("2025-03-10T00:00:00Z").getTime() / 1000),
+  }
+);
+
+// Search with a relative query anchored to a known date
+const results = await client.search("what did I do last week?", {
+  filters: { user_id: "jordan" },
+  referenceDate: "2025-03-21T00:00:00Z",
+});
+```
+</CodeGroup>
+
+<Tip>
+  `reference_date` is especially useful in automated tests and demos because it makes relative phrases like `last week` resolve consistently every time.
+</Tip>
+
+## Supported query patterns
+
+<AccordionGroup>
+  <Accordion title="Historical questions">
+    Examples: `last week`, `last month`, `in March 2025`, `on 2025-03-10`
+  </Accordion>
+  <Accordion title="Upcoming questions">
+    Examples: `upcoming`, `next week`, `tomorrow`, `what do I have coming up?`
+  </Accordion>
+  <Accordion title="Current-state questions">
+    Examples: `right now`, `currently`, `where do I work now?`
+  </Accordion>
+  <Accordion title="As-of questions">
+    Examples: `as of March 2025`, `where was I living as of 2024?`
+  </Accordion>
+  <Accordion title="Duration questions">
+    Examples: `how long have I lived here?`, `since when have I worked there?`
+  </Accordion>
+</AccordionGroup>
+
+## Verify the feature is working
+
+- Run a temporal search with a time-aware query (e.g., "what did I do last week?") and confirm the memory that fits the time window ranks first.
+- Use `reference_date` in test queries so relative phrases resolve consistently across runs.
+- For backfilled data, pass `timestamp` on `add()` to confirm the memory reflects the right point in time.
+
+## Best practices
+
+- Use explicit dates in source conversations when events or plans matter temporally.
+- Pass `timestamp` during historical imports so the ingestion time does not become the only time anchor.
+- Scope searches with `filters` so time-aware ranking operates inside the right user boundary.
+- Use `reference_date` in automated tests and reproducible demos.
+
+<CardGroup cols={1}>
+  <Card title="Memory Timestamps" icon="calendar" href="/platform/features/timestamp">
+    Anchor imported memories to when they actually happened.
+  </Card>
+</CardGroup>
+
+<Snippet file="get-help.mdx" />

docs/platform/mem0-mcp.mdx

@@ -10,7 +10,7 @@ estimatedTime: "~2 minutes"
   - Mem0 Platform account (<a href="https://app.mem0.ai?utm_source=oss&utm_medium=platform-mem0-mcp" rel="nofollow">Sign up here</a>)
   - API key (<a href="https://app.mem0.ai/settings/api-keys?utm_source=oss&utm_medium=platform-mem0-mcp" rel="nofollow">Get one from dashboard</a>)
   - Node.js 14+ (for npx)
-  - An MCP-compatible client (Claude, Claude Code, Cursor, Windsurf, VS Code, OpenCode)
+  - An MCP-compatible client (Claude, Claude Code, Codex, Cursor, Windsurf, VS Code, OpenCode)
 </Info>
 
 ## What is Mem0 MCP?
@@ -46,6 +46,8 @@ The MCP server exposes these memory tools to your AI client:
 | `delete_all_memories` | Bulk delete all memories in scope |
 | `delete_entities` | Delete a user/agent/app/run entity and its memories |
 | `list_entities` | Enumerate users/agents/apps/runs stored in Mem0 |
+| `list_events` | List memory operation events with filters and pagination |
+| `get_event_status` | Check the status of an async memory operation by `event_id` |
 
 ---
 
@@ -86,6 +88,33 @@ You can also configure individual clients:
     ```
   </Accordion>
 
+  <Accordion title="Codex">
+    **Direct MCP (fastest, MCP only).** Codex reads MCP servers from `~/.codex/config.toml` as TOML (not JSON). Add:
+
+    ```toml
+    [mcp_servers.mem0]
+    url = "https://mcp.mem0.ai/mcp"
+    bearer_token_env_var = "MEM0_API_KEY"
+    ```
+
+    Export `MEM0_API_KEY` in the shell you launch Codex from, then restart Codex. `codex mcp add` only supports stdio servers, so HTTP servers must be added via `config.toml` directly — or via the **Plugins → Connect to a custom MCP → Streamable HTTP** UI in the Codex app.
+
+    <Note>
+      Codex uses the server name `mem0` (not `mem0-mcp` like the other clients on this page) so it matches the name the bundled plugin registers if you ever sideload it later.
+    </Note>
+
+    **Sideloaded plugin (full experience).** If you want the memory protocol skill, Mem0 SDK skill, and opt-in lifecycle hooks alongside the MCP server, sideload the plugin from a clone of `mem0ai/mem0`. The repo ships a marketplace manifest at `.agents/plugins/marketplace.json`, so you can register it with one CLI call:
+
+    ```bash
+    git clone https://github.com/mem0ai/mem0.git ~/codex-plugins/mem0-source
+    codex plugin marketplace add ~/codex-plugins/mem0-source
+    ```
+
+    Then run `codex` and `/plugins`, browse the **Mem0 Plugins** marketplace, and install **Mem0**. Don't combine this with the Direct MCP setup above — the sideloaded plugin auto-registers `mem0` via `.codex-mcp.json`, so a manual `[mcp_servers.mem0]` block would create a duplicate.
+
+    See the [Codex integration guide](/integrations/codex) for full details, lifecycle-hook setup, and management commands (`codex plugin marketplace upgrade` / `remove`).
+  </Accordion>
+
   <Accordion title="Cursor">
     ```bash
     npx mcp-add \

docs/platform/overview.mdx

@@ -11,8 +11,8 @@ Mem0 is the memory engine that keeps conversations contextual so users never rep
 ## Why it matters
 
 - **Personalized replies**: Memories persist across users and agents, cutting prompt bloat and repeat questions.
-- **Hosted stack**: Mem0 runs the vector store, graph services, and rerankers—no provisioning, tuning, or maintenance.
-- **Enterprise controls**: SOC 2, audit logs, and workspace governance ship by default for production readiness.
+- **Hosted stack**: Mem0 runs the vector store and rerankers—no provisioning, tuning, or maintenance.
+- **Enterprise controls**: Audit logs and workspace governance ship by default for production readiness.
 
 <AccordionGroup>
   <Accordion title="What you get with Mem0 Platform" icon="sparkles">
@@ -21,8 +21,8 @@ Mem0 is the memory engine that keeps conversations contextual so users never rep
     | --- | --- |
     | Fast setup | Add a few lines of code and you’re production-ready—no vector database or LLM configuration required. |
     | Production scale | Automatic scaling, high availability, and managed infrastructure so you focus on product work. |
-    | Advanced features | Graph memory, webhooks, multimodal support, and custom categories are ready to enable. |
-    | Enterprise ready | SOC 2 Type II, GDPR compliance, and dedicated support keep security and governance covered. |
+    | Advanced features | webhooks, multimodal support, and custom categories are ready to enable. |
+    | Enterprise ready | Audit logs, workspace governance, and dedicated support keep security and governance covered. |
   </Accordion>
 </AccordionGroup>
 
@@ -49,7 +49,7 @@ Mem0 is the memory engine that keeps conversations contextual so users never rep
     Add, search, update, and delete workflows.
   </Card>
   <Card title="Explore Platform Features" icon="sparkles" href="/platform/features/platform-overview">
-    Graph memory, async clients, and rerankers.
+    async clients and rerankers.
   </Card>
   <Card title="Configure Advanced Operations" icon="bolt" href="/platform/advanced-memory-operations">
     Metadata filters and per-request toggles.

docs/platform/platform-vs-oss.mdx

@@ -57,7 +57,6 @@ Mem0 offers two powerful ways to add memory to your AI applications. Choose base
   <Accordion title="Advanced Capabilities" icon="sparkles">
     | Feature | Platform | Open Source |
     |---------|----------|-------------|
-    | **Graph Memory** | ✅ (Managed) | ✅ (Self-configured) |
     | **Multimodal support** | ✅ | ✅ |
     | **Custom categories** | ✅ | Limited |
     | **Advanced retrieval** | ✅ | ✅ |

docs/platform/quickstart.mdx

@@ -7,6 +7,10 @@ iconType: "solid"
 
 Get started with Mem0 Platform's hosted API in under 5 minutes. This guide shows you how to authenticate and store your first memory.
 
+<Note>
+**Are you an AI agent?** See [Sign up as an agent](/platform/agent-signup) — mint a working API key in four commands, no email or dashboard required.
+</Note>
+
 ## Prerequisites
 
 - Mem0 Platform account (<a href="https://app.mem0.ai?utm_source=oss&utm_medium=platform-quickstart" rel="nofollow">Sign up here</a>)
@@ -151,7 +155,7 @@ Learn how to search, update, and delete memories with complete CRUD operations
 </Card>
 
 <Card title="Platform Features" icon="star" href="/platform/features/platform-overview">
-  Explore advanced features like metadata filtering, graph memory, and webhooks
+  Explore advanced features like metadata filtering and webhooks
 </Card>
 
 <Card title="API Reference" icon="code" href="/api-reference/memory/add-memories">

docs/vibecoding.mdx

@@ -22,13 +22,35 @@ We follow the llms.txt standard:
 
 ## Agent Skills
 
-Teach your coding assistant how to build with Mem0:
+Mem0 ships two kinds of skills for AI coding assistants. Both work with Claude Code, Codex, Cursor, Windsurf, OpenCode, OpenClaw, and any assistant that supports the skills standard.
+
+### Reference skills — always on
+
+Teach your assistant Mem0's SDK surface so it writes correct code in everyday development:
 
 ```bash
 npx skills add https://github.com/mem0ai/mem0 --skill mem0
+npx skills add https://github.com/mem0ai/mem0 --skill mem0-cli
+npx skills add https://github.com/mem0ai/mem0 --skill mem0-vercel-ai-sdk
 ```
 
-Works with Claude Code, Cursor, Windsurf, and any assistant that supports skills. Once installed, your assistant understands Mem0's full API, framework integrations, and common patterns.
+- `mem0` — Python and TypeScript SDKs (Platform + OSS), plus framework integrations (LangChain, CrewAI, OpenAI Agents, LangGraph, LlamaIndex, etc.)
+- `mem0-cli` — terminal workflows for the `mem0` CLI (both Node and Python builds)
+- `mem0-vercel-ai-sdk` — `@mem0/vercel-ai-provider` and `createMem0`
+
+### Pipeline skills — run on demand
+
+Let your assistant execute an end-to-end workflow in an existing repo. Invoked as slash commands:
+
+```bash
+npx skills add https://github.com/mem0ai/mem0 --skill mem0-integrate
+npx skills add https://github.com/mem0ai/mem0 --skill mem0-test-integration
+```
+
+- `/mem0-integrate` — wire Mem0 into an existing repository using a goal-driven, test-first pipeline. Detects the stack, asks whether to use Platform or OSS, writes failing tests first, and keeps the integration additive and feature-flagged.
+- `/mem0-test-integration` — verify what `/mem0-integrate` produced. Runs the repo's native test suite and a real end-to-end smoke flow against your API key, then produces a scorecard.
+
+See the [skills index](https://github.com/mem0ai/mem0/tree/main/skills) for the full catalog.
 
 ## MCP Server Setup
 
@@ -74,7 +96,7 @@ applications that gives agents persistent context across sessions.
 Mem0 is a memory layer for AI apps — managed (Mem0 Platform) or self-hosted
 (Open Source). It stores, retrieves, and manages user memories so agents
 remember preferences, learn from interactions, and personalize over time.
-Sub-50ms retrieval. Dual storage: vector embeddings + graph databases.
+Sub-50ms retrieval. Storage: vector embeddings.
 
 **Architecture Overview:**
 - Memory is scoped by user_id, agent_id, or run_id

embedchain/CITATION.cff

@@ -1,8 +0,0 @@
-cff-version: 1.2.0
-message: "If you use this software, please cite it as below."
-authors:
-- family-names: "Singh"
-  given-names: "Taranjeet"
-title: "Embedchain"
-date-released: 2023-06-20
-url: "https://github.com/embedchain/embedchain"

embedchain/CONTRIBUTING.md

@@ -1,76 +0,0 @@
-# Contributing to embedchain
-
-Let us make contribution easy, collaborative and fun.
-
-## Submit your Contribution through PR
-
-To make a contribution, follow these steps:
-
-1. Fork and clone this repository
-2. Do the changes on your fork with dedicated feature branch `feature/f1`
-3. If you modified the code (new feature or bug-fix), please add tests for it
-4. Include proper documentation / docstring and examples to run the feature
-5. Check the linting
-6. Ensure that all tests pass
-7. Submit a pull request
-
-For more details about pull requests, please read [GitHub's guides](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/creating-a-pull-request).
-
-
-### 📦 Package manager
-
-We use `poetry` as our package manager. You can install poetry by following the instructions [here](https://python-poetry.org/docs/#installation).
-
-Please DO NOT use pip or conda to install the dependencies. Instead, use poetry:
-
-```bash
-make install_all
-
-#activate
-
-poetry shell
-```
-
-### 📌 Pre-commit
-
-To ensure our standards, make sure to install pre-commit before starting to contribute.
-
-```bash
-pre-commit install
-```
-
-### 🧹 Linting
-
-We use `ruff` to lint our code. You can run the linter by running the following command:
-
-```bash
-make lint
-```
-
-Make sure that the linter does not report any errors or warnings before submitting a pull request.
-
-### Code Formatting with `black`
-
-We use `black` to reformat the code by running the following command:
-
-```bash
-make format
-```
-
-### 🧪 Testing
-
-We use `pytest` to test our code. You can run the tests by running the following command:
-
-```bash
-poetry run pytest
-```
-
-
-Several packages have been removed from Poetry to make the package lighter. Therefore, it is recommended to run `make install_all` to install the remaining packages and ensure all tests pass.
-
-
-Make sure that all tests pass before submitting a pull request.
-
-## 🚀 Release Process
-
-At the moment, the release process is manual. We try to make frequent releases. Usually, we release a new version when we have a new feature or bugfix. A developer with admin rights to the repository will create a new release on GitHub, and then publish the new version to PyPI.

embedchain/Makefile

@@ -1,56 +0,0 @@
-# Variables
-PYTHON := python3
-PIP := $(PYTHON) -m pip
-PROJECT_NAME := embedchain
-
-# Targets
-.PHONY: install format lint clean test ci_lint ci_test coverage
-
-install:
-	poetry install
-
-# TODO: use a more efficient way to install these packages
-install_all:
-	poetry install --all-extras
-	poetry run pip install ruff==0.6.9 pinecone-text pinecone-client langchain-anthropic "unstructured[local-inference, all-docs]" ollama langchain_together==0.1.3 \
-		langchain_cohere==0.1.5 deepgram-sdk==3.2.7 langchain-huggingface psutil clarifai==10.0.1 flask==2.3.3 twilio==8.5.0 fastapi-poe==0.0.16 discord==2.3.2 \
-	 	slack-sdk==3.21.3 huggingface_hub==0.23.0 gitpython==3.1.38 yt_dlp==2023.11.14 PyGithub==1.59.1 feedparser==6.0.10 newspaper3k==0.2.8 listparser==0.19 \
-	 	modal==0.56.4329 dropbox==11.36.2 boto3==1.34.20 youtube-transcript-api==0.6.1 pytube==15.0.0 beautifulsoup4==4.12.3
-
-install_es:
-	poetry install --extras elasticsearch
-
-install_opensearch:
-	poetry install --extras opensearch
-
-install_milvus:
-	poetry install --extras milvus
-
-shell:
-	poetry shell
-
-py_shell:
-	poetry run python
-
-format:
-	$(PYTHON) -m black .
-	$(PYTHON) -m isort .
-
-clean:
-	rm -rf dist build *.egg-info
-
-lint:
-	poetry run ruff .
-
-build:
-	poetry build
-
-publish:
-	poetry publish
-
-# for example: make test file=tests/test_factory.py
-test:
-	poetry run pytest $(file)
-
-coverage:
-	poetry run pytest --cov=$(PROJECT_NAME) --cov-report=xml

embedchain/README.md

@@ -1,125 +0,0 @@
-<p align="center">
-  <img src="docs/logo/dark.svg" width="400px" alt="Embedchain Logo">
-</p>
-
-<p align="center">
-  <a href="https://pypi.org/project/embedchain/">
-    <img src="https://img.shields.io/pypi/v/embedchain" alt="PyPI">
-  </a>
-  <a href="https://pepy.tech/project/embedchain">
-    <img src="https://static.pepy.tech/badge/embedchain" alt="Downloads">
-  </a>
-  <a href="https://embedchain.ai/slack">
-    <img src="https://img.shields.io/badge/slack-embedchain-brightgreen.svg?logo=slack" alt="Slack">
-  </a>
-  <a href="https://embedchain.ai/discord">
-    <img src="https://dcbadge.vercel.app/api/server/6PzXDgEjG5?style=flat" alt="Discord">
-  </a>
-  <a href="https://twitter.com/embedchain">
-    <img src="https://img.shields.io/twitter/follow/embedchain" alt="Twitter">
-  </a>
-  <a href="https://colab.research.google.com/drive/138lMWhENGeEu7Q1-6lNbNTHGLZXBBz_B?usp=sharing">
-    <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab">
-  </a>
-  <a href="https://codecov.io/gh/embedchain/embedchain">
-    <img src="https://codecov.io/gh/embedchain/embedchain/graph/badge.svg?token=EMRRHZXW1Q" alt="codecov">
-  </a>
-</p>
-
-<hr />
-
-## What is Embedchain?
-
-Embedchain is an Open Source Framework for personalizing LLM responses. It makes it easy to create and deploy personalized AI apps. At its core, Embedchain follows the design principle of being *"Conventional but Configurable"* to serve both software engineers and machine learning engineers.
-
-Embedchain streamlines the creation of personalized LLM applications, offering a seamless process for managing various types of unstructured data. It efficiently segments data into manageable chunks, generates relevant embeddings, and stores them in a vector database for optimized retrieval. With a suite of diverse APIs, it enables users to extract contextual information, find precise answers, or engage in interactive chat conversations, all tailored to their own data.
-
-## 🔧 Quick install
-
-### Python API
-
-```bash
-pip install embedchain
-```
-
-## ✨ Live demo
-
-Checkout the [Chat with PDF](https://embedchain.ai/demo/chat-pdf) live demo we created using Embedchain. You can find the source code [here](https://github.com/mem0ai/mem0/tree/main/embedchain/examples/chat-pdf).
-
-## 🔍 Usage
-
-<!-- Demo GIF or Image -->
-<p align="center">
-  <img src="docs/images/cover.gif" width="900px" alt="Embedchain Demo">
-</p>
-
-For example, you can create an Elon Musk bot using the following code:
-
-```python
-import os
-from embedchain import App
-
-# Create a bot instance
-os.environ["OPENAI_API_KEY"] = "<YOUR_API_KEY>"
-app = App()
-
-# Embed online resources
-app.add("https://en.wikipedia.org/wiki/Elon_Musk")
-app.add("https://www.forbes.com/profile/elon-musk")
-
-# Query the app
-app.query("How many companies does Elon Musk run and name those?")
-# Answer: Elon Musk currently runs several companies. As of my knowledge, he is the CEO and lead designer of SpaceX, the CEO and product architect of Tesla, Inc., the CEO and founder of Neuralink, and the CEO and founder of The Boring Company. However, please note that this information may change over time, so it's always good to verify the latest updates.
-```
-
-You can also try it in your browser with Google Colab:
-
-[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/17ON1LPonnXAtLaZEebnOktstB_1cJJmh?usp=sharing)
-
-## 📖 Documentation
-Comprehensive guides and API documentation are available to help you get the most out of Embedchain:
-
-- [Introduction](https://docs.embedchain.ai/get-started/introduction#what-is-embedchain)
-- [Getting Started](https://docs.embedchain.ai/get-started/quickstart)
-- [Examples](https://docs.embedchain.ai/examples)
-- [Supported data types](https://docs.embedchain.ai/components/data-sources/overview)
-
-## 🔗 Join the Community
-
-* Connect with fellow developers by joining our [Slack Community](https://embedchain.ai/slack) or [Discord Community](https://embedchain.ai/discord).
-
-* Dive into [GitHub Discussions](https://github.com/embedchain/embedchain/discussions), ask questions, or share your experiences.
-
-## 🤝 Schedule a 1-on-1 Session
-
-Book a [1-on-1 Session](https://cal.com/taranjeetio/ec) with the founders, to discuss any issues, provide feedback, or explore how we can improve Embedchain for you.
-
-## 🌐 Contributing
-
-Contributions are welcome! Please check out the issues on the repository, and feel free to open a pull request.
-For more information, please see the [contributing guidelines](CONTRIBUTING.md).
-
-For more reference, please go through [Development Guide](https://docs.embedchain.ai/contribution/dev) and [Documentation Guide](https://docs.embedchain.ai/contribution/docs).
-
-<a href="https://github.com/embedchain/embedchain/graphs/contributors">
-  <img src="https://contrib.rocks/image?repo=embedchain/embedchain" />
-</a>
-
-## Anonymous Telemetry
-
-We collect anonymous usage metrics to enhance our package's quality and user experience. This includes data like feature usage frequency and system info, but never personal details. The data helps us prioritize improvements and ensure compatibility. If you wish to opt-out, set the environment variable `EC_TELEMETRY=false`. We prioritize data security and don't share this data externally.
-
-## Citation
-
-If you utilize this repository, please consider citing it with:
-
-```
-@misc{embedchain,
-  author = {Taranjeet Singh, Deshraj Yadav},
-  title = {Embedchain: The Open Source RAG Framework},
-  year = {2023},
-  publisher = {GitHub},
-  journal = {GitHub repository},
-  howpublished = {\url{https://github.com/embedchain/embedchain}},
-}
-```

embedchain/configs/anthropic.yaml

@@ -1,8 +0,0 @@
-llm:
-  provider: anthropic
-  config:
-    model: 'claude-instant-1'
-    temperature: 0.5
-    max_tokens: 1000
-    top_p: 1
-    stream: false

embedchain/configs/aws_bedrock.yaml

@@ -1,15 +0,0 @@
-llm:
-  provider: aws_bedrock
-  config:
-    model: amazon.titan-text-express-v1
-    deployment_name: your_llm_deployment_name
-    temperature: 0.5
-    max_tokens: 8192
-    top_p: 1
-    stream: false
-
-embedder::
-  provider: aws_bedrock
-  config:
-    model: amazon.titan-embed-text-v2:0
-    deployment_name: you_embedding_model_deployment_name