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69 Commits

Author SHA1 Message Date
rudrajmehta-mem0 8296c06206 docs: remove deprecated Graph Memory references
Graph Memory was deprecated on April 16, 2026. This removes remaining
mentions across docs that could mislead readers into thinking it is still
a supported feature.

- Platform pages (overview, quickstart, faqs, platform-vs-oss, vibecoding):
  remove graph memory from feature lists, comparison table, and intro copy
- Platform features (platform-overview, mcp-integration,
  advanced-memory-operations): rephrase "graph-powered retrieval" to
  "advanced retrieval"; drop "Enable graph memories" tip; remove graph-edge
  verification step from the metadata example
- Core concepts (add, search, memory-types, memory-evaluation): remove
  "optional graph storage" / "graph features" / "graph writes" / "graph
  toggles"; drop "graph" from Entity Search description; remove outdated
  add/search architecture diagrams (replacement pending)
- Open source features (overview, rest-api): remove "graph relationships"
  and "graph backend(s)" from REST server config narrative
- API reference (organizations-projects): drop "graph settings" from
  Update Project Settings description
- Cookbooks: remove "Graph Memory on Neptune" card (page removed) and
  Neptune mention from AWS Bedrock card; remove "Graph Capabilities"
  bullet from Gemini cookbook; remove graph-memory conditional bullet from
  controlling-memory-ingestion
- CLI: remove --graph / --no-graph flags from mem0 add / mem0 search
  flag tables and MEM0_ENABLE_GRAPH env var
- Images: delete orphan add_architecture.png and search_architecture.png
2026-05-27 18:26:36 -07:00
Kartik 116c439b1d fix(opencode-plugin): rename package to @mem0/opencode-plugin (#5272) 2026-05-28 00:16:45 +05:30
Kartik 49b7953c44 fix(opencode-plugin): add plugin array to bundled opencode.json (#5271) 2026-05-27 23:46:05 +05:30
Kartik 3e6ab39429 feat(mem0-plugin): add OpenCode & Antigravity plugins, CC parity, docs cleanup (#5268) 2026-05-27 23:17:37 +05:30
Chaithanya Kumar 75a37ec93d feat(sdk): add delete_linked option to MemoryClient.delete (Python + TS) (#5270)
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-27 22:38:16 +05:30
youneshima 88934304c6 fix(cli-node): forward --no-infer flag to add (#5267)
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-27 10:05:30 +05:30
youneshima 098a599579 fix: refresh stale mem0ai pins in examples and openclaw (#5212)
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-26 23:08:45 +05:30
Kartik 5a2201d76b fix(pgvector): boolean filter casing, LIKE escaping, and TS scalar coercion (#5264) 2026-05-26 23:03:47 +05:30
Kartik ad736d9a06 fix(pgvector, server): add rich filter operators and fix /search 502 (#5263) 2026-05-26 22:47:41 +05:30
Kartik 7f6d46050e feat(mem0-plugin): v0.2.6 — fix memory visibility, remove redundant hooks, reduce latency (#5257) 2026-05-26 19:37:51 +05:30
Kartik f9c52baf21 feat(mem0-plugin): v0.2.5 — fix identity scoping, skill param bugs, add checklists (#5247) 2026-05-25 19:21:10 +05:30
Kartik 0da3359a1a feat(mem0-plugin): v0.2.4 — fix stats, session scoping, reduce noise, improve skill discovery (#5244) 2026-05-24 22:13:26 +05:30
Kartik 6b9707fee9 docs(mem0-plugin): add changelog entries for v0.2.1, v0.2.2, v0.2.3 (#5241) 2026-05-23 17:35:48 +05:30
Kartik 99beb007ab feat(mem0-plugin): improve auto-triggering — pre-fetch, dedup, skill enforcement v0.2.3 (#5237) 2026-05-23 17:20:54 +05:30
Kartik 16a7702d09 fix(mem0-plugin): v0.2.2 (#5234) 2026-05-22 21:47:14 +05:30
Saket Aryan 53a3998873 docs: fix capitalization in introduction hero subtitle (#5232)
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-22 20:28:01 +05:30
Saket Aryan 08aa143db3 chore: extract embedchain to mem0ai/embedchain-archive (#5230) 2026-05-22 20:02:19 +05:30
Kartik ac141fdafe chore(mem0-plugin): bump marketplace versions to v0.2.1 (#5231) 2026-05-22 19:55:21 +05:30
Kartik b1188d6044 fix(mem0-plugin): reduce memory noise, match openclaw storage pattern (#5229) 2026-05-22 19:25:59 +05:30
Kartik 0d61af60c2 feat(mem0-plugin): plugin v0.2.1 — Tiers 1-8 + PostHog telemetry + review fixes (#5215) 2026-05-22 19:01:14 +05:30
Kartik 58696e4bd4 fix(ci): remove deprecated embedchain CI and fix required check reporting (#5210)
Co-authored-by: Saket Aryan <saketaryan2002@gmail.com>
2026-05-22 12:41:55 +05:30
Harsh Vardhan Gupta 8b11e0787a fix(deps): address additional CVEs in langchain, starlette, mcp, cryptography, and lodash (#5219) 2026-05-22 01:18:41 +05:30
Harsh Vardhan Gupta 09dc74d61a fix(deps): bump vulnerable dependencies across Python and TypeScript. (#5217) 2026-05-21 23:28:35 +05:30
Kartik 606ede7c0a feat(mem0-plugin): onboarding, project scoping, identity banner (#5207) 2026-05-20 22:30:07 +05:30
Mragank Shekhar edd1b3e2f2 feat(cli): add mem0 whoami + mem0 agent-rush subcommands (#5199) 2026-05-20 19:05:12 +05:30
Prathamesh 74d043731b docs(llms.txt): lead with signup flow and CLI install (#5159)
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-19 16:25:24 -07:00
Mragank Shekhar 843ab82905 chore: trigger Mintlify redeploy for #5152 docs (#5185) 2026-05-18 16:22:48 +05:30
youneshima 79793b0d2e docs: link platform migration guide from readme (#5171) 2026-05-16 19:13:47 -07:00
Mragank Shekhar 5f7ace2aef docs: promote "Sign up as an agent" + drop plugin-sync prose (#5152) 2026-05-16 21:52:34 +05:30
rudrajmehta-mem0 219b1a6f3d docs(faqs): add self-serve account deletion FAQ (#5158)
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-16 03:16:42 +05:30
youneshima 57c8468ce6 docs: add hosted Qdrant migration script (#5156) 2026-05-16 01:46:20 +05:30
Chaithanya Kumar ddee5f8671 feat(ts): expose latestOnly on hosted memory reads (#5153) 2026-05-15 23:15:51 +05:30
Deshraj Yadav fbce5fab14 docs: remove unverified SOC2/GDPR compliance claims (#5150) 2026-05-14 23:22:37 -07:00
Mragank Shekhar 6a1597c6fb fix(plugin): drop API-key-derived user_id, restore $USER fallback (#5147) 2026-05-15 02:37:55 +05:30
Mragank Shekhar c9e8482a35 fix(docs): Mintlify <5s parse error + add Agent Mode to /platform/cli (#5145) 2026-05-14 21:49:08 +05:30
Mragank Shekhar e602923751 feat(cli): Agent Mode bootstrap + claim flow (Python + Node) (#5123) 2026-05-14 20:35:25 +05:30
Agam Pandey 70bc9e51d5 docs(readme): update LongMemEval benchmark to 94.8 and add Temporal Reasoning (#5131) 2026-05-13 14:31:15 +05:30
Agam Pandey 0107fd53b8 feat: add temporal reasoning cookbook and docs (#5061) 2026-05-13 01:59:38 +05:30
Mragank Shekhar 54a03cc721 chore(plugin): bump mem0 plugin to v0.1.2 (#5094) 2026-05-09 20:56:34 +05:30
Mragank Shekhar e95de4ca50 fix(plugin): hook cleanup + identity + compact-summary flow (#5076) 2026-05-09 19:19:30 +05:30
youneshima a623cfaf76 Oss qdrant hosted memories to platform migration (#5080) 2026-05-08 08:04:09 +05:30
Chaithanya Kumar 92491c00c2 docs(memory-decay): use SDK calls in code samples (#5079)
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-08 01:53:55 +05:30
Mragank Shekhar 9043fbf61e chore(release): bump mem0ai to 2.0.2 (py) and 3.0.3 (ts) (#5078) 2026-05-08 01:27:23 +05:30
Chaithanya Kumar c90cbc75a2 docs: memory decay v0.5 — platform feature page + API reference (#5056)
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-08 01:21:33 +05:30
Gabriel Stein 58304fc939 refactor(plugin): hand mem0 search decisions to the agent (#4992)
Co-authored-by: Mgeeeek <ms8939@bennett.edu.in>
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-07 20:41:39 +05:30
Chaithanya Kumar 397f3414ee feat(sdk): expose decay on project.update (Python + TypeScript) (#5062)
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-06 15:33:32 +05:30
Gabriel Stein a734e057cf fix (telemetry): stitch oss and platform telemetry identities for python and typescript sdk
Co-authored-by: Younes Slaoui <younes.slaoui@mem0.ai>
2026-05-05 13:48:21 -07:00
Saket Aryan 0fdaa29b4a feat(skills): add mem0-integrate + mem0-test-integration pipeline skills (#4961) 2026-05-05 18:52:22 +05:30
Kartik 6d3486ca56 docs: update changelog for v1.0.11 with new features, improvements, fixes, and dependency updates (#5022) 2026-04-29 22:45:26 +05:30
Kartik ebb9bb2b15 fix: adding skills config and updating the plugin the config (#4958) 2026-04-29 22:19:40 +05:30
Kabir Kohli 594b4e65d6 fix(openclaw): bump protobufjs to >=7.5.5 (GHSA-xq3m-2v4x-88gg) (#5012) 2026-04-29 10:43:19 +05:30
Harsh Vardhan Gupta 1b95c99db4 fix: sql injection, prompt injection (#4997)
Co-authored-by: kartik-mem0 <kartik.labhshetwar@mem0.ai>
2026-04-29 00:51:16 +05:30
Gabriel Stein b66cf0f272 docs(mcp): document list_events and get_event_status tools (#4989) 2026-04-29 00:32:48 +05:30
Gabriel Stein 72dca1cdf5 docs(codex): fix broken install instructions, lead with direct MCP (#4951) 2026-04-29 00:32:27 +05:30
Zeger Hoogeboom ece7ff6b84 (TS) Fix PGVector implementation, where vector distance was inverted. (#4944) 2026-04-28 00:39:48 +05:30
Gabriel Stein 30ce028a71 feat(mem0-plugin): add Codex lifecycle hooks via opt-in installer (#4917) 2026-04-27 22:59:35 +05:30
Kartik bd9d27ff50 docs: changelog updates, version bump in mem0-ts and pyproject (#4976) 2026-04-25 23:06:57 +05:30
Prathamesh 08b746c9be chore(readme): update cover banner image (#4966) 2026-04-25 19:17:02 +05:30
Pratik Rai 693e709389 fix(api): map entity params to filters in GET /memories (#4955) (#4960) 2026-04-24 23:52:14 +05:30
Kartik 553e275112 fix(docs): updating endpoints to v3 in the api reference (#4953) 2026-04-24 17:34:11 +05:30
Varun Chawla 43dde3b186 fix: add ca_certs config option for Elasticsearch vector store (#3993) 2026-04-24 02:46:32 +05:30
Andrew Halpern cca7551192 fix(memory): honor prompt param in vector store extraction (#4914) 2026-04-23 22:36:54 +05:30
cid 5be2630f5b fix: add missing text_lemmatized in AsyncMemory._create_memory (#4886) 2026-04-23 20:04:43 +05:30
Kartik 2549a84e5c fix: update command on docs and logic (#4946) 2026-04-23 19:42:28 +05:30
Jean Ibarz 34ed122ef3 fix(ts): forward timeout config to OpenAI client in JS OSS LLM providers (#4770)
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: Kartik <kartik.labhshetwar@mem0.ai>
2026-04-23 19:29:27 +05:30
Gabriel Stein db8ac61713 Self-hosted dashboard and admin auth (#4837)
Co-authored-by: kartik-mem0 <kartik.labhshetwar@mem0.ai>
2026-04-23 19:06:36 +05:30
Rudrasinh Nimeshkumar Ravalji 15feaa8ac4 fix(llms): narrow _is_reasoning_model to not match gpt-5.x variants (#4746)
Co-authored-by: Claude <noreply@anthropic.com>
2026-04-23 18:58:12 +05:30
Kartik 282feaebf2 fix: remove the process env from the tests and fix the plugin manifest (#4927) 2026-04-22 22:57:44 +05:30
Kartik f5dc825d47 refactor: update memory skill loader, plugin config, and add privacy docs (#4905) 2026-04-22 17:15:19 +05:30
1096 changed files with 49132 additions and 46392 deletions
+1 -1
View File
@@ -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": "0.1.0"
"version": "0.2.7"
}
]
}
+20
View File
@@ -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"
}
]
}
+1 -1
View File
@@ -12,7 +12,7 @@
"name": "mem0",
"source": "./mem0-plugin",
"description": "Mem0 memory layer for AI applications. Add persistent memory, personalization, and semantic search.",
"version": "0.1.0"
"version": "0.2.7"
}
]
}
+15 -58
View File
@@ -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: ${{ secrets.CODECOV_TOKEN }}
+6 -3
View File
@@ -4,6 +4,10 @@ __pycache__/
*$py.class
**/node_modules/
# Self-hosted server local runtime state
server/history/
server/.env
# C extensions
*.so
@@ -15,8 +19,8 @@ dist/
downloads/
eggs/
.eggs/
lib/
lib64/
/lib/
/lib64/
parts/
sdist/
var/
@@ -166,7 +170,6 @@ cython_debug/
# Database
db
test-db
!embedchain/embedchain/core/db/
.vscode
.idea/
+5 -6
View File
@@ -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 +413,6 @@ 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 |
### CD Workflows (automated publishing)
@@ -574,7 +574,6 @@ 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.
+1 -1
View File
@@ -1313,7 +1313,7 @@ async def delete_memory(memory_id: str):
- **Documentation**: https://docs.mem0.ai
- **GitHub Repository**: https://github.com/mem0ai/mem0
- **Discord Community**: https://mem0.dev/DiG
- **Platform**: https://app.mem0.ai
- **Platform**: https://app.mem0.ai?utm_source=oss&utm_medium=llm
- **Research Paper**: https://mem0.ai/research
- **Examples**: https://github.com/mem0ai/mem0/tree/main/examples
-221
View File
@@ -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!")
```
+72 -10
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@@ -39,7 +39,7 @@
</p>
<p align="center">
<a href="https://mem0.ai/research"><strong>📄 Building Production-Ready AI Agents with Scalable Long-Term Memory →</strong></a>
<a href="https://mem0.ai/research"><strong>📄 Benchmarking Mem0's token-efficient memory algorithm →</strong></a>
</p>
## New Memory Algorithm (April 2026)
@@ -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)
@@ -85,18 +86,37 @@ See the [migration guide](https://docs.mem0.ai/migration/oss-v2-to-v3) for upgra
## 🚀 Quickstart Guide <a name="quickstart"></a>
Choose between our hosted platform or self-hosted package:
### Sign up as an agent
### Hosted Platform
AI agents can mint a working Mem0 API key in under five seconds — no email, no dashboard, no OTP. Four commands end-to-end:
Get up and running in minutes with automatic updates, analytics, and enterprise security.
```bash
# 1. Install
npm install -g @mem0/cli # or: pip install mem0-cli
1. Sign up on [Mem0 Platform](https://app.mem0.ai)
2. Embed the memory layer via SDK or API keys
# 2. Sign up as an agent (replace `claude-code` with your name)
mem0 init --agent --agent-caller claude-code
### Self-Hosted (Open Source)
# 3. Add a memory
mem0 add "I am using mem0"
Install the sdk via pip:
# 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 |
| **Setup** | `pip install mem0ai` | `docker compose up` | Sign up at [app.mem0.ai](https://app.mem0.ai?utm_source=oss&utm_medium=readme) |
| **Dashboard** | -- | [Yes](https://docs.mem0.ai/open-source/setup) | Yes |
| **Auth & API Keys** | -- | Yes | Yes |
| **Advanced Features** | -- | Teasers | All included |
Just testing? Use the library. Building for a team? Self-hosted. Want zero ops? Cloud.
### Library (pip / npm)
```bash
pip install mem0ai
@@ -110,10 +130,31 @@ python -m spacy download en_core_web_sm
```
Install sdk via npm:
```bash
npm install mem0ai
```
### Self-Hosted Server
> **Note:** Self-hosted auth is on by default. Upgrading from a pre-auth build? Set `ADMIN_API_KEY`, register an admin through the wizard, or `AUTH_DISABLED=true` for local dev only. See [upgrade notes](https://docs.mem0.ai/open-source/setup#upgrade-notes).
```bash
# Recommended: one command — start the stack, create an admin, issue the first API key.
cd server && make bootstrap
# Manual: start the stack and finish setup via the browser wizard.
cd server && docker compose up -d # http://localhost:3000
```
See the [self-hosted docs](https://docs.mem0.ai/open-source/overview) for configuration.
### Cloud Platform
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
Manage memories from your terminal:
@@ -128,6 +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).
+4 -2
View File
@@ -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)." }
]
},
{
+36
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@@ -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/`.
+1 -1
View File
@@ -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": {
+32
View File
@@ -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;
}
+34 -2
View File
@@ -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(
+1 -1
View File
@@ -96,7 +96,7 @@ export function printError(message: string, hint?: string): void {
const resolvedHint =
hint ??
(message.includes("Authentication failed")
? `Run ${brand("mem0 init")} to reconfigure your API key · https://app.mem0.ai/dashboard/api-keys`
? `Run ${brand("mem0 init")} to reconfigure your API key · https://app.mem0.ai/dashboard/api-keys?utm_source=oss&utm_medium=cli-node`
: undefined);
if (resolvedHint) {
console.error(` ${dim(resolvedHint)}`);
+285
View File
@@ -0,0 +1,285 @@
/**
* Agent Mode commands — bootstrap (unattended signup) and OTP-based claim.
*/
import readline from "node:readline";
import { colors, printError, printInfo, printSuccess } from "../branding.js";
import { type Mem0Config, saveConfig } from "../config.js";
const { brand, dim } = colors;
const SOURCE_HEADERS = {
"X-Mem0-Source": "cli",
"X-Mem0-Client-Language": "node",
} as const;
export interface BootstrapEnvelope {
api_key: string;
default_user_id: string;
org_id: string;
project_id: string;
mcp_url?: string;
smoke_test_url?: string;
claim_command?: string;
mem0_notice?: string;
}
function isValidEnvelope(v: unknown): v is BootstrapEnvelope {
return (
!!v &&
typeof v === "object" &&
typeof (v as BootstrapEnvelope).api_key === "string" &&
(v as BootstrapEnvelope).api_key.length > 0 &&
typeof (v as BootstrapEnvelope).default_user_id === "string" &&
(v as BootstrapEnvelope).default_user_id.length > 0
);
}
/**
* POST /api/v1/auth/agent_mode/ and mutate config in place.
*
* @param config - Mem0Config mutated in place with the new platform values.
* @param source - `--source` flag passthrough (analytics tag, free-form).
* @param agentCaller - Self-declared agent identity passed via `--agent-caller`
* (e.g. `claude-code`, `cursor`). May be null when the caller omitted the
* flag; the agent can backfill later via `mem0 identify <name>`. Sent to the
* backend in the request body and saved into `platform.agentCaller` for
* local introspection.
*/
export async function bootstrapViaBackend(
config: Mem0Config,
{
source,
agentCaller,
}: { source?: string | null; agentCaller?: string | null } = {},
): Promise<void> {
const baseUrl = (config.platform.baseUrl || "https://api.mem0.ai").replace(
/\/+$/,
"",
);
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());
});
});
}
+147
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@@ -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}. ${m.memory ?? JSON.stringify(m)}`);
});
}
+75
View File
@@ -0,0 +1,75 @@
/**
* mem0 identify — declare which agent owns the current agent-mode key.
*
* Used when `mem0 init --agent` ran without --agent-caller, so the backend
* saved agent_caller=NULL. The agent re-runs `mem0 identify <name>` to PATCH
* its own row with its real identity. Idempotent.
*/
import { printError, printSuccess } from "../branding.js";
import { loadConfig, saveConfig } from "../config.js";
const SOURCE_HEADERS = {
"X-Mem0-Source": "cli",
"X-Mem0-Client-Language": "node",
} as const;
export async function runIdentify(name: string): Promise<void> {
const config = loadConfig();
if (!config.platform.apiKey) {
printError("No API key configured. Run `mem0 init --agent` first.");
process.exit(1);
}
if (!config.platform.agentMode) {
printError("This command only works on unclaimed agent-mode keys.");
process.exit(1);
}
const clean = (name ?? "").trim();
if (!clean) {
printError("Agent name is required.");
process.exit(1);
}
const baseUrl = (config.platform.baseUrl || "https://api.mem0.ai").replace(
/\/+$/,
"",
);
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 ${canonical}.`);
}
+169 -3
View File
@@ -21,6 +21,8 @@ import {
redactKey,
saveConfig,
} from "../config.js";
import { formatJsonEnvelope } from "../output.js";
import { isAgentMode } from "../state.js";
const { brand, dim } = colors;
@@ -33,6 +35,65 @@ function validateEmail(email: string): void {
}
}
/** @internal — exported for unit tests. */
export async function pingKey(
apiKey: string,
baseUrl: string,
timeoutMs = 5000,
): Promise<boolean> {
// Returns false ONLY on a definitive "invalid key" signal (HTTP 401/403).
// Network errors, timeouts, and 5xx responses return true so we prefer
// reusing an existing key over silently minting a new shadow on a transient
// blip (which would also clobber config + plugin-sync targets).
try {
const resp = await fetch(`${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,
@@ -185,7 +246,7 @@ function promptLine(label: string, defaultValue?: string): Promise<string> {
async function setupPlatform(config: Mem0Config): Promise<void> {
console.log();
console.log(
` ${dim("Get your API key at https://app.mem0.ai/dashboard/api-keys")}`,
` ${dim("Get your API key at https://app.mem0.ai/dashboard/api-keys?utm_source=oss&utm_medium=cli-node")}`,
);
console.log();
@@ -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> {
@@ -234,7 +296,7 @@ async function validatePlatform(config: Mem0Config): Promise<void> {
} else {
printError(
`Could not connect: ${status.error ?? "Unknown error"}`,
"Visit https://app.mem0.ai/dashboard/api-keys to get a new key, or run mem0 init again.",
"Visit https://app.mem0.ai/dashboard/api-keys?utm_source=oss&utm_medium=cli-node to get a new key, or run mem0 init again.",
);
}
} catch (e) {
@@ -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";
+2 -2
View File
@@ -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,
});
+1 -1
View File
@@ -63,7 +63,7 @@ export async function cmdStatus(
` ${dim("Run")} ${brand("mem0 init")} ${dim("to reconfigure your API key")}`,
);
lines.push(
` ${dim("Get a key at")} ${brand("https://app.mem0.ai/dashboard/api-keys")}`,
` ${dim("Get a key at")} ${brand("https://app.mem0.ai/dashboard/api-keys?utm_source=oss&utm_medium=cli-node")}`,
);
}
}
+18
View File
@@ -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");
}
+50
View File
@@ -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 {
+112 -4
View File
@@ -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();
});
+16
View File
@@ -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));
}
+120
View File
@@ -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;
}
}
+17
View File
@@ -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;
}
+4
View File
@@ -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,
+141
View File
@@ -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");
});
});
+48 -16
View File
@@ -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());
+168
View File
@@ -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);
});
});
+36
View File
@@ -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/`.
+1 -1
View File
@@ -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"
+36
View File
@@ -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
+130 -5
View File
@@ -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")
+21 -2
View File
@@ -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,
+5 -3
View File
@@ -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:
@@ -146,7 +148,7 @@ def timed_status(console: Console, message: str):
if "Authentication failed" in ctx.error_msg:
_err.print(
f" [{DIM_COLOR}]Run [bold]mem0 init[/bold] to reconfigure your API key"
f" · [bold]https://app.mem0.ai/dashboard/api-keys[/bold][/]"
f" · [bold]https://app.mem0.ai/dashboard/api-keys?utm_source=oss&utm_medium=cli-python[/bold][/]"
)
raise
else:
@@ -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()
@@ -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}")
@@ -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}.")
+160 -4
View File
@@ -19,7 +19,13 @@ from mem0_cli.branding import (
print_info,
print_success,
)
from mem0_cli.config import CONFIG_FILE, DEFAULT_BASE_URL, Mem0Config, load_config, save_config
from mem0_cli.config import (
CONFIG_FILE,
DEFAULT_BASE_URL,
Mem0Config,
load_config,
save_config,
)
console = Console()
err_console = Console(stderr=True)
@@ -97,6 +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,
@@ -176,21 +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()
@@ -236,6 +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"
)
@@ -252,6 +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():
@@ -259,7 +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"
@@ -267,6 +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)
@@ -307,6 +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"
)
@@ -325,6 +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)
@@ -352,7 +505,9 @@ def run_init(
def _setup_platform(config: Mem0Config) -> None:
"""Platform setup flow."""
console.print()
console.print(f" [{DIM_COLOR}]Get your API key at https://app.mem0.ai/dashboard/api-keys[/]")
console.print(
f" [{DIM_COLOR}]Get your API key at https://app.mem0.ai/dashboard/api-keys?utm_source=oss&utm_medium=cli-python[/]"
)
console.print()
console.print(f" [{BRAND_COLOR}]API Key[/]: ", end="")
@@ -362,6 +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:
@@ -404,7 +560,7 @@ def _validate_platform(config: Mem0Config) -> None:
print_error(
err_console,
f"Could not connect: {status.get('error', 'Unknown error')}",
hint="Visit https://app.mem0.ai/dashboard/api-keys to get a new key, then run mem0 init again.",
hint="Visit https://app.mem0.ai/dashboard/api-keys?utm_source=oss&utm_medium=cli-python to get a new key, then run mem0 init again.",
)
except Exception as e:
print_error(err_console, f"Connection test failed: {e}")
+1 -1
View File
@@ -77,7 +77,7 @@ def cmd_status(
f" [{DIM_COLOR}]Run [bold]mem0 init[/bold] to reconfigure your API key[/]"
)
lines.append(
f" [{DIM_COLOR}]Get a key at [bold]https://app.mem0.ai/dashboard/api-keys[/bold][/]"
f" [{DIM_COLOR}]Get a key at [bold]https://app.mem0.ai/dashboard/api-keys?utm_source=oss&utm_medium=cli-python[/bold][/]"
)
lines.append(f" [{DIM_COLOR}]Latency:[/] {_elapsed:.2f}s")
@@ -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")
+45
View File
@@ -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"""
+19
View File
@@ -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))
+119
View File
@@ -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
+21
View File
@@ -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
+4 -2
View File
@@ -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(),
+157
View File
@@ -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
+206
View File
@@ -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
+2 -2
View File
@@ -10,7 +10,7 @@ description: "REST APIs for memory management, search, and entity operations"
Mem0 provides a comprehensive REST API for integrating advanced memory capabilities into your applications. Create, search, update, and manage memories across users, agents, and custom entities with simple HTTP requests.
<Info>
**Quick start:** Get your API key from the <a href="https://app.mem0.ai/dashboard/api-keys" rel="nofollow">Mem0 Dashboard</a> and make your first memory operation in minutes.
**Quick start:** Get your API key from the <a href="https://app.mem0.ai/dashboard/api-keys?utm_source=oss&utm_medium=api-reference" rel="nofollow">Mem0 Dashboard</a> and make your first memory operation in minutes.
</Info>
---
@@ -87,7 +87,7 @@ All API requests require authentication using Token-based authentication. Includ
Authorization: Token <your-api-key>
```
Get your API key from the <a href="https://app.mem0.ai/dashboard/api-keys" rel="nofollow">Mem0 Dashboard</a>.
Get your API key from the <a href="https://app.mem0.ai/dashboard/api-keys?utm_source=oss&utm_medium=api-reference" rel="nofollow">Mem0 Dashboard</a>.
<Warning>
**Keep your API key secure.** Never expose it in client-side code or public repositories. Use environment variables and server-side requests only.
+2
View File
@@ -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.
+22 -20
View File
@@ -1,18 +1,18 @@
---
title: 'Add Memories'
description: "Add facts, messages, or metadata to a user memory store with support for async processing and event tracking."
openapi: post /v1/memories/
title: Add Memories
description: "Add facts, messages, or metadata to a user memory store with async processing and event tracking via the V3 additive pipeline."
openapi: post /v3/memories/add/
---
Add new facts, messages, or metadata to a user’s memory store. The Add Memories endpoint accepts either raw text or conversational turns and commits them asynchronously so the memory is ready for later search, retrieval, and graph queries.
Extract and store memories from a conversation using the V3 additive pipeline. The endpoint uses single-pass ADD-only extraction — one LLM call, no UPDATE/DELETE. Memories accumulate over time; nothing is overwritten.
## Endpoint
- **Method**: `POST`
- **URL**: `/v1/memories/`
- **URL**: `/v3/memories/add/`
- **Content-Type**: `application/json`
Memories are processed asynchronously by default. The response contains queued events you can track while the platform finalizes enrichment.
Processing is asynchronous. The response returns an `event_id` you can poll via `GET /v1/event/{event_id}/`.
## Required headers
@@ -23,7 +23,7 @@ Memories are processed asynchronously by default. The response contains queued e
## Request body
Provide at least one message or direct memory string. Most callers supply `messages` so Mem0 can infer structured memories as part of ingestion.
Provide conversation messages for Mem0 to extract memories from. At least one entity ID (`user_id`, `agent_id`, `app_id`, or `run_id`) is required so the memory is scoped to a session. Entity IDs are accepted at the top level.
<CodeGroup>
```json Basic request
@@ -43,12 +43,15 @@ Provide at least one message or direct memory string. Most callers supply `messa
| Field | Type | Required | Description |
| --- | --- | --- | --- |
| `user_id` | string | No* | Associates the memory with a user. Provide when you want the memory scoped to a specific identity. |
| `messages` | array | No* | Conversation turns for Mem0 to infer memories from. Each object should include `role` and `content`. |
| `messages` | array | Yes | Conversation turns for Mem0 to extract memories from. Each object should include `role` and `content`. |
| `user_id` | string | No* | Associates the memory with a user. |
| `agent_id` | string | No* | Associates the memory with an agent. |
| `run_id` | string | No* | Associates the memory with a run. |
| `app_id` | string | No* | Associates the memory with an app. |
| `metadata` | object | Optional | Custom key/value metadata (e.g., `{"topic": "preferences"}`). |
| `infer` | boolean (default `true`) | Optional | Set to `false` to skip inference and store the provided text as-is. |
> \* Provide at least one `messages` entry to describe what you are storing. For scoped memories, include `user_id`. You can also attach `agent_id`, `app_id`, `run_id`, `project_id`, or `org_id` to refine ownership.
> \* At least one entity ID (`user_id`, `agent_id`, `app_id`, or `run_id`) is required.
<Tip>
Need more details? See [all request parameters](#body-messages) below for complete field descriptions, types, and constraints.
@@ -56,19 +59,15 @@ Provide at least one message or direct memory string. Most callers supply `messa
## Response
Successful requests return an array of events queued for processing. Each event includes the generated memory text and an identifier you can persist for auditing.
The request is queued for background processing. The response contains an `event_id` for tracking status.
<CodeGroup>
```json 200 response
[
{
"id": "mem_01JF8ZS4Y0R0SPM13R5R6H32CJ",
"event": "ADD",
"data": {
"memory": "The user moved to Austin in 2025."
}
}
]
{
"message": "Memory processing has been queued for background execution",
"status": "PENDING",
"event_id": "evt-uuid"
}
```
```json 400 response
@@ -81,3 +80,6 @@ Successful requests return an array of events queued for processing. Each event
```
</CodeGroup>
<Info>
Poll the event status via `GET /v1/event/{event_id}/`. Status will be `SUCCEEDED` or `FAILED` once processing completes.
</Info>
+17 -6
View File
@@ -1,10 +1,12 @@
---
title: "Get Memories"
description: "Retrieve memories with advanced filtering using logical operators like AND, OR, NOT, and comparison queries."
openapi: post /v2/memories/
description: "Retrieve memories with paginated results and advanced filtering using logical operators like AND, OR, NOT, and comparison queries."
openapi: post /v3/memories/
---
The v2 get memories API is powerful and flexible, allowing for more precise memory listing without the need for a search query. It supports complex logical operations (AND, OR, NOT) and comparison operators for advanced filtering capabilities. The comparison operators include:
List memories scoped by filters with paginated results. Entity IDs (`user_id`, `agent_id`, `app_id`, `run_id`) **must** be passed inside the `filters` object — top-level entity IDs are rejected with 400.
The `filters` object supports complex logical operations (AND, OR, NOT) and comparison operators:
- `in`: Matches any of the values specified
- `gte`: Greater than or equal to
@@ -15,6 +17,8 @@ The v2 get memories API is powerful and flexible, allowing for more precise memo
- `icontains`: Case-insensitive containment check
- `*`: Wildcard character that matches everything
Pass `page` and `page_size` as query parameters to paginate through results.
<CodeGroup>
```python Code
memories = client.get_all(
@@ -27,12 +31,17 @@ memories = client.get_all(
"created_at": {"gte": "2024-07-01", "lte": "2024-07-31"}
}
]
}
},
page=1,
page_size=50
)
```
```python Output
{
"count": 2,
"next": null,
"previous": null,
"results": [
{
"id": "f4cbdb08-7062-4f3e-8eb2-9f5c80dfe64c",
@@ -46,10 +55,12 @@ memories = client.get_all(
"created_at": "2024-07-05T15:30:00Z",
"updated_at": "2024-07-05T15:30:00Z"
}
],
"total": 2
]
}
```
</CodeGroup>
<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>
+20 -8
View File
@@ -1,10 +1,14 @@
---
title: 'Search Memories'
description: "Search memories with semantic queries and advanced filtering using logical and comparison operators."
openapi: post /v2/memories/search/
description: "Search memories with hybrid retrieval (semantic + BM25 + entity matching) and advanced filtering using logical and comparison operators."
openapi: post /v3/memories/search/
---
The v2 search API is powerful and flexible, allowing for more precise memory retrieval. It supports complex logical operations (AND, OR, NOT) and comparison operators for advanced filtering capabilities. The comparison operators include:
Relevance-ranked hybrid search across stored memories. V3 uses multi-signal retrieval — semantic, BM25 keyword, and entity matching scored in parallel and fused. The returned `score` is a combined `[0, 1]` value.
Entity IDs (`user_id`, `agent_id`, `app_id`, `run_id`) **must** be passed inside the `filters` object — top-level entity IDs are rejected with 400. At least one entity ID is required.
The `filters` object supports complex logical operations (AND, OR, NOT) and comparison operators:
- `in`: Matches any of the values specified
- `gte`: Greater than or equal to
- `lte`: Less than or equal to
@@ -14,6 +18,14 @@ The v2 search API is powerful and flexible, allowing for more precise memory ret
- `icontains`: Case-insensitive containment check
- `*`: Wildcard character that matches everything
### Search parameter defaults
| Parameter | V1/V2 | V3 |
| --- | --- | --- |
| `top_k` | Supported (default 10) | Supported (1-1000, default 10) |
| `threshold` | No default | Default `0.1` (pass `0.0` to disable) |
| `rerank` | Default `true` | Default `false` (pass `true` to enable) |
<CodeGroup>
```python Platform API Example
related_memories = client.search(
@@ -33,20 +45,20 @@ related_memories = client.search(
```json Output
{
"memories": [
"results": [
{
"id": "ea925981-272f-40dd-b576-be64e4871429",
"memory": "Likes to play cricket and plays cricket on weekends.",
"user_id": "alice",
"metadata": {
"category": "hobbies"
},
"score": 0.32116443111457704,
"score": 0.82,
"created_at": "2024-07-26T10:29:36.630547-07:00",
"updated_at": null,
"user_id": "alice",
"agent_id": "sports-agent"
"categories": ["hobbies"]
}
],
]
}
```
</CodeGroup>
+14 -1
View File
@@ -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>
+29 -1
View File
@@ -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>
+91
View File
@@ -4,6 +4,97 @@ 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:**
- Telemetry `distinct_id` now uses SHA-256 instead of MD5 — prevents rainbow-table reversal of API key hashes
- User email is now SHA-256 hashed before sending as `distinct_id` — no PII in telemetry payloads
- Declared PostHog telemetry endpoint (`us.i.posthog.com`) in `providerEndpoints`
**Fixes:**
- Fixed version-pinned install records preventing plugin updates. `ensureInstallRecord()` now detects semver-pinned specs (e.g. `@mem0/openclaw-mem0@1.0.7`) and rewrites them to `@latest` or `clawhub:` prefix so `openclaw plugins update` resolves to the newest release
- Fixed `searchThreshold` default inconsistency: standardized to `0.3` across docs, README, and manifest
- `PLUGIN_VERSION` now injected at build time via tsup `define` from `package.json` — no more hardcoded version strings
**Manifest Compliance:**
- Removed non-spec fields: `requiredEnvVars`, `dataLocations`, `privacy`, `setup` (with `externalEndpoints`, `providers`, `requiresRuntime`, `postInstallHint`)
- Replaced `setup.externalEndpoints` with spec-compliant `providerEndpoints` using `endpointClass` + `hosts` format
- Env var declarations now rely solely on `providerAuthEnvVars` (already spec-compliant)
**Docs:**
- Fixed `openclaw plugins update` command: uses plugin ID (`openclaw-mem0`), not npm package name (`@mem0/openclaw-mem0`)
- Added update section to README
- Removed redundant "Key Features" and "Conclusion" sections from integration docs
</Update>
<Update label="2026-04-22" description="v1.0.9">
**Security & Compliance:**
- Added top-level `requiredEnvVars` to plugin manifest, declaring env vars per mode (platform, OSS OpenAI, OSS Anthropic, OSS Ollama). Fixes ClaHub scanner "required env vars: none" mismatch
- Added `sensitive: true` and descriptions to `apiKey` and `userEmail` in `configSchema` — previously only declared in `uiHints`
- Added `default: false` with descriptions to `autoCapture` and `autoRecall` in `configSchema` so scanner can confirm opt-in defaults
- Added `dataLocations` field to manifest declaring all persistence paths (config, vectorStore, historyDb, dreamState)
- Added `privacy` field to manifest documenting data flow for platform vs open-source mode and credential storage guidance
- Added `externalEndpoints` to `setup` section declaring api.mem0.ai and app.mem0.ai with purpose and requirement context
**Tests:**
- Replaced direct `process.env` access in `tests/cli-commands.test.ts` and `tests/fs-safe.test.ts` with `vi.stubEnv`/`vi.unstubAllEnvs`. Fixes ClaHub static analysis flag for "environment variable access combined with network send"
- 421 tests across 15 test files
</Update>
<Update label="2026-04-21" description="v1.0.8">
**New Features:**
- **OSS Onboarding Wizard:** New guided 4-step interactive setup for open-source mode — walks through LLM provider, embedding provider, vector store, and user ID selection with prefilled defaults
- **Agent-Friendly CLI:** Added `--json` flag to all 16 CLI commands for machine-readable output. Agents can call `openclaw mem0 help --json` to discover every command and flag
- **Non-Interactive OSS Setup:** Added `--mode open-source` with `--oss-llm`, `--oss-embedder`, `--oss-vector` flags for fully automated OSS configuration without prompts
- **JSON Helpers Module:** New `cli/json-helpers.ts` with `jsonOut`, `jsonErr`, and `redactSecrets` utilities for consistent structured output
**Improvements:**
- **Init Flow Redesigned:** Replaced 3-option flat menu with 2-level structure: Platform (email login or API key) and Open Source (guided wizard)
- **Provider Selection:** LLM providers: OpenAI, Ollama, Anthropic. Embedding providers: OpenAI, Ollama. Vector stores: Qdrant, PGVector
- **Input Prefill:** All prompts with defaults (base URL, user ID) now prefill the input field instead of showing defaults in brackets
- **Smart Reuse:** When LLM and embedder use the same provider, API key and base URL are automatically reused from the LLM step
- **Default Model:** Updated default LLM model to `gpt-5-mini`
- **Manifest Compliance:** Removed undocumented fields, aligned env var declarations between SKILL.md and manifest, fixed `configSchema.required` for clean installs
**Tests:**
- 404 tests across 15 test files (+3 new: `json-helpers.test.ts`, `oss-wizard.test.ts`, `cli-commands.test.ts`)
</Update>
<Update label="2026-04-20" description="v1.0.7">
**New Features:**
+18 -1
View File
@@ -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>
+108 -1
View File
@@ -7,6 +7,52 @@ 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:**
- **Client:** Map `user_id`, `agent_id`, `run_id` entity params to filters in `GET /memories` ([#4960](https://github.com/mem0ai/mem0/pull/4960))
- **Memory:** Honor `prompt` param in vector store extraction pipeline ([#4914](https://github.com/mem0ai/mem0/pull/4914))
- **Memory:** Add missing `text_lemmatized` field in `AsyncMemory._create_memory` ([#4886](https://github.com/mem0ai/mem0/pull/4886))
- **Memory:** Merge same-key operator dicts in AND metadata filters ([#4853](https://github.com/mem0ai/mem0/pull/4853))
- **LLMs:** Narrow `_is_reasoning_model` check to not match `gpt-5.x` variants ([#4746](https://github.com/mem0ai/mem0/pull/4746))
- **Vector Stores:** Add `ca_certs` config option for Elasticsearch vector store ([#3993](https://github.com/mem0ai/mem0/pull/3993))
- **Vector Stores:** Add `agent_id` and `run_id` to Elasticsearch/OpenSearch default mappings ([#4906](https://github.com/mem0ai/mem0/pull/4906))
- **Embeddings:** Set FastEmbed `embedding_dims` from model metadata at init ([#4711](https://github.com/mem0ai/mem0/pull/4711))
**Security:**
- Bump vulnerable dependencies to patched versions ([#4835](https://github.com/mem0ai/mem0/pull/4835))
</Update>
<Update label="2026-04-14" description="v2.0.0">
**Major Release** — Python SDK with V3 memory pipeline, ADD-only extraction, and cleaned-up API surface.
@@ -24,7 +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))
@@ -893,6 +939,43 @@ 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:**
- **LLMs:** Forward `timeout` config to OpenAI client in JS OSS LLM providers ([#4770](https://github.com/mem0ai/mem0/pull/4770))
**Improvements:**
- **Telemetry:** Harden TS telemetry version injection and require changelog entry on version bump ([#4900](https://github.com/mem0ai/mem0/pull/4900))
- **Docs:** Update memory tool list, CLI usage, and config file reading logic ([#4861](https://github.com/mem0ai/mem0/pull/4861))
</Update>
<Update label="2026-04-20" description="v3.0.1">
**Bug Fixes:**
@@ -1269,6 +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:**
@@ -45,7 +45,7 @@ Before you begin, follow these steps to set up the demo application:
OPENAI_API_KEY=your_openai_api_key
MEM0_API_KEY=your_mem0_api_key
```
You can obtain your `MEM0_API_KEY` by signing up at <a href="https://app.mem0.ai/dashboard/api-keys" rel="nofollow">Mem0 API Dashboard</a>.
You can obtain your `MEM0_API_KEY` by signing up at <a href="https://app.mem0.ai/dashboard/api-keys?utm_source=oss&utm_medium=cookbook-companions-quickstart" rel="nofollow">Mem0 API Dashboard</a>.
5. Start the development server:
```bash
@@ -38,7 +38,7 @@ client = MemoryClient(api_key="your-api-key")
```
<Note>
Replace `your-api-key` with your actual Mem0 API key from the <a href="https://app.mem0.ai" rel="nofollow">dashboard</a>. Without proper API authentication, memory operations will fail.
Replace `your-api-key` with your actual Mem0 API key from the <a href="https://app.mem0.ai?utm_source=oss&utm_medium=cookbook-memory-ingestion" rel="nofollow">dashboard</a>. Without proper API authentication, memory operations will fail.
</Note>
---
@@ -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 |
@@ -17,7 +17,7 @@ from mem0 import MemoryClient
client = MemoryClient(api_key="m0-...")
```
Grab an API key from the <a href="https://app.mem0.ai/" rel="nofollow">Mem0 dashboard</a> to get started.
Grab an API key from the <a href="https://app.mem0.ai/?utm_source=oss&utm_medium=cookbook-entity-partitioning" rel="nofollow">Mem0 dashboard</a> to get started.
## Store and Retrieve Scoped Memories
@@ -20,7 +20,7 @@ client = MemoryClient(api_key="your-api-key")
```
<Note>
Your API key needs export permissions to download memory data. Check your project settings on the <a href="https://app.mem0.ai" rel="nofollow">dashboard</a> if export operations fail with authentication errors.
Your API key needs export permissions to download memory data. Check your project settings on the <a href="https://app.mem0.ai?utm_source=oss&utm_medium=cookbook-exporting-memories" rel="nofollow">dashboard</a> if export operations fail with authentication errors.
</Note>
Let's add some sample memories to work with:
@@ -42,7 +42,7 @@ Create a `.env` file in the root of the project and add the following (you can u
```bash
# Mem0 Configuration
MEM0_API_KEY= # Mem0 API Key (get from https://app.mem0.ai/dashboard/api-keys)
MEM0_API_KEY= # Mem0 API Key (get from https://app.mem0.ai/dashboard/api-keys?utm_source=oss&utm_medium=cookbook-eliza-os)
MEM0_USER_ID= # Default: eliza-os-user
MEM0_PROVIDER= # Default: openai
MEM0_PROVIDER_API_KEY= # API Key for the provider (OpenAI, Anthropic, etc.)
@@ -55,7 +55,7 @@ GEMINI_API_KEY=your-gemini-api-key-here
```
<Note>
Ensure you have your Mem0 API key from the <a href="https://app.mem0.ai" rel="nofollow">Mem0 Dashboard</a> and your Gemini API key from the [Google AI Studio](https://ai.studio/app/api-keys).
Ensure you have your Mem0 API key from the <a href="https://app.mem0.ai?utm_source=oss&utm_medium=cookbook-gemini-3" rel="nofollow">Mem0 Dashboard</a> and your Gemini API key from the [Google AI Studio](https://ai.studio/app/api-keys).
</Note>
## Gemini Memory Agent
@@ -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
@@ -41,7 +41,7 @@ Set up your environment variables:
- `MEM0_API_KEY`: Your Mem0 Platform API key
- `OPENAI_API_KEY`: Your OpenAI API key
You can obtain your Mem0 Platform API key from the <a href="https://app.mem0.ai" rel="nofollow">Mem0 Platform</a>.
You can obtain your Mem0 Platform API key from the <a href="https://app.mem0.ai?utm_source=oss&utm_medium=cookbook-llamaindex-multiagent" rel="nofollow">Mem0 Platform</a>.
## Complete Implementation
@@ -357,7 +357,7 @@ Based on our previous session, I remember we covered Vision Language Models and
## Help & Resources
- [LlamaIndex Agent Workflows](https://docs.llamaindex.ai/en/stable/use_cases/agents/)
- <a href="https://app.mem0.ai/" rel="nofollow">Mem0 Platform</a>
- <a href="https://app.mem0.ai/?utm_source=oss&utm_medium=cookbook-llamaindex-multiagent" rel="nofollow">Mem0 Platform</a>
---
@@ -25,7 +25,7 @@ os.environ["OPENAI_API_KEY"] = "<your-openai-api-key>"
llm = OpenAI(model="gpt-5-mini")
```
Initialize the Mem0 client. You can find your API key <a href="https://app.mem0.ai/dashboard/api-keys" rel="nofollow">here</a>. Read about Mem0 [Open Source](https://docs.mem0.ai/open-source/overview).
Initialize the Mem0 client. You can find your API key <a href="https://app.mem0.ai/dashboard/api-keys?utm_source=oss&utm_medium=cookbook-llamaindex-react" rel="nofollow">here</a>. Read about Mem0 [Open Source](https://docs.mem0.ai/open-source/overview).
```python
os.environ["MEM0_API_KEY"] = "<your-mem0-api-key>"
@@ -223,7 +223,7 @@ context = Mem0Context(user_id="user123")
## Resources
- [Mem0 Documentation](https://docs.mem0.ai/introduction)
- <a href="https://app.mem0.ai/dashboard" rel="nofollow">Mem0 Dashboard</a>
- <a href="https://app.mem0.ai/dashboard?utm_source=oss&utm_medium=cookbook-agents-sdk-tool" rel="nofollow">Mem0 Dashboard</a>
- [API Reference](https://docs.mem0.ai/api-reference)
---
@@ -23,7 +23,7 @@ MEM0_API_KEY=your_mem0_api_key
OPENAI_API_KEY=your_openai_api_key
```
Get your Mem0 API key from the <a href="https://app.mem0.ai/dashboard/api-keys" rel="nofollow">Mem0 Dashboard</a>.
Get your Mem0 API key from the <a href="https://app.mem0.ai/dashboard/api-keys?utm_source=oss&utm_medium=cookbook-openai-tool-calls" rel="nofollow">Mem0 Dashboard</a>.
### Configuration
@@ -303,7 +303,7 @@ run().catch(console.error);
## Resources
- [Mem0 Documentation](https://docs.mem0.ai/introduction)
- <a href="https://app.mem0.ai/dashboard" rel="nofollow">Mem0 Dashboard</a>
- <a href="https://app.mem0.ai/dashboard?utm_source=oss&utm_medium=cookbook-openai-tool-calls" rel="nofollow">Mem0 Dashboard</a>
- [API Reference](https://docs.mem0.ai/api-reference)
- [OpenAI Documentation](https://platform.openai.com/docs)
+1 -8
View File
@@ -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>
+1 -1
View File
@@ -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:
+3 -7
View File
@@ -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
@@ -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>
+1 -1
View File
@@ -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
+12 -6
View File
@@ -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"
]
},
{
@@ -153,6 +156,7 @@
"icon": "rocket",
"pages": [
"open-source/overview",
"open-source/setup",
"vibecoding",
"open-source/python-quickstart",
"open-source/node-quickstart"
@@ -448,7 +452,9 @@
"pages": [
"integrations/claude-code",
"integrations/cursor",
"integrations/codex"
"integrations/codex",
"integrations/opencode",
"integrations/antigravity"
]
},
{
@@ -578,7 +584,7 @@
"primary": {
"type": "button",
"label": "Your Dashboard",
"href": "https://app.mem0.ai"
"href": "https://app.mem0.ai?utm_source=oss&utm_medium=docs-nav"
}
},
"footer": {
@@ -608,7 +614,7 @@
"title": "Try in Playground",
"description": "Open this example in the interactive Mem0 playground",
"icon": "play",
"href": "https://app.mem0.ai/playground"
"href": "https://app.mem0.ai/playground?utm_source=oss&utm_medium=docs-nav"
}
]
},
@@ -1142,4 +1148,4 @@
"destination": "/introduction"
}
]
}
}
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+1 -1
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@@ -24,7 +24,7 @@ pip install mem0ai agentops python-dotenv
2. Valid API keys:
- [AgentOps API Key](https://app.agentops.ai/dashboard/api-keys)
- OpenAI API Key (for LLM operations)
- <a href="https://app.mem0.ai/dashboard/api-keys" rel="nofollow">Mem0 API Key</a> (optional, for cloud operations)
- <a href="https://app.mem0.ai/dashboard/api-keys?utm_source=oss&utm_medium=integration-agentops" rel="nofollow">Mem0 API Key</a> (optional, for cloud operations)
## Basic Integration Example
+1 -1
View File
@@ -23,7 +23,7 @@ pip install agno mem0ai python-dotenv
```
2. Valid API keys:
- <a href="https://app.mem0.ai/dashboard/api-keys" rel="nofollow">Mem0 API Key</a>
- <a href="https://app.mem0.ai/dashboard/api-keys?utm_source=oss&utm_medium=integration-agno" rel="nofollow">Mem0 API Key</a>
- OpenAI API Key (for the agent model)
## Quick Integration (Using `Mem0Tools`)
+105
View File
@@ -0,0 +1,105 @@
---
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** (one command, no clone needed):
```bash
npx degit mem0ai/mem0/mem0-plugin/.antigravity ~/.gemini/config/plugins/mem0
```
**Option B — agy CLI** (if you have the repo cloned):
```bash
agy plugin install /path/to/mem0/mem0-plugin/.antigravity
```
**Option C — MCP only** (no hooks or skills):
Create `~/.gemini/config/plugins/mem0/plugin.json`:
```json
{
"name": "mem0",
"mcpServers": {
"mem0": {
"serverUrl": "https://mcp.mem0.ai/mcp/",
"headers": { "Authorization": "Token ${MEM0_API_KEY}" }
}
}
}
```
Restart Antigravity. The full plugin auto-registers the MCP server, lifecycle hooks, scripts, and all `/mem0:` skills. It reads `MEM0_API_KEY` from your environment automatically — no extra config needed.
## What's Included
| Component | Full Plugin (A/B) | MCP Only (C) |
|-----------|:-----------------:|:------------:|
| MCP Server (9 memory tools) | Yes | Yes |
| Lifecycle Hooks | Yes | No |
| 16 Slash Commands | Yes | No |
## Available MCP Tools
| Tool | Description |
|------|-------------|
| `add_memory` | Save text or conversation history for a user/agent |
| `search_memories` | Semantic search across memories with filters |
| `get_memories` | List memories with filters and pagination |
| `get_memory` | Retrieve a specific memory by ID |
| `update_memory` | Overwrite a memory's text by ID |
| `delete_memory` | Delete a single memory by ID |
| `delete_all_memories` | Bulk delete all memories in scope |
| `delete_entities` | Delete a user/agent/app/run entity and its memories |
| `list_entities` | List users/agents/apps/runs stored in Mem0 |
## Lifecycle Hooks
The plugin uses the same shell scripts as Claude Code, Cursor, and Codex — hooks bridge environment variables using `${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>
+2 -2
View File
@@ -19,7 +19,7 @@ pip install autogen mem0ai openai python-dotenv
First, we'll import the necessary libraries and set up our configurations.
<Note>Remember to get the Mem0 API key from <a href="https://app.mem0.ai" rel="nofollow">Mem0 Platform</a>.</Note>
<Note>Remember to get the Mem0 API key from <a href="https://app.mem0.ai?utm_source=oss&utm_medium=integration-autogen" rel="nofollow">Mem0 Platform</a>.</Note>
```python
import os
@@ -32,7 +32,7 @@ load_dotenv()
# Configuration
# OPENAI_API_KEY = 'sk-xxx' # Replace with your actual OpenAI API key
# MEM0_API_KEY = 'your-mem0-key' # Replace with your actual Mem0 API key from https://app.mem0.ai
# MEM0_API_KEY = 'your-mem0-key' # Replace with your actual Mem0 API key from https://app.mem0.ai?utm_source=oss&utm_medium=integration-autogen
USER_ID = "alice"
# Set up OpenAI API key
+5 -5
View File
@@ -18,7 +18,7 @@ In this guide, you'll:
- **Python 3.12+**
- **[uv](https://docs.astral.sh/uv/)** — Python package manager
- **Node.js 18+** and **npm** — only needed if using the web console
- A **Mem0 API key** from <a href="https://app.mem0.ai" rel="nofollow">app.mem0.ai</a>
- A **Mem0 API key** from <a href="https://app.mem0.ai?utm_source=oss&utm_medium=integration-chatdev" rel="nofollow">app.mem0.ai</a>
- An **OpenAI API key** (or another LLM provider supported by ChatDev)
## Setup and Configuration
@@ -39,7 +39,7 @@ cd frontend && npm install && cd ..
Set up your environment variables in a `.env` file:
<Note>Get your Mem0 API key from <a href="https://app.mem0.ai" rel="nofollow">Mem0 Platform</a>.</Note>
<Note>Get your Mem0 API key from <a href="https://app.mem0.ai?utm_source=oss&utm_medium=integration-chatdev" rel="nofollow">Mem0 Platform</a>.</Note>
```bash
MEM0_API_KEY=your-mem0-api-key
@@ -194,7 +194,7 @@ This means retrieval returns memories from **both** the user's scope and the age
| Field | Required | Description |
|-------|----------|-------------|
| `api_key` | Yes | Mem0 API key from <a href="https://app.mem0.ai" rel="nofollow">app.mem0.ai</a> |
| `api_key` | Yes | Mem0 API key from <a href="https://app.mem0.ai?utm_source=oss&utm_medium=integration-chatdev" rel="nofollow">app.mem0.ai</a> |
| `user_id` | No | Scope memories to a specific user |
| `agent_id` | No | Scope memories to a specific agent |
@@ -216,9 +216,9 @@ This means retrieval returns memories from **both** the user's scope and the age
- **No memories returned on first run** — This is expected. Memories are stored *after* the agent responds, so the first interaction has no prior context. Memories appear starting from the second interaction onward.
- **`mem0ai` not installed** — If you see `ImportError: mem0ai is required for Mem0Memory`, run `uv add mem0ai` or `pip install mem0ai` to add the dependency.
- **Invalid API key** — A wrong or expired `MEM0_API_KEY` will log errors like `Mem0 search failed` or `Mem0 add failed` but won't crash the agent. Check your key at <a href="https://app.mem0.ai" rel="nofollow">app.mem0.ai</a>.
- **Invalid API key** — A wrong or expired `MEM0_API_KEY` will log errors like `Mem0 search failed` or `Mem0 add failed` but won't crash the agent. Check your key at <a href="https://app.mem0.ai?utm_source=oss&utm_medium=integration-chatdev" rel="nofollow">app.mem0.ai</a>.
- **Pipeline headers in memories** — ChatDev automatically strips internal pipeline headers (e.g., `=== INPUT FROM TASK (user) ===`) before sending text to Mem0, so your memories stay clean.
- **Clearing test memories** — To delete memories created during testing, use the Mem0 dashboard at <a href="https://app.mem0.ai" rel="nofollow">app.mem0.ai</a> or the Python SDK: `MemoryClient().delete_all(user_id="your-test-user")`.
- **Clearing test memories** — To delete memories created during testing, use the Mem0 dashboard at <a href="https://app.mem0.ai?utm_source=oss&utm_medium=integration-chatdev" rel="nofollow">app.mem0.ai</a> or the Python SDK: `MemoryClient().delete_all(user_id="your-test-user")`.
## Key Features
+45 -27
View File
@@ -5,27 +5,35 @@ 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:
1. A Mem0 Platform account and API key:
- <a href="https://app.mem0.ai" rel="nofollow">Sign up at app.mem0.ai</a>
- <a href="https://app.mem0.ai/dashboard/api-keys" rel="nofollow">Get your API key</a> (starts with `m0-`)
- <a href="https://app.mem0.ai?utm_source=oss&utm_medium=integration-claude-code" rel="nofollow">Sign up at app.mem0.ai</a>
- <a href="https://app.mem0.ai/dashboard/api-keys?utm_source=oss&utm_medium=integration-claude-code" rel="nofollow">Get your API key</a> (starts with `m0-`)
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">
+63 -125
View File
@@ -1,111 +1,81 @@
---
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
Before setting up Mem0 with Codex, ensure you have:
1. A Mem0 Platform account and API key:
- <a href="https://app.mem0.ai" rel="nofollow">Sign up at app.mem0.ai</a>
- <a href="https://app.mem0.ai/dashboard/api-keys" rel="nofollow">Get your API key</a> (starts with `m0-`)
- <a href="https://app.mem0.ai?utm_source=oss&utm_medium=integration-codex" rel="nofollow">Sign up at app.mem0.ai</a>
- <a href="https://app.mem0.ai/dashboard/api-keys?utm_source=oss&utm_medium=integration-codex" rel="nofollow">Get your API key</a> (starts with `m0-`)
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">
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@@ -22,7 +22,7 @@ pip install crewai crewai-tools mem0ai
Import required modules and set up configurations:
<Note>Remember to get your API keys from <a href="https://app.mem0.ai" rel="nofollow">Mem0 Platform</a>, [OpenAI](https://platform.openai.com) and [Serper Dev](https://serper.dev) for search capabilities.</Note>
<Note>Remember to get your API keys from <a href="https://app.mem0.ai?utm_source=oss&utm_medium=integration-crewai" rel="nofollow">Mem0 Platform</a>, [OpenAI](https://platform.openai.com) and [Serper Dev](https://serper.dev) for search capabilities.</Note>
```python
import os
+20 -20
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@@ -5,29 +5,30 @@ 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:
1. A Mem0 Platform account and API key:
- <a href="https://app.mem0.ai" rel="nofollow">Sign up at app.mem0.ai</a>
- <a href="https://app.mem0.ai/dashboard/api-keys" rel="nofollow">Get your API key</a> (starts with `m0-`)
- <a href="https://app.mem0.ai?utm_source=oss&utm_medium=integration-cursor" rel="nofollow">Sign up at app.mem0.ai</a>
- <a href="https://app.mem0.ai/dashboard/api-keys?utm_source=oss&utm_medium=integration-cursor" rel="nofollow">Get your API key</a> (starts with `m0-`)
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
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@@ -38,7 +38,7 @@ npx flowise start
### 2. Obtain Your Mem0 API Key
1. Navigate to the <a href="https://app.mem0.ai/dashboard/api-keys" rel="nofollow">Mem0 API Key dashboard</a>.
1. Navigate to the <a href="https://app.mem0.ai/dashboard/api-keys?utm_source=oss&utm_medium=integration-flowise" rel="nofollow">Mem0 API Key dashboard</a>.
2. Generate or copy your existing Mem0 API Key.
![Mem0 API Key](https://raw.githubusercontent.com/FlowiseAI/FlowiseDocs/main/en/.gitbook/assets/mem0/api-key.png)
@@ -70,7 +70,7 @@ Test your memory configuration:
1. Save your Flowise configuration
2. Run a test chat and store some information
3. Verify the stored memories in the <a href="https://app.mem0.ai/dashboard/requests" rel="nofollow">Mem0 Dashboard</a>
3. Verify the stored memories in the <a href="https://app.mem0.ai/dashboard/requests?utm_source=oss&utm_medium=integration-flowise" rel="nofollow">Mem0 Dashboard</a>
![Flowise Test Chat](https://raw.githubusercontent.com/FlowiseAI/FlowiseDocs/main/en/.gitbook/assets/mem0/flowise-chat-1.png)
@@ -103,7 +103,7 @@ Available settings include:
### Platform Configuration
Additional settings available in <a href="https://app.mem0.ai/dashboard/project-settings" rel="nofollow">Mem0 Project Settings</a>:
Additional settings available in <a href="https://app.mem0.ai/dashboard/project-settings?utm_source=oss&utm_medium=integration-flowise" rel="nofollow">Mem0 Project Settings</a>:
1. **Custom Instructions**: Define memory extraction rules
2. **Expiration Date**: Set automatic memory cleanup periods
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@@ -22,7 +22,7 @@ pip install google-adk mem0ai python-dotenv
```
2. Valid API keys:
- <a href="https://app.mem0.ai/dashboard/api-keys" rel="nofollow">Mem0 API Key</a>
- <a href="https://app.mem0.ai/dashboard/api-keys?utm_source=oss&utm_medium=integration-google-ai-adk" rel="nofollow">Mem0 API Key</a>
- Google AI Studio API Key
## Basic Integration Example
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@@ -52,7 +52,7 @@ hermes memory setup
Select **mem0** as the provider and enter your Mem0 API key when prompted. The wizard writes your config to `~/.hermes/mem0.json`.
<Note>Get your API key from <a href="https://app.mem0.ai" rel="nofollow">app.mem0.ai</a>.</Note>
<Note>Get your API key from <a href="https://app.mem0.ai?utm_source=oss&utm_medium=integration-hermes" rel="nofollow">app.mem0.ai</a>.</Note>
### Option 2: Manual Configuration
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@@ -16,7 +16,7 @@ Combining Mem0 with Keywords AI allows you to:
4. Optimize token usage and reduce costs
<Note>
You can get your Mem0 API key from the <a href="https://app.mem0.ai/" rel="nofollow">Mem0 dashboard</a>.
You can get your Mem0 API key from the <a href="https://app.mem0.ai/?utm_source=oss&utm_medium=integration-keywords" rel="nofollow">Mem0 dashboard</a>.
</Note>
## Setup and Configuration
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@@ -22,7 +22,7 @@ pip install langchain langchain_openai mem0ai python-dotenv
Import required modules and set up configurations:
<Note>Remember to get the Mem0 API key from <a href="https://app.mem0.ai" rel="nofollow">Mem0 Platform</a>.</Note>
<Note>Remember to get the Mem0 API key from <a href="https://app.mem0.ai?utm_source=oss&utm_medium=integration-langchain" rel="nofollow">Mem0 Platform</a>.</Note>
```python
import os
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@@ -23,7 +23,7 @@ pip install langgraph langchain-openai mem0ai python-dotenv
Import required modules and set up configurations:
<Note>Remember to get the Mem0 API key from <a href="https://app.mem0.ai" rel="nofollow">Mem0 Platform</a>.</Note>
<Note>Remember to get the Mem0 API key from <a href="https://app.mem0.ai?utm_source=oss&utm_medium=integration-langgraph" rel="nofollow">Mem0 Platform</a>.</Note>
```python
from typing import Annotated, TypedDict, List
+1 -1
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@@ -22,7 +22,7 @@ pip install llama-index-core llama-index-memory-mem0 python-dotenv
Set your Mem0 Platform API key as an environment variable. You can replace `<your-mem0-api-key>` with your actual API key:
<Note type="info">
You can obtain your Mem0 Platform API key from the <a href="https://app.mem0.ai/login" rel="nofollow">Mem0 Platform</a>.
You can obtain your Mem0 Platform API key from the <a href="https://app.mem0.ai/login?utm_source=oss&utm_medium=integration-llama-index" rel="nofollow">Mem0 Platform</a>.
</Note>
```python
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@@ -23,7 +23,7 @@ npm install @mastra/core @mastra/mem0 @ai-sdk/openai zod
Set up your environment variables:
<Note>Remember to get the Mem0 API key from <a href="https://app.mem0.ai" rel="nofollow">Mem0 Platform</a>.</Note>
<Note>Remember to get the Mem0 API key from <a href="https://app.mem0.ai?utm_source=oss&utm_medium=integration-mastra" rel="nofollow">Mem0 Platform</a>.</Note>
```bash
MEM0_API_KEY=your-mem0-api-key
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@@ -22,7 +22,7 @@ pip install openai-agents mem0ai
```
2. Valid API keys:
- <a href="https://app.mem0.ai/dashboard/api-keys" rel="nofollow">Mem0 API Key</a>
- <a href="https://app.mem0.ai/dashboard/api-keys?utm_source=oss&utm_medium=integration-openai-agents-sdk" rel="nofollow">Mem0 API Key</a>
- [OpenAI API Key](https://platform.openai.com/api-keys)
## Basic Integration Example
+171 -30
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@@ -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 run silently with no manual configuration 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
@@ -114,7 +115,7 @@ That's it. No API key, no config file editing, no environment variables. The plu
</Step>
<Step title="Get your API key">
Get your API key from <a href="https://app.mem0.ai?utm_source=mem0-docs" rel="nofollow">app.mem0.ai</a>.
Get your API key from <a href="https://app.mem0.ai?utm_source=oss&utm_medium=integration-openclaw" rel="nofollow">app.mem0.ai</a>.
</Step>
<Step title="Select the plugin as your memory backend in `openclaw.json`">
@@ -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"
}
}
}
}
@@ -147,7 +160,81 @@ OpenClaw treats memory plugins as an exclusive slot. Installing the plugin alone
### Open-Source Mode (Self-hosted)
No Mem0 key needed. Requires `OPENAI_API_KEY` for default embeddings/LLM.
No Mem0 key needed. Defaults use OpenAI (`gpt-5-mini` for LLM, `text-embedding-3-small` for embeddings) — requires `OPENAI_API_KEY`. For a fully local setup, use Ollama for both.
#### Option 1: Interactive Wizard (Recommended)
Run the guided 4-step wizard:
```bash
openclaw mem0 init --mode open-source
```
The wizard walks you through:
<Steps>
<Step title="LLM provider">
Choose OpenAI (`gpt-5-mini`), Ollama (`llama3.1:8b`, fully local), or Anthropic (`claude-sonnet-4-5-20250514`). Provide an API key or base URL as needed.
</Step>
<Step title="Embedding provider">
Choose OpenAI (`text-embedding-3-small`) or Ollama (`nomic-embed-text`, local). If the same provider was chosen for LLM, the API key and URL are reused automatically.
</Step>
<Step title="Vector store">
Choose Qdrant (`http://localhost:6333`) or PGVector (PostgreSQL). Connectivity is verified before proceeding.
</Step>
<Step title="User ID">
Set your memory namespace identifier.
</Step>
</Steps>
#### Option 2: Non-Interactive Setup
For CI/CD, scripts, or agent-driven setup — pass all options as flags:
```bash
# Fully local with Ollama + Qdrant
openclaw mem0 init --mode open-source \
--oss-llm ollama --oss-embedder ollama --oss-vector qdrant
# OpenAI + Qdrant
openclaw mem0 init --mode open-source \
--oss-llm openai --oss-llm-key <key> \
--oss-embedder openai --oss-embedder-key <key> \
--oss-vector qdrant
# Anthropic LLM + OpenAI embeddings + PGVector
openclaw mem0 init --mode open-source \
--oss-llm anthropic --oss-llm-key <key> \
--oss-embedder openai --oss-embedder-key <key> \
--oss-vector pgvector --oss-vector-user postgres --oss-vector-password secret
```
Add `--json` for machine-readable output (useful when an LLM agent is driving the setup).
<Accordion title="All --oss-* flags">
| Flag | Description |
|------|-------------|
| `--oss-llm <provider>` | `openai`, `ollama`, or `anthropic` |
| `--oss-llm-key <key>` | API key for LLM provider |
| `--oss-llm-model <model>` | Override default LLM model |
| `--oss-llm-url <url>` | Base URL (Ollama only) |
| `--oss-embedder <provider>` | `openai` or `ollama` |
| `--oss-embedder-key <key>` | API key for embedder |
| `--oss-embedder-model <model>` | Override default embedder model |
| `--oss-embedder-url <url>` | Base URL (Ollama only) |
| `--oss-vector <provider>` | `qdrant` or `pgvector` |
| `--oss-vector-url <url>` | Qdrant server URL (default: `http://localhost:6333`) |
| `--oss-vector-host <host>` | PGVector host |
| `--oss-vector-port <port>` | PGVector port |
| `--oss-vector-user <user>` | PGVector user |
| `--oss-vector-password <pw>` | PGVector password |
| `--oss-vector-dbname <db>` | PGVector database name |
| `--oss-vector-dims <n>` | Override embedding dimensions |
</Accordion>
#### Option 3: Manual Config
Minimal config — uses OpenAI defaults:
```json5
{
@@ -168,7 +255,7 @@ No Mem0 key needed. Requires `OPENAI_API_KEY` for default embeddings/LLM.
}
```
Sensible defaults work out of the box. To customize the embedder, vector store, or LLM:
To customize providers:
```json5
{
@@ -184,8 +271,8 @@ Sensible defaults work out of the box. To customize the embedder, vector store,
"userId": "your-user-id",
"oss": {
"embedder": { "provider": "openai", "config": { "model": "text-embedding-3-small" } },
"vectorStore": { "provider": "qdrant", "config": { "host": "localhost", "port": 6333 } },
"llm": { "provider": "openai", "config": { "model": "gpt-4o" } }
"vectorStore": { "provider": "qdrant", "config": { "url": "http://localhost:6333" } },
"llm": { "provider": "openai", "config": { "model": "gpt-5-mini" } }
}
}
}
@@ -225,6 +312,8 @@ The `memory_search` and `memory_list` tools accept a `scope` parameter (`"sessio
## CLI Commands
All commands support `--json` for machine-readable output — useful when an LLM agent drives the CLI programmatically. Run `openclaw mem0 help --json` to discover every command and flag.
```bash
# Search all memories (long-term + session)
openclaw mem0 search "what languages does the user know"
@@ -238,6 +327,10 @@ openclaw mem0 search "what languages does the user know" --scope session
# List all memories
openclaw mem0 list
openclaw mem0 list --user-id alice --top-k 20
# JSON output (any command)
openclaw mem0 search "preferences" --json
openclaw mem0 status --json
```
## Configuration Options
@@ -248,8 +341,8 @@ openclaw mem0 list --user-id alice --top-k 20
|-----|------|---------|-------------|
| `mode` | `"platform"` \| `"open-source"` | `"platform"` | Which backend to use |
| `userId` | `string` | OS username | Scope memories per user |
| `autoRecall` | `boolean` | `true` | Inject memories before each turn |
| `autoCapture` | `boolean` | `true` | Store facts after each turn |
| `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) |
@@ -275,18 +368,16 @@ openclaw mem0 list --user-id alice --top-k 20
| `oss.historyDbPath` | `string` | — | SQLite path for memory edit history |
| `oss.disableHistory` | `boolean` | `false` | Disable memory edit history tracking |
Everything inside `oss` is optional — defaults use OpenAI embeddings (`text-embedding-3-small`), in-memory vector store, and OpenAI LLM.
Everything inside `oss` is optional — defaults use OpenAI embeddings (`text-embedding-3-small`), in-memory vector store, and OpenAI LLM (`gpt-5-mini`).
## Plugin Management
### Updating the Plugin
```bash
openclaw plugins update @mem0/openclaw-mem0
openclaw plugins update openclaw-mem0
```
<Note>Use the npm package name (`@mem0/openclaw-mem0`) for plugin management commands, not the plugin ID (`openclaw-mem0`).</Note>
### Checking Plugin Status
```bash
@@ -331,23 +422,73 @@ If the plugin installs but doesn't work:
If `openclaw plugins update` fails:
1. Use the full npm package name: `openclaw plugins update @mem0/openclaw-mem0`
2. If that fails, uninstall and reinstall:
1. Use the plugin ID: `openclaw plugins update openclaw-mem0`
2. Update all plugins at once: `openclaw plugins update --all`
3. If that fails, uninstall and reinstall:
```bash
openclaw plugins uninstall openclaw-mem0
openclaw plugins install @mem0/openclaw-mem0
```
## Key Features
## Privacy & Security
1. **Zero Configuration** — Auto-recall and auto-capture work out of the box with no prompting required
2. **Dual Memory Scopes** — Session-scoped short-term and user-scoped long-term memories
3. **Flexible Backend** — Use Mem0 Cloud for managed service or self-host with open-source mode
4. **Rich Tool Suite** — Eight agent tools for explicit memory operations when needed
### Data Flow
## Conclusion
| Mode | Where data goes | Storage |
|------|----------------|---------|
| **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) |
The `@mem0/openclaw-mem0` plugin gives OpenClaw agents persistent memory with minimal setup. Whether using Mem0 Cloud or self-hosting, your agents can now remember user preferences, facts, and context across sessions automatically.
### Auto-Capture and Auto-Recall
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
{
"plugins": {
"entries": {
"openclaw-mem0": {
"config": {
"autoCapture": false, // disable automatic fact extraction
"autoRecall": false // disable automatic memory injection
}
}
}
}
}
```
The agent can always use memory tools (`memory_add`, `memory_search`, etc.) explicitly regardless of these settings.
### Credential Protection
The plugin never stores API keys, tokens, or secrets as memories. Five independent layers enforce this:
1. **Triage gate** — The extraction prompt rejects values matching known credential patterns (`sk-`, `m0-`, `ghp_`, `AKIA`, `Bearer`, `password=`, `token=`, `secret=`)
2. **Dream cleanup** — Periodic memory consolidation deletes any memories that slipped through containing credential patterns
3. **Extraction instructions** — Default extraction rules explicitly instruct the model to store only that a credential was configured, never the value
4. **Configurable patterns** — Add custom credential patterns via `skills.triage.credentialPatterns`
5. **CLI redaction** — `openclaw mem0 config show` redacts sensitive fields (`apiKey`, `oss.*.config.apiKey`)
### API Key Storage
Plugin config is stored in `~/.openclaw/openclaw.json` with file permissions `0o600` (owner-read-only). For production deployments, use environment variable references (`${MEM0_API_KEY}`) or SecretRef objects instead of plaintext keys.
### Telemetry
Anonymous usage telemetry (PostHog) is enabled by default to help improve the plugin. No conversation content or memory values are included — only event counts (recall, capture, tool usage, CLI commands).
To opt out, set the environment variable:
```bash
export MEM0_TELEMETRY=false
```
### System Prompt Context
The plugin injects memory-related instructions into the agent's system context via OpenClaw's `prependSystemContext` mechanism. This includes the memory triage protocol and recalled memories. This is the standard OpenClaw plugin SDK pattern for memory backends — no user-facing prompts are modified.
<CardGroup cols={2}>
<Card title="OpenAI Agents SDK" icon="robot" href="/integrations/openai-agents-sdk">
+123
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@@ -0,0 +1,123 @@
---
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
}
}
}
```
<Info icon="check">
Start a new OpenCode session and ask: *"Search my memories for hello"*. If the `mem0` tools appear and respond, you're all set.
</Info>
## 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>
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@@ -9,7 +9,7 @@ Mem0 is a self-improving memory layer for LLM applications, enabling personalize
**Get your API Key**: You'll need a Mem0 API key to use this extension:
a. Sign up at <a href="https://app.mem0.ai" rel="nofollow">app.mem0.ai</a>
a. Sign up at <a href="https://app.mem0.ai?utm_source=oss&utm_medium=integration-raycast" rel="nofollow">app.mem0.ai</a>
b. Navigate to your API Keys page

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