chore: trigger CI build_mem0 / build_embedchain on cli-only PR

- Python: 0.2.4 → 0.2.5 in cli/python/pyproject.toml
- Node:   0.2.4 → 0.2.5 in cli/node/package.json
- docs/changelog/sdk.mdx: new CLI v0.2.5 entry (Agent Mode bootstrap,
  --agent-caller, mem0 identify, plugin sync, claim flow, pingKey fix,
  rate-limit clarity, JSON envelope command field, envelope validation)
- CI fix: ruff format applied to config.py + test_init_internals.py

Release flow: merge → tag cli-v0.2.5 (Python CD) and cli-node-v0.2.5
(Node CD) on GitHub Releases. OIDC trusted publishing — no tokens needed.

.claude-plugin/marketplace.json

@@ -12,7 +12,7 @@
       "name": "mem0",
       "source": "./mem0-plugin",
       "description": "Mem0 memory layer for AI applications. Add persistent memory, personalization, and semantic search to Claude workflows.",
-      "version": "0.1.0"
+      "version": "0.1.2"
     }
   ]
 }

.cursor-plugin/marketplace.json

@@ -12,7 +12,7 @@
       "name": "mem0",
       "source": "./mem0-plugin",
       "description": "Mem0 memory layer for AI applications. Add persistent memory, personalization, and semantic search.",
-      "version": "0.1.0"
+      "version": "0.1.1"
     }
   ]
 }

.gitignore

@@ -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/

AGENTS.md

@@ -27,7 +27,7 @@ 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 |
@@ -387,7 +387,9 @@ 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
 

LLM.md

@@ -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
 

Makefile

@@ -42,9 +42,6 @@ clean:
 test:
 	hatch run test
 
-test-py-3.9:
-	hatch run dev_py_3_9:test
-
 test-py-3.10:
 	hatch run dev_py_3_10:test
 

README.md

@@ -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 +86,19 @@ 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:
+> **Agent Mode — for AI agents setting up Mem0 autonomously.** Run `mem0 init --agent --agent-caller <your-name> --json` (after `pip install mem0-cli` or `npm install -g @mem0/cli`), replacing `<your-name>` with your AI agent identity (e.g. `claude-code`, `cursor`, `codex`). This mints an evaluation Mem0 API key in <5 seconds — no email, no dashboard, no OTP. If you forgot to pass `--agent-caller`, run `mem0 identify <your-name>` after init. Use the key immediately against the Platform or the MCP server. The human owner can claim ownership later with `mem0 init --email <their-email>`: memories transfer, the same key keeps working, and the agent isn't disrupted.
 
-### Hosted Platform
+| | 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 |
 
-Get up and running in minutes with automatic updates, analytics, and enterprise security.
+Just testing? Use the library. Building for a team? Self-hosted. Want zero ops? Cloud.
 
-1. Sign up on [Mem0 Platform](https://app.mem0.ai)
-2. Embed the memory layer via SDK or API keys
-
-### Self-Hosted (Open Source)
-
-Install the sdk via pip:
+### Library (pip / npm)
 
 ```bash
 pip install mem0ai
@@ -110,10 +112,30 @@ 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
+
 ### CLI
 
 Manage memories from your terminal:
@@ -128,6 +150,27 @@ mem0 search "What does Alice prefer?" --user-id alice
 
 See the [CLI documentation](https://docs.mem0.ai/platform/cli) for the full command reference.
 
+### Agent Skills
+
+Teach your AI coding assistant (Claude Code, Codex, Cursor, Windsurf, OpenCode, OpenClaw, and any tool that supports the skills standard) how to build with Mem0. Two categories:
+
+**Reference skills — always on** (SDK knowledge loaded into the assistant's context):
+
+```bash
+npx skills add https://github.com/mem0ai/mem0 --skill mem0
+npx skills add https://github.com/mem0ai/mem0 --skill mem0-cli
+npx skills add https://github.com/mem0ai/mem0 --skill mem0-vercel-ai-sdk
+```
+
+**Pipeline skills — run on demand** (execute an end-to-end workflow in an existing repo):
+
+```bash
+npx skills add https://github.com/mem0ai/mem0 --skill mem0-integrate
+npx skills add https://github.com/mem0ai/mem0 --skill mem0-test-integration
+```
+
+Use `/mem0-integrate` to wire Mem0 into an existing repo via a test-first pipeline, then `/mem0-test-integration` to verify. See the [skills catalog](./skills/) or [Vibecoding with Mem0](https://docs.mem0.ai/vibecoding) for the full picture.
+
 ### Basic Usage
 
 Mem0 requires an LLM to function, with `gpt-5-mini` from OpenAI as the default. However, it supports a variety of LLMs; for details, refer to our [Supported LLMs documentation](https://docs.mem0.ai/components/llms/overview).

cli/cli-spec.json

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

cli/node/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@mem0/cli",
-  "version": "0.2.3",
+  "version": "0.2.5",
   "description": "The official CLI for mem0 — the memory layer for AI agents",
   "type": "module",
   "bin": {

cli/node/src/agent-detect.ts

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

cli/node/src/backend/base.ts

@@ -15,7 +15,6 @@ export interface AddOptions {
 	infer?: boolean;
 	expires?: string;
 	categories?: string[];
-	enableGraph?: boolean;
 }
 
 export interface SearchOptions {
@@ -29,7 +28,6 @@ export interface SearchOptions {
 	keyword?: boolean;
 	filters?: Record<string, unknown>;
 	fields?: string[];
-	enableGraph?: boolean;
 }
 
 export interface ListOptions {
@@ -42,7 +40,6 @@ export interface ListOptions {
 	category?: string;
 	after?: string;
 	before?: string;
-	enableGraph?: boolean;
 }
 
 export interface DeleteOptions {

cli/node/src/backend/platform.ts

@@ -3,7 +3,7 @@
  */
 
 import type { PlatformConfig } from "../config.js";
-import { isAgentMode } from "../state.js";
+import { captureNotice, isAgentMode } from "../state.js";
 import { CLI_VERSION } from "../version.js";
 import {
 	APIError,
@@ -90,7 +90,39 @@ export class PlatformBackend implements Backend {
 		if (resp.status === 204) {
 			return {};
 		}
-		return resp.json();
+
+		const data = await resp.json();
+
+		// Pull the unclaimed-Agent-Mode notice out of the body (or the header
+		// fallback for endpoints returning non-dict / non-dict-leading payloads)
+		// and stash for end-of-command surfacing.
+		let notice: string | null = null;
+		if (
+			data &&
+			typeof data === "object" &&
+			!Array.isArray(data) &&
+			"mem0_notice" in data
+		) {
+			notice = (data as Record<string, unknown>).mem0_notice as string;
+			// biome-ignore lint/performance/noDelete: intentional strip so downstream consumers don't see duplicate notice
+			delete (data as Record<string, unknown>).mem0_notice;
+		} else if (
+			Array.isArray(data) &&
+			data.length > 0 &&
+			typeof data[0] === "object" &&
+			data[0] !== null &&
+			"mem0_notice" in data[0]
+		) {
+			notice = (data[0] as Record<string, unknown>).mem0_notice as string;
+			// biome-ignore lint/performance/noDelete: see above.
+			delete (data[0] as Record<string, unknown>).mem0_notice;
+		}
+		if (!notice) {
+			notice = resp.headers.get("X-Mem0-Notice-Message") ?? null;
+		}
+		captureNotice(notice);
+
+		return data;
 	}
 
 	async add(
@@ -115,10 +147,9 @@ export class PlatformBackend implements Backend {
 		if (opts.infer === false) payload.infer = false;
 		if (opts.expires) payload.expiration_date = opts.expires;
 		if (opts.categories) payload.categories = opts.categories;
-		if (opts.enableGraph) payload.enable_graph = true;
 		payload.source = "CLI";
 
-		return (await this._request("POST", "/v1/memories/", {
+		return (await this._request("POST", "/v3/memories/add/", {
 			json: payload,
 		})) as Record<string, unknown>;
 	}
@@ -176,10 +207,9 @@ export class PlatformBackend implements Backend {
 		if (opts.rerank) payload.rerank = true;
 		if (opts.keyword) payload.keyword_search = true;
 		if (opts.fields) payload.fields = opts.fields;
-		if (opts.enableGraph) payload.enable_graph = true;
 		payload.source = "CLI";
 
-		const result = (await this._request("POST", "/v2/memories/search/", {
+		const result = (await this._request("POST", "/v3/memories/search/", {
 			json: payload,
 		})) as unknown;
 		if (Array.isArray(result)) return result;
@@ -227,10 +257,9 @@ export class PlatformBackend implements Backend {
 			extraFilters: Object.keys(extra).length > 0 ? extra : undefined,
 		});
 		if (apiFilters) payload.filters = apiFilters;
-		if (opts.enableGraph) payload.enable_graph = true;
 		payload.source = "CLI";
 
-		const result = (await this._request("POST", "/v2/memories/", {
+		const result = (await this._request("POST", "/v3/memories/", {
 			json: payload,
 			params,
 		})) as unknown;

cli/node/src/branding.ts

@@ -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)}`);

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

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

cli/node/src/commands/config.ts

@@ -29,7 +29,6 @@ export function cmdConfigShow(opts: { output?: string } = {}): void {
 					agent_id: config.defaults.agentId || null,
 					app_id: config.defaults.appId || null,
 					run_id: config.defaults.runId || null,
-					enable_graph: config.defaults.enableGraph,
 				},
 				platform: {
 					api_key: redactKey(config.platform.apiKey),
@@ -56,7 +55,6 @@ export function cmdConfigShow(opts: { output?: string } = {}): void {
 	]);
 	table.push(["defaults.app_id", config.defaults.appId || dim("(not set)")]);
 	table.push(["defaults.run_id", config.defaults.runId || dim("(not set)")]);
-	table.push(["defaults.enable_graph", String(config.defaults.enableGraph)]);
 	table.push(["", ""]);
 
 	// Platform

cli/node/src/commands/identify.ts

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

cli/node/src/commands/init.ts

@@ -21,6 +21,8 @@ import {
 	redactKey,
 	saveConfig,
 } from "../config.js";
+import { formatJsonEnvelope } from "../output.js";
+import { isAgentMode } from "../state.js";
 
 const { brand, dim } = colors;
 
@@ -33,6 +35,65 @@ function validateEmail(email: string): void {
 	}
 }
 
+/** @internal — exported for unit tests. */
+export async function pingKey(
+	apiKey: string,
+	baseUrl: string,
+	timeoutMs = 5000,
+): Promise<boolean> {
+	// Returns false ONLY on a definitive "invalid key" signal (HTTP 401/403).
+	// Network errors, timeouts, and 5xx responses return true so we prefer
+	// reusing an existing key over silently minting a new shadow on a transient
+	// blip (which would also clobber config + plugin-sync targets).
+	try {
+		const resp = await fetch(`${baseUrl.replace(/\/+$/, "")}/v1/ping/`, {
+			headers: { Authorization: `Token ${apiKey}` },
+			signal: AbortSignal.timeout(timeoutMs),
+		});
+		return resp.status !== 401 && resp.status !== 403;
+	} catch {
+		return true; // unknown — prefer reuse
+	}
+}
+
+async function maybeIdentify(
+	key: string,
+	baseUrl: string,
+	agentCaller: string | undefined,
+): Promise<void> {
+	// Best-effort PATCH agent_caller when --agent-caller is supplied on a
+	// reused key. Silent no-op on any failure — reuse must not break.
+	if (!agentCaller) return;
+	try {
+		const resp = await fetch(
+			`${baseUrl.replace(/\/+$/, "")}/api/v1/auth/agent_mode/caller/`,
+			{
+				method: "PATCH",
+				headers: {
+					Authorization: `Token ${key}`,
+					"Content-Type": "application/json",
+				},
+				body: JSON.stringify({ agent_caller: agentCaller }),
+				signal: AbortSignal.timeout(10_000),
+			},
+		);
+		if (resp.ok) {
+			try {
+				const body = (await resp.json()) as { agent_caller?: string };
+				if (fs.existsSync(CONFIG_FILE)) {
+					const cfg = loadConfig();
+					cfg.platform.agentCaller = body.agent_caller ?? agentCaller;
+					saveConfig(cfg);
+				}
+			} catch {
+				/* swallow — best effort */
+			}
+		}
+	} catch {
+		/* swallow — best effort */
+	}
+}
+
 async function emailLogin(
 	email: string,
 	code: string | undefined,
@@ -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";
 

cli/node/src/commands/memory.ts

@@ -49,7 +49,6 @@ export async function cmdAdd(
 		noInfer: boolean;
 		expires?: string;
 		categories?: string;
-		enableGraph: boolean;
 		output: string;
 	},
 ): Promise<void> {
@@ -140,7 +139,6 @@ export async function cmdAdd(
 				infer: !opts.noInfer,
 				expires: opts.expires,
 				categories: cats,
-				enableGraph: opts.enableGraph,
 			});
 		});
 	} catch (e) {
@@ -225,7 +223,6 @@ export async function cmdSearch(
 		keyword: boolean;
 		filterJson?: string;
 		fields?: string;
-		enableGraph: boolean;
 		output: string;
 	},
 ): Promise<void> {
@@ -274,7 +271,6 @@ export async function cmdSearch(
 				keyword: opts.keyword,
 				filters,
 				fields: fieldList,
-				enableGraph: opts.enableGraph,
 			});
 		});
 	} catch (e) {
@@ -368,7 +364,6 @@ export async function cmdList(
 		category?: string;
 		after?: string;
 		before?: string;
-		enableGraph: boolean;
 		output: string;
 	},
 ): Promise<void> {
@@ -396,7 +391,6 @@ export async function cmdList(
 				category: opts.category,
 				after: opts.after,
 				before: opts.before,
-				enableGraph: opts.enableGraph,
 			});
 		});
 	} catch (e) {

cli/node/src/commands/utils.ts

@@ -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")}`,
 			);
 		}
 	}

cli/node/src/config.ts

@@ -21,6 +21,12 @@ export interface PlatformConfig {
 	apiKey: string;
 	baseUrl: string;
 	userEmail: string;
+	// Agent Mode (unclaimed-shadow signup)
+	agentMode: boolean; // true while the key is an unclaimed agent-mode key
+	createdVia: string; // "agent_mode" | "email" | "api_key" | "existing_key"
+	agentCaller: string; // canonical agent name when createdVia === "agent_mode" (e.g. "claude-code")
+	claimedAt: string; // ISO timestamp once the agent has been claimed
+	defaultUserId: string; // `user_<slug>` returned by bootstrap; auto-default scope
 }
 
 export interface DefaultsConfig {
@@ -28,7 +34,6 @@ export interface DefaultsConfig {
 	agentId: string;
 	appId: string;
 	runId: string;
-	enableGraph: boolean;
 }
 
 export interface TelemetryConfig {
@@ -50,12 +55,16 @@ export function createDefaultConfig(): Mem0Config {
 			agentId: "",
 			appId: "",
 			runId: "",
-			enableGraph: false,
 		},
 		platform: {
 			apiKey: "",
 			baseUrl: DEFAULT_BASE_URL,
 			userEmail: "",
+			agentMode: false,
+			createdVia: "",
+			agentCaller: "",
+			claimedAt: "",
+			defaultUserId: "",
 		},
 		telemetry: {
 			anonymousId: "",
@@ -81,14 +90,17 @@ 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 ?? "";
 		config.defaults.agentId = defaults.agent_id ?? "";
 		config.defaults.appId = defaults.app_id ?? "";
 		config.defaults.runId = defaults.run_id ?? "";
-		config.defaults.enableGraph = defaults.enable_graph ?? false;
-
 		const telemetry = data.telemetry ?? {};
 		config.telemetry.anonymousId = telemetry.anonymous_id ?? "";
 	}
@@ -104,12 +116,6 @@ export function loadConfig(): Mem0Config {
 		config.defaults.agentId = process.env.MEM0_AGENT_ID;
 	if (process.env.MEM0_APP_ID) config.defaults.appId = process.env.MEM0_APP_ID;
 	if (process.env.MEM0_RUN_ID) config.defaults.runId = process.env.MEM0_RUN_ID;
-	if (process.env.MEM0_ENABLE_GRAPH) {
-		config.defaults.enableGraph = ["true", "1", "yes"].includes(
-			process.env.MEM0_ENABLE_GRAPH.toLowerCase(),
-		);
-	}
-
 	return config;
 }
 
@@ -123,12 +129,16 @@ export function saveConfig(config: Mem0Config): void {
 			agent_id: config.defaults.agentId,
 			app_id: config.defaults.appId,
 			run_id: config.defaults.runId,
-			enable_graph: config.defaults.enableGraph,
 		},
 		platform: {
 			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,
@@ -137,6 +147,20 @@ export function saveConfig(config: Mem0Config): void {
 
 	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 {
@@ -154,7 +178,6 @@ const KEY_MAP: Record<string, [keyof Mem0Config, string]> = {
 	"defaults.agent_id": ["defaults", "agentId"],
 	"defaults.app_id": ["defaults", "appId"],
 	"defaults.run_id": ["defaults", "runId"],
-	"defaults.enable_graph": ["defaults", "enableGraph"],
 	// Short-form aliases
 	api_key: ["platform", "apiKey"],
 	base_url: ["platform", "baseUrl"],
@@ -163,7 +186,6 @@ const KEY_MAP: Record<string, [keyof Mem0Config, string]> = {
 	agent_id: ["defaults", "agentId"],
 	app_id: ["defaults", "appId"],
 	run_id: ["defaults", "runId"],
-	enable_graph: ["defaults", "enableGraph"],
 };
 
 export function getNestedValue(config: Mem0Config, dottedKey: string): unknown {

cli/node/src/index.ts

@@ -13,7 +13,12 @@ import { colors, printError, printWarning } from "./branding.js";
 import type { Mem0Config } from "./config.js";
 import { loadConfig, saveConfig } from "./config.js";
 import { richFormatHelp } from "./help.js";
-import { setAgentMode } from "./state.js";
+import {
+	isAgentMode,
+	setAgentMode,
+	setCurrentCommand,
+	takeNotice,
+} from "./state.js";
 import { captureEvent } from "./telemetry.js";
 import { CLI_VERSION } from "./version.js";
 
@@ -134,18 +139,6 @@ function resolveIds(
 	};
 }
 
-/**
- * Resolve graph tri-state: --no-graph > --graph > config default.
- */
-function resolveGraph(
-	config: Mem0Config,
-	opts: { graph?: boolean; noGraph?: boolean },
-): boolean {
-	if (opts.noGraph) return false;
-	if (opts.graph) return true;
-	return config.defaults.enableGraph;
-}
-
 // ── Main program ──────────────────────────────────────────────────────────
 
 program
@@ -153,6 +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}`);
@@ -161,7 +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.")
@@ -178,6 +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}`,
@@ -205,11 +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,
@@ -217,9 +244,24 @@ 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);
+	});
+
 // ── Memory: add ───────────────────────────────────────────────────────────
 
 program
@@ -236,8 +278,6 @@ program
 	.option("--no-infer", "Skip inference, store raw.")
 	.option("--expires <date>", "Expiration date (YYYY-MM-DD).")
 	.option("--categories <value>", "Categories (JSON array or comma-separated).")
-	.option("--graph", "Enable graph memory extraction.", false)
-	.option("--no-graph", "Disable graph memory extraction.")
 	.option("-o, --output <format>", "Output format: text, json, quiet.", "text")
 	.option("--api-key <key>", "Override API key.")
 	.option("--base-url <url>", "Override API base URL.")
@@ -253,9 +293,8 @@ program
 			opts.baseUrl,
 		);
 		const ids = resolveIds(config, opts);
-		const enableGraph = resolveGraph(config, opts);
 		const output = isAgent ? "agent" : opts.output;
-		await cmdAdd(backend, text, { ...ids, ...opts, enableGraph, output });
+		await cmdAdd(backend, text, { ...ids, ...opts, output });
 	});
 
 // ── Memory: search ────────────────────────────────────────────────────────
@@ -285,8 +324,6 @@ program
 	.option("--keyword", "Use keyword search.", false)
 	.option("--filter <json>", "Advanced filter expression (JSON).")
 	.option("--fields <list>", "Specific fields to return (comma-separated).")
-	.option("--graph", "Enable graph in search.", false)
-	.option("--no-graph", "Disable graph in search.")
 	.option("-o, --output <format>", "Output: text, json, table.", "text")
 	.option("--api-key <key>", "Override API key.")
 	.option("--base-url <url>", "Override API base URL.")
@@ -310,7 +347,6 @@ program
 			opts.baseUrl,
 		);
 		const ids = resolveIds(config, opts);
-		const enableGraph = resolveGraph(config, opts);
 		const output = isAgent ? "agent" : opts.output;
 		await cmdSearch(backend, resolvedQuery, {
 			...ids,
@@ -320,7 +356,6 @@ program
 			keyword: opts.keyword,
 			filterJson: opts.filter,
 			fields: opts.fields,
-			enableGraph,
 			output,
 		});
 	});
@@ -364,8 +399,6 @@ program
 	.option("--category <name>", "Filter by category.")
 	.option("--after <date>", "Created after (YYYY-MM-DD).")
 	.option("--before <date>", "Created before (YYYY-MM-DD).")
-	.option("--graph", "Enable graph in listing.", false)
-	.option("--no-graph", "Disable graph in listing.")
 	.option("-o, --output <format>", "Output: text, json, table.", "table")
 	.option("--api-key <key>", "Override API key.")
 	.option("--base-url <url>", "Override API base URL.")
@@ -381,7 +414,6 @@ program
 			opts.baseUrl,
 		);
 		const ids = resolveIds(config, opts);
-		const enableGraph = resolveGraph(config, opts);
 		const output = isAgent ? "agent" : opts.output;
 		await cmdList(backend, {
 			...ids,
@@ -390,7 +422,6 @@ program
 			category: opts.category,
 			after: opts.after,
 			before: opts.before,
-			enableGraph,
 			output,
 		});
 	});
@@ -792,4 +823,16 @@ program
 
 // ── Entrypoint ────────────────────────────────────────────────────────────
 
-program.parse();
+// Surface any unclaimed Agent Mode notice once per command, after the primary
+// output. In JSON/agent mode the notice is folded into the envelope by
+// formatJsonEnvelope, so skip the stderr banner there to avoid duplication.
+function surfaceNotice(): void {
+	const notice = takeNotice();
+	if (notice && !isAgentMode()) {
+		process.stderr.write(`\n\x1b[33m🔔 ${notice}\x1b[0m\n\n`);
+	}
+}
+
+program.parseAsync().finally(() => {
+	surfaceNotice();
+});

cli/node/src/output.ts

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

cli/node/src/plugin-sync.ts

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

cli/node/src/state.ts

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

cli/node/src/telemetry.ts

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

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

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

cli/node/tests/cli-integration.test.ts

@@ -107,22 +107,22 @@ describe("CLI Integration — help and version", () => {
     expect(result.exitCode).toBe(0);
   });
 
-  it("add help has --graph flag", () => {
+  it("add help has --output flag", () => {
     const result = run(["add", "--help"]);
     expect(result.exitCode).toBe(0);
-    expect(result.stdout).toContain("--graph");
+    expect(result.stdout).toContain("--output");
   });
 
-  it("search help has --graph flag", () => {
+  it("search help has --rerank flag", () => {
     const result = run(["search", "--help"]);
     expect(result.exitCode).toBe(0);
-    expect(result.stdout).toContain("--graph");
+    expect(result.stdout).toContain("--rerank");
   });
 
-  it("list help has --graph flag", () => {
+  it("list help has --category flag", () => {
     const result = run(["list", "--help"]);
     expect(result.exitCode).toBe(0);
-    expect(result.stdout).toContain("--graph");
+    expect(result.stdout).toContain("--category");
   });
 });
 

cli/node/tests/commands.test.ts

@@ -42,7 +42,7 @@ describe("cmdAdd", () => {
       userId: "alice",
       immutable: false,
       noInfer: false,
-      enableGraph: false,
+
       output: "text",
     });
     expect(mockBackend.add).toHaveBeenCalledOnce();
@@ -55,7 +55,7 @@ describe("cmdAdd", () => {
       messages: JSON.stringify([{ role: "user", content: "I love Python" }]),
       immutable: false,
       noInfer: false,
-      enableGraph: false,
+
       output: "text",
     });
     expect(mockBackend.add).toHaveBeenCalledOnce();
@@ -67,7 +67,7 @@ describe("cmdAdd", () => {
       userId: "alice",
       immutable: false,
       noInfer: false,
-      enableGraph: false,
+
       output: "json",
     });
     expect(output).toContain("results");
@@ -79,7 +79,7 @@ describe("cmdAdd", () => {
       userId: "alice",
       immutable: false,
       noInfer: false,
-      enableGraph: false,
+
       output: "quiet",
     });
     expect(output).not.toContain("dark mode");
@@ -101,7 +101,7 @@ describe("cmdAdd deduplicates PENDING", () => {
       userId: "alice",
       immutable: false,
       noInfer: false,
-      enableGraph: false,
+
       output: "text",
     });
     expect(output.match(/Queued/g)?.length).toBe(1);
@@ -114,7 +114,7 @@ describe("cmdAdd deduplicates PENDING", () => {
       userId: "alice",
       immutable: false,
       noInfer: false,
-      enableGraph: false,
+
       output: "json",
     });
     const data = JSON.parse(output);
@@ -130,7 +130,7 @@ describe("cmdAdd deduplicates PENDING", () => {
       userId: "alice",
       immutable: false,
       noInfer: false,
-      enableGraph: false,
+
       output: "agent",
     });
     const data = JSON.parse(output);
@@ -148,7 +148,7 @@ describe("cmdSearch", () => {
       threshold: 0.3,
       rerank: false,
       keyword: false,
-      enableGraph: false,
+
       output: "text",
     });
     expect(output).toContain("Found 2");
@@ -162,7 +162,7 @@ describe("cmdSearch", () => {
       threshold: 0.3,
       rerank: false,
       keyword: false,
-      enableGraph: false,
+
       output: "json",
     });
     expect(output).toContain("memory");
@@ -177,7 +177,7 @@ describe("cmdSearch", () => {
       threshold: 0.3,
       rerank: false,
       keyword: false,
-      enableGraph: false,
+
       output: "text",
     });
     expect(errOutput).toContain("No memories found");
@@ -205,7 +205,7 @@ describe("cmdList", () => {
       userId: "alice",
       page: 1,
       pageSize: 100,
-      enableGraph: false,
+
       output: "table",
     });
     expect(output).toContain("dark mode");
@@ -218,7 +218,7 @@ describe("cmdList", () => {
       userId: "alice",
       page: 1,
       pageSize: 100,
-      enableGraph: false,
+
       output: "text",
     });
     expect(errOutput).toContain("No memories found");
@@ -316,7 +316,7 @@ describe("agent mode", () => {
       userId: "alice",
       immutable: false,
       noInfer: false,
-      enableGraph: false,
+
       output: "agent",
     });
     const parsed = JSON.parse(output.trim());
@@ -336,7 +336,7 @@ describe("agent mode", () => {
       threshold: 0.3,
       rerank: false,
       keyword: false,
-      enableGraph: false,
+
       output: "agent",
     });
     const parsed = JSON.parse(output.trim());
@@ -361,7 +361,7 @@ describe("agent mode", () => {
       userId: "alice",
       page: 1,
       pageSize: 100,
-      enableGraph: false,
+
       output: "agent",
     });
     const parsed = JSON.parse(output.trim());

cli/node/tests/config.test.ts

@@ -64,7 +64,6 @@ describe("createDefaultConfig", () => {
     expect(config.platform.baseUrl).toBe("https://api.mem0.ai");
     expect(config.platform.apiKey).toBe("");
     expect(config.defaults.userId).toBe("");
-    expect(config.defaults.enableGraph).toBe(false);
   });
 });
 
@@ -105,9 +104,4 @@ describe("setNestedValue", () => {
     expect(config.defaults.userId).toBe("bob");
   });
 
-  it("coerces boolean for enable_graph", () => {
-    const config = createDefaultConfig();
-    expect(setNestedValue(config, "defaults.enable_graph", "true")).toBe(true);
-    expect(config.defaults.enableGraph).toBe(true);
-  });
 });

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

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

cli/python/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "mem0-cli"
-version = "0.2.3"
+version = "0.2.5"
 description = "The official CLI for mem0 — the memory layer for AI agents"
 readme = "README.md"
 license = "Apache-2.0"

cli/python/src/mem0_cli/__init__.py

@@ -1,3 +1,3 @@
 """mem0 CLI — the command-line interface for the mem0 memory layer."""
 
-__version__ = "0.2.3"
+__version__ = "0.2.4"

cli/python/src/mem0_cli/agent_detect.py

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

cli/python/src/mem0_cli/app.py

@@ -237,6 +237,14 @@ def main_callback(
         cmd_version()
         raise typer.Exit()
     if ctx.invoked_subcommand:
+        # Stash the active subcommand name so the JSON error envelope
+        # (print_error in agent mode) can report which command failed
+        # instead of an empty `"command": ""` field.
+        from mem0_cli.state import set_current_command
+
+        set_current_command(ctx.invoked_subcommand)
+    if ctx.invoked_subcommand and ctx.invoked_subcommand != "init":
+        # init fires its own telemetry from init_cmd.run_init with full M1-M6 props.
         _fire_telemetry(ctx.invoked_subcommand)
 
 
@@ -267,8 +275,6 @@ def add(
     categories: str | None = typer.Option(
         None, "--categories", help="Categories (JSON array or comma-separated)."
     ),
-    graph: bool = typer.Option(False, "--graph", help="Enable graph memory extraction."),
-    no_graph: bool = typer.Option(False, "--no-graph", help="Disable graph memory extraction."),
     output: str = typer.Option(
         "text", "--output", "-o", help="Output format: text, json, quiet.", rich_help_panel="Output"
     ),
@@ -295,13 +301,6 @@ def add(
     backend, config = _get_backend_and_config(api_key, base_url)
     ids = _resolve_ids(config, user_id=user_id, agent_id=agent_id, app_id=app_id, run_id=run_id)
 
-    if no_graph:
-        graph_enabled = False
-    elif graph:
-        graph_enabled = True
-    else:
-        graph_enabled = config.defaults.enable_graph
-
     cmd_add(
         backend,
         text,
@@ -313,7 +312,6 @@ def add(
         no_infer=no_infer,
         expires=expires,
         categories=categories,
-        enable_graph=graph_enabled,
         output=output,
     )
 
@@ -357,12 +355,6 @@ def search(
         help="Specific fields to return (comma-separated).",
         rich_help_panel="Search",
     ),
-    graph: bool = typer.Option(
-        False, "--graph", help="Enable graph in search.", rich_help_panel="Search"
-    ),
-    no_graph: bool = typer.Option(
-        False, "--no-graph", help="Disable graph in search.", rich_help_panel="Search"
-    ),
     output: str = typer.Option(
         "text", "--output", "-o", help="Output: text, json, table.", rich_help_panel="Output"
     ),
@@ -396,13 +388,6 @@ def search(
     backend, config = _get_backend_and_config(api_key, base_url)
     ids = _resolve_ids(config, user_id=user_id, agent_id=agent_id, app_id=app_id, run_id=run_id)
 
-    if no_graph:
-        graph_enabled = False
-    elif graph:
-        graph_enabled = True
-    else:
-        graph_enabled = config.defaults.enable_graph
-
     cmd_search(
         backend,
         query,
@@ -413,7 +398,6 @@ def search(
         keyword=keyword,
         filter_json=filter_json,
         fields=fields,
-        enable_graph=graph_enabled,
         output=output,
     )
 
@@ -480,12 +464,6 @@ def list_cmd(
     before: str | None = typer.Option(
         None, "--before", help="Created before (YYYY-MM-DD).", rich_help_panel="Filters"
     ),
-    graph: bool = typer.Option(
-        False, "--graph", help="Enable graph in listing.", rich_help_panel="Filters"
-    ),
-    no_graph: bool = typer.Option(
-        False, "--no-graph", help="Disable graph in listing.", rich_help_panel="Filters"
-    ),
     output: str = typer.Option(
         "table", "--output", "-o", help="Output: text, json, table.", rich_help_panel="Output"
     ),
@@ -511,13 +489,6 @@ def list_cmd(
     backend, config = _get_backend_and_config(api_key, base_url)
     ids = _resolve_ids(config, user_id=user_id, agent_id=agent_id, app_id=app_id, run_id=run_id)
 
-    if no_graph:
-        graph_enabled = False
-    elif graph:
-        graph_enabled = True
-    else:
-        graph_enabled = config.defaults.enable_graph
-
     cmd_list(
         backend,
         **ids,
@@ -526,7 +497,6 @@ def list_cmd(
         category=category,
         after=after,
         before=before,
-        enable_graph=graph_enabled,
         output=output,
     )
 
@@ -889,6 +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.
 
@@ -897,10 +880,38 @@ 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)
 
 
 # (entity_app registered at module level, below sub-group definitions)
@@ -1236,11 +1247,28 @@ def main() -> None:
     import sys
 
     # Allow --json/--agent anywhere in the command line (not just before subcommand).
-    _json_flags = {"--json", "--agent"}
-    if any(a in _json_flags for a in sys.argv[1:]):
+    # Special case: `mem0 init --agent` is a subcommand flag (Agent Mode bootstrap)
+    # consumed by init_cmd, not a global JSON-output toggle — leave it in argv.
+    argv_rest = sys.argv[1:]
+    is_init = "init" in argv_rest
+    _global_flags = {"--json"} if is_init else {"--json", "--agent"}
+    if any(a in _global_flags for a in argv_rest):
         from mem0_cli.state import set_agent_mode
 
         set_agent_mode(True)
-        sys.argv = [sys.argv[0]] + [a for a in sys.argv[1:] if a not in _json_flags]
+        sys.argv = [sys.argv[0]] + [a for a in argv_rest if a not in _global_flags]
 
-    app()
+    try:
+        app()
+    finally:
+        # Surface any unclaimed Agent Mode notice once per command, after the
+        # primary output. In JSON/agent mode the notice is folded into the
+        # envelope by format_json_envelope, so skip the stderr banner there
+        # to avoid duplicate output.
+        from mem0_cli.state import is_agent_mode, take_notice
+
+        notice = take_notice()
+        if notice and not is_agent_mode():
+            from rich.console import Console
+
+            Console(stderr=True).print(f"\n[yellow]🔔 {notice}[/yellow]\n")

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

@@ -26,7 +26,6 @@ class Backend(ABC):
         infer: bool = True,
         expires: str | None = None,
         categories: list[str] | None = None,
-        enable_graph: bool = False,
     ) -> dict: ...
 
     @abstractmethod
@@ -44,7 +43,6 @@ class Backend(ABC):
         keyword: bool = False,
         filters: dict | None = None,
         fields: list[str] | None = None,
-        enable_graph: bool = False,
     ) -> list[dict]: ...
 
     @abstractmethod
@@ -63,7 +61,6 @@ class Backend(ABC):
         category: str | None = None,
         after: str | None = None,
         before: str | None = None,
-        enable_graph: bool = False,
     ) -> list[dict]: ...
 
     @abstractmethod

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

@@ -30,7 +30,7 @@ class PlatformBackend(Backend):
         )
 
     def _request(self, method: str, path: str, **kwargs: Any) -> Any:
-        from mem0_cli.state import is_agent_mode
+        from mem0_cli.state import capture_notice, is_agent_mode
 
         self._client.headers["X-Mem0-Caller-Type"] = "agent" if is_agent_mode() else "user"
         resp = self._client.request(method, path, **kwargs)
@@ -48,7 +48,26 @@ class PlatformBackend(Backend):
         resp.raise_for_status()
         if resp.status_code == 204:
             return {}
-        return resp.json()
+        data = resp.json()
+
+        # Pull the unclaimed-Agent-Mode notice out of the body (or the header
+        # fallback for endpoints that return non-dict / non-dict-leading
+        # payloads) and stash it for end-of-command surfacing.
+        notice = None
+        if isinstance(data, dict) and "mem0_notice" in data:
+            notice = data.pop("mem0_notice")
+        elif (
+            isinstance(data, list)
+            and data
+            and isinstance(data[0], dict)
+            and "mem0_notice" in data[0]
+        ):
+            notice = data[0].pop("mem0_notice")
+        if notice is None:
+            notice = resp.headers.get("X-Mem0-Notice-Message") or None
+        capture_notice(notice)
+
+        return data
 
     def add(
         self,
@@ -64,7 +83,6 @@ class PlatformBackend(Backend):
         infer: bool = True,
         expires: str | None = None,
         categories: list[str] | None = None,
-        enable_graph: bool = False,
     ) -> dict:
         payload: dict[str, Any] = {}
 
@@ -91,11 +109,9 @@ class PlatformBackend(Backend):
             payload["expiration_date"] = expires
         if categories:
             payload["categories"] = categories
-        if enable_graph:
-            payload["enable_graph"] = True
         payload["source"] = "CLI"
 
-        return self._request("POST", "/v1/memories/", json=payload)
+        return self._request("POST", "/v3/memories/add/", json=payload)
 
     def _build_filters(
         self,
@@ -106,7 +122,7 @@ class PlatformBackend(Backend):
         run_id: str | None = None,
         extra_filters: dict | None = None,
     ) -> dict | None:
-        """Build a filters dict for v2 API endpoints.
+        """Build a filters dict for v3 API endpoints.
 
         Entity IDs are ANDed (all provided IDs must match).
         Extra filters (date ranges, categories) are also ANDed.
@@ -152,7 +168,6 @@ class PlatformBackend(Backend):
         keyword: bool = False,
         filters: dict | None = None,
         fields: list[str] | None = None,
-        enable_graph: bool = False,
     ) -> list[dict]:
         payload: dict[str, Any] = {"query": query, "top_k": top_k, "threshold": threshold}
 
@@ -171,11 +186,9 @@ class PlatformBackend(Backend):
             payload["keyword_search"] = True
         if fields:
             payload["fields"] = fields
-        if enable_graph:
-            payload["enable_graph"] = True
         payload["source"] = "CLI"
 
-        result = self._request("POST", "/v2/memories/search/", json=payload)
+        result = self._request("POST", "/v3/memories/search/", json=payload)
         return (
             result
             if isinstance(result, list)
@@ -197,12 +210,11 @@ class PlatformBackend(Backend):
         category: str | None = None,
         after: str | None = None,
         before: str | None = None,
-        enable_graph: bool = False,
     ) -> list[dict]:
         payload: dict[str, Any] = {}
         params = {"page": str(page), "page_size": str(page_size)}
 
-        # Build filters for v2 API — entity IDs and date filters go inside "filters"
+        # Build filters — entity IDs and date filters go inside "filters"
         extra: dict[str, Any] = {}
         if category:
             extra["categories"] = {"contains": category}
@@ -220,11 +232,9 @@ class PlatformBackend(Backend):
         )
         if api_filters:
             payload["filters"] = api_filters
-        if enable_graph:
-            payload["enable_graph"] = True
         payload["source"] = "CLI"
 
-        result = self._request("POST", "/v2/memories/", json=payload, params=params)
+        result = self._request("POST", "/v3/memories/", json=payload, params=params)
         return (
             result
             if isinstance(result, list)

cli/python/src/mem0_cli/branding.py

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

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

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

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

@@ -39,7 +39,6 @@ def cmd_config_show(*, output: str = "text") -> None:
                     "agent_id": config.defaults.agent_id or None,
                     "app_id": config.defaults.app_id or None,
                     "run_id": config.defaults.run_id or None,
-                    "enable_graph": config.defaults.enable_graph,
                 },
                 "platform": {
                     "api_key": redact_key(config.platform.api_key),
@@ -73,10 +72,6 @@ def cmd_config_show(*, output: str = "text") -> None:
         "defaults.run_id",
         config.defaults.run_id or f"[{DIM_COLOR}](not set)[/]",
     )
-    table.add_row(
-        "defaults.enable_graph",
-        str(config.defaults.enable_graph).lower(),
-    )
     table.add_row("", "")
 
     # Platform

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

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

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

@@ -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}")

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

@@ -62,7 +62,6 @@ def cmd_add(
     no_infer: bool,
     expires: str | None,
     categories: str | None,
-    enable_graph: bool = False,
     output: str = "text",
 ) -> None:
     """Add a memory."""
@@ -145,7 +144,6 @@ def cmd_add(
                 infer=not no_infer,
                 expires=expires,
                 categories=cats,
-                enable_graph=enable_graph,
             )
         except Exception as e:
             ts.error_msg = str(e)
@@ -226,7 +224,6 @@ def cmd_search(
     keyword: bool,
     filter_json: str | None,
     fields: str | None,
-    enable_graph: bool = False,
     output: str = "text",
 ) -> None:
     """Search memories."""
@@ -269,7 +266,6 @@ def cmd_search(
                 keyword=keyword,
                 filters=filters,
                 fields=field_list,
-                enable_graph=enable_graph,
             )
         except Exception as e:
             print_error(err_console, str(e))
@@ -356,7 +352,6 @@ def cmd_list(
     category: str | None,
     after: str | None,
     before: str | None,
-    enable_graph: bool = False,
     output: str = "table",
 ) -> None:
     """List memories."""
@@ -385,7 +380,6 @@ def cmd_list(
                 category=category,
                 after=after,
                 before=before,
-                enable_graph=enable_graph,
             )
         except Exception as e:
             print_error(err_console, str(e))

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

@@ -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")
 

cli/python/src/mem0_cli/config.py

@@ -28,6 +28,14 @@ class PlatformConfig:
     api_key: str = ""
     base_url: str = DEFAULT_BASE_URL
     user_email: str = ""
+    # Agent Mode (unclaimed-shadow signup)
+    agent_mode: bool = False  # True while the key is an unclaimed agent-mode key
+    created_via: str = ""  # "agent_mode" | "email" | "api_key" | "existing_key"
+    agent_caller: str = (
+        ""  # canonical agent name when created_via == "agent_mode" (e.g. "claude-code")
+    )
+    claimed_at: str = ""  # ISO timestamp once the agent has been claimed by a human
+    default_user_id: str = ""  # `user_<slug>` returned by bootstrap; used as auto-default
 
 
 @dataclass
@@ -36,7 +44,6 @@ class DefaultsConfig:
     agent_id: str = ""
     app_id: str = ""
     run_id: str = ""
-    enable_graph: bool = False
 
 
 @dataclass
@@ -60,7 +67,6 @@ SHORT_KEY_ALIASES: dict[str, str] = {
     "agent_id": "defaults.agent_id",
     "app_id": "defaults.app_id",
     "run_id": "defaults.run_id",
-    "enable_graph": "defaults.enable_graph",
 }
 
 
@@ -85,14 +91,17 @@ 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", "")
         config.defaults.agent_id = defaults.get("agent_id", "")
         config.defaults.app_id = defaults.get("app_id", "")
         config.defaults.run_id = defaults.get("run_id", "")
-        config.defaults.enable_graph = defaults.get("enable_graph", False)
-
         telemetry = data.get("telemetry", {})
         config.telemetry.anonymous_id = telemetry.get("anonymous_id", "")
 
@@ -121,10 +130,6 @@ def load_config() -> Mem0Config:
     if env_run_id:
         config.defaults.run_id = env_run_id
 
-    env_graph = os.environ.get("MEM0_ENABLE_GRAPH")
-    if env_graph:
-        config.defaults.enable_graph = env_graph.lower() in ("true", "1", "yes")
-
     return config
 
 
@@ -139,12 +144,16 @@ def save_config(config: Mem0Config) -> None:
             "agent_id": config.defaults.agent_id,
             "app_id": config.defaults.app_id,
             "run_id": config.defaults.run_id,
-            "enable_graph": config.defaults.enable_graph,
         },
         "platform": {
             "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,
@@ -156,6 +165,19 @@ def save_config(config: Mem0Config) -> None:
 
     os.chmod(CONFIG_FILE, stat.S_IRUSR | stat.S_IWUSR)  # 0600
 
+    # Propagate the active api_key to ecosystem touchpoints (Claude Code
+    # plugin env injection, shell rc exports). Idempotent — only updates
+    # EXISTING entries; never creates new ones. Best-effort: any IOError
+    # in the sync is swallowed so config.json is always the authoritative
+    # write, never blocked by plugin-state issues.
+    if config.platform.api_key:
+        try:
+            from mem0_cli.plugin_sync import sync_api_key
+
+            sync_api_key(config.platform.api_key)
+        except Exception:
+            pass
+
 
 def redact_key(key: str) -> str:
     """Redact an API key for display: m0-xxx...xxx"""

cli/python/src/mem0_cli/output.py

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

cli/python/src/mem0_cli/plugin_sync.py

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

cli/python/src/mem0_cli/state.py

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

cli/python/src/mem0_cli/telemetry.py

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

cli/python/tests/test_agent_mode.py

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

cli/python/tests/test_cli_integration.py

@@ -224,24 +224,13 @@ class TestCLIIsolated:
 
 
 class TestCLINewFeatures:
-    """Tests for MCP parity features: --graph, --limit, entities delete."""
+    """Tests for MCP parity features: --limit, entities delete."""
 
-    def test_add_help_has_graph(self):
-        result = _run(["add", "--help"])
-        assert result.returncode == 0
-        assert "--graph" in result.stdout
-
-    def test_search_help_has_graph_and_limit(self):
+    def test_search_help_has_limit(self):
         result = _run(["search", "--help"])
         assert result.returncode == 0
-        assert "--graph" in result.stdout
         assert "--limit" in result.stdout
 
-    def test_list_help_has_graph(self):
-        result = _run(["list", "--help"])
-        assert result.returncode == 0
-        assert "--graph" in result.stdout
-
     def test_delete_entity_via_delete_flag(self):
         """delete --entity should appear in help output."""
         result = _run(["delete", "--help"])

cli/python/tests/test_commands.py

@@ -997,85 +997,6 @@ class TestEntitiesDeleteCommand:
         mock_backend.delete_entities.assert_not_called()
 
 
-class TestEnableGraph:
-    def test_add_with_graph(self, mock_backend):
-        console, _buf = _make_console()
-        err_console, _err_buf = _make_err_console()
-        with (
-            patch("mem0_cli.commands.memory.console", console),
-            patch("mem0_cli.commands.memory.err_console", err_console),
-        ):
-            cmd_add(
-                mock_backend,
-                "test",
-                user_id="alice",
-                agent_id=None,
-                app_id=None,
-                run_id=None,
-                messages=None,
-                file=None,
-                metadata=None,
-                immutable=False,
-                no_infer=False,
-                expires=None,
-                categories=None,
-                enable_graph=True,
-                output="text",
-            )
-        call_kwargs = mock_backend.add.call_args
-        assert call_kwargs.kwargs.get("enable_graph") is True
-
-    def test_search_with_graph(self, mock_backend):
-        console, _buf = _make_console()
-        err_console, _err_buf = _make_err_console()
-        with (
-            patch("mem0_cli.commands.memory.console", console),
-            patch("mem0_cli.commands.memory.err_console", err_console),
-        ):
-            cmd_search(
-                mock_backend,
-                "test",
-                user_id="alice",
-                agent_id=None,
-                app_id=None,
-                run_id=None,
-                top_k=10,
-                threshold=0.3,
-                rerank=False,
-                keyword=False,
-                filter_json=None,
-                fields=None,
-                enable_graph=True,
-                output="text",
-            )
-        call_kwargs = mock_backend.search.call_args
-        assert call_kwargs.kwargs.get("enable_graph") is True
-
-    def test_list_with_graph(self, mock_backend):
-        console, _buf = _make_console()
-        err_console, _err_buf = _make_err_console()
-        with (
-            patch("mem0_cli.commands.memory.console", console),
-            patch("mem0_cli.commands.memory.err_console", err_console),
-        ):
-            cmd_list(
-                mock_backend,
-                user_id="alice",
-                agent_id=None,
-                app_id=None,
-                run_id=None,
-                page=1,
-                page_size=100,
-                category=None,
-                after=None,
-                before=None,
-                enable_graph=True,
-                output="table",
-            )
-        call_kwargs = mock_backend.list_memories.call_args
-        assert call_kwargs.kwargs.get("enable_graph") is True
-
-
 class TestEventCommands:
     def test_event_list_table(self, mock_backend):
         console, buf = _make_console()

cli/python/tests/test_config.py

@@ -121,46 +121,6 @@ class TestConfig:
         assert config.defaults.agent_id == ""
         assert config.defaults.app_id == ""
         assert config.defaults.run_id == ""
-        assert config.defaults.enable_graph is False
-
-    def test_enable_graph_save_and_load(self, isolate_config):
-        config = Mem0Config()
-        config.defaults.enable_graph = True
-        save_config(config)
-        loaded = load_config()
-        assert loaded.defaults.enable_graph is True
-
-    def test_enable_graph_env_var_true(self, isolate_config, monkeypatch):
-        monkeypatch.setenv("MEM0_ENABLE_GRAPH", "true")
-        loaded = load_config()
-        assert loaded.defaults.enable_graph is True
-
-    def test_enable_graph_env_var_false(self, isolate_config, monkeypatch):
-        config = Mem0Config()
-        config.defaults.enable_graph = True
-        save_config(config)
-        monkeypatch.setenv("MEM0_ENABLE_GRAPH", "false")
-        loaded = load_config()
-        assert loaded.defaults.enable_graph is False
-
-    def test_backward_compat_no_enable_graph_key(self, isolate_config):
-        """Old config files without 'enable_graph' key should default to False."""
-        import json
-
-        from mem0_cli.config import CONFIG_FILE, ensure_config_dir
-
-        ensure_config_dir()
-        data = {
-            "version": 1,
-            "defaults": {"user_id": "alice"},
-            "platform": {"api_key": "m0-test", "base_url": "https://api.mem0.ai"},
-        }
-        with open(CONFIG_FILE, "w") as f:
-            json.dump(data, f)
-
-        loaded = load_config()
-        assert loaded.defaults.enable_graph is False
-        assert loaded.defaults.user_id == "alice"
 
 
 class TestNestedAccess:
@@ -192,11 +152,6 @@ class TestNestedAccess:
         assert set_nested_value(config, "defaults.user_id", "bob")
         assert config.defaults.user_id == "bob"
 
-    def test_set_defaults_enable_graph(self):
-        config = Mem0Config()
-        assert set_nested_value(config, "defaults.enable_graph", "true")
-        assert config.defaults.enable_graph is True
-
 
 class TestResolveIds:
     def test_cli_flag_overrides_default(self):

cli/python/tests/test_init_internals.py

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

docs/api-reference.mdx

@@ -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.

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

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

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

@@ -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>

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

@@ -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>

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

@@ -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>

docs/api-reference/organizations-projects.mdx

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

docs/changelog/highlights.mdx

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

docs/changelog/openclaw.mdx

@@ -4,6 +4,97 @@ 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:**

docs/changelog/platform.mdx

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

docs/changelog/sdk.mdx

@@ -7,6 +7,37 @@ mode: "wide"
 <Tabs>
 <Tab title="Python">
 
+<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 +55,7 @@ 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 +924,29 @@ See the [OSS v1 to v2 migration guide](https://docs.mem0.ai/migration/oss-v1-to-
 </Tab>
 
 <Tab title="TypeScript">
+<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 +1323,33 @@ See the [TypeScript SDK migration guide](https://docs.mem0.ai/migration/ts-v2-to
 
 <Tab title="CLI">
 
+<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 <5s 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:**
+- **V3 API Routes:** Migrated `add`, `search`, and `list` commands from v1/v2 to v3 API endpoints — `POST /v3/memories/add/`, `POST /v3/memories/search/`, `POST /v3/memories/`. Aligns both CLIs with the Python and TypeScript SDKs which already use v3 ([#4916](https://github.com/mem0ai/mem0/pull/4916))
+
+**Breaking Changes:**
+- **`--graph` / `--no-graph` removed:** The `enable_graph` config option, `--graph` and `--no-graph` CLI flags, and `MEM0_ENABLE_GRAPH` environment variable have been removed from both CLIs. Graph memory is now a project-level setting on the Platform ([#4916](https://github.com/mem0ai/mem0/pull/4916))
+
+</Update>
+
 <Update label="2026-04-11" description="Python v0.2.3 / Node v0.2.3">
 
 **Bug Fixes:**

docs/cookbooks/companions/quickstart-demo.mdx

@@ -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

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

@@ -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>
 
 ---

docs/cookbooks/essentials/entity-partitioning-playbook.mdx

@@ -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
 

docs/cookbooks/essentials/exporting-memories.mdx

@@ -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:

docs/cookbooks/frameworks/eliza-os-character.mdx

@@ -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.)

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

@@ -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

docs/cookbooks/frameworks/llamaindex-multiagent.mdx

@@ -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>
 
 ---
 

docs/cookbooks/frameworks/llamaindex-react.mdx

@@ -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>"
 

docs/cookbooks/integrations/agents-sdk-tool.mdx

@@ -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)
 
 ---

docs/cookbooks/integrations/openai-tool-calls.mdx

@@ -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)
 

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

@@ -216,7 +216,7 @@ memory.delete_all(user_id="alice")
 ## Put it into practice
 
 - Review the <Link href="/api-reference/memory/delete-memory">Delete Memory API reference</Link>, plus <Link href="/api-reference/memory/batch-delete">Batch Delete</Link> and <Link href="/api-reference/memory/delete-memories">Filtered Delete</Link>.
-- Pair deletes with <Link href="/platform/features/expiration-date">Expiration Policies</Link> to automate retention.
+- Pair deletes with <Link href="/platform/features/platform-overview">Expiration Policies</Link> to automate retention.
 
 ## See it live
 
@@ -236,6 +236,6 @@ memory.delete_all(user_id="alice")
     title="Enable Expiration Policies"
     description="Automate retention with the platform’s expiration feature."
     icon="clock"
-    href="/platform/features/expiration-date"
+    href="/platform/features/platform-overview"
   />
 </CardGroup>

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

@@ -156,6 +156,10 @@ 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 +255,4 @@ For the full list of filter logic, comparison operators, and optional search par
     icon="rocket"
     href="/cookbooks/operations/support-inbox"
   />
-</CardGroup>
+</CardGroup>

docs/docs.json

@@ -72,7 +72,8 @@
                           "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 +84,8 @@
                           "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 +155,7 @@
                     "icon": "rocket",
                     "pages": [
                       "open-source/overview",
+                      "open-source/setup",
                       "vibecoding",
                       "open-source/python-quickstart",
                       "open-source/node-quickstart"
@@ -399,6 +402,8 @@
                       "integrations/langgraph",
                       "integrations/llama-index",
                       "integrations/crewai",
+                      "integrations/autogen",
+                      "integrations/agno",
                       "integrations/camel-ai",
                       "integrations/openai-agents-sdk",
                       "integrations/google-ai-adk",
@@ -427,7 +432,12 @@
                     "group": "Developer Tools",
                     "icon": "wrench",
                     "pages": [
-                      "integrations/langchain-tools"
+                      "integrations/dify",
+                      "integrations/flowise",
+                      "integrations/langchain-tools",
+                      "integrations/agentops",
+                      "integrations/keywords",
+                      "integrations/raycast"
                     ]
                   }
                 ]
@@ -571,7 +581,7 @@
     "primary": {
       "type": "button",
       "label": "Your Dashboard",
-      "href": "https://app.mem0.ai"
+      "href": "https://app.mem0.ai?utm_source=oss&utm_medium=docs-nav"
     }
   },
   "footer": {
@@ -601,7 +611,7 @@
         "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"
       }
     ]
   },
@@ -1094,34 +1104,6 @@
       "source": "/v0x/faqs",
       "destination": "/platform/faqs"
     },
-    {
-      "source": "/integrations/raycast",
-      "destination": "/integrations"
-    },
-    {
-      "source": "/integrations/autogen",
-      "destination": "/integrations"
-    },
-    {
-      "source": "/integrations/keywords",
-      "destination": "/integrations"
-    },
-    {
-      "source": "/integrations/agentops",
-      "destination": "/integrations"
-    },
-    {
-      "source": "/integrations/flowise",
-      "destination": "/integrations"
-    },
-    {
-      "source": "/integrations/agno",
-      "destination": "/integrations"
-    },
-    {
-      "source": "/integrations/dify",
-      "destination": "/integrations"
-    },
     {
       "source": "/integrations/multion",
       "destination": "/integrations"
@@ -1163,4 +1145,4 @@
       "destination": "/introduction"
     }
   ]
-}
+}

docs/integrations.mdx

@@ -20,6 +20,23 @@ Here are the available integrations for Mem0:
 ## Integrations
 
 <CardGroup cols={2}>
+  <Card
+    title="AgentOps"
+    icon={
+      <svg
+        xmlns="http://www.w3.org/2000/svg"
+        width="25"
+        height="26"
+        viewBox="0 0 30 36"
+        fill="none"
+      >
+      <path d="M10.4659 6.47277C10.45 6.37428 10.4381 6.27986 10.4303 6.18101L10.4285 6.16388C10.4212 6.09482 10.414 6.02566 10.4106 5.95626L1.18538 21.8752C0.505422 23.0493 0.323356 24.4208 0.675227 25.7289C0.849119 26.3869 1.14971 26.9859 1.55323 27.5098C1.95675 28.0338 2.46282 28.4751 3.05175 28.8143C3.83464 29.2675 4.70856 29.5 5.59028 29.5C6.03318 29.5 6.4798 29.4408 6.91899 29.3226C8.23581 28.972 9.3349 28.1326 10.0152 26.9545L15.9268 16.749V16.7449L16.5001 15.7637L17.6431 13.7936L16.5001 11.8234L15.9309 10.8381L15.9268 10.8341L13.7836 7.13406C13.6651 6.933 13.5741 6.72418 13.5109 6.51165C13.2817 5.80223 13.3292 5.04172 13.6097 4.37599L13.8115 4.02535C14.3532 3.09155 15.31 2.53987 16.3184 2.47692C16.3738 2.46915 16.4251 2.46915 16.4804 2.46915C16.5421 2.46915 16.6038 2.47257 16.6654 2.47599L16.6822 2.47692C17.6906 2.53987 18.6474 3.09155 19.1892 4.02535L21.2216 7.52838L21.8146 8.55289L21.8421 8.60399L30.1024 22.8601C30.5174 23.5814 30.6281 24.4167 30.4148 25.2205C30.1975 26.0244 29.6832 26.6942 28.9598 27.1081C28.2364 27.5258 27.3977 27.6361 26.5911 27.4195C25.7844 27.2066 25.1123 26.6905 24.6968 25.9696L18.2119 14.7788L17.069 16.7449L22.9847 26.9545C23.6646 28.1326 24.7641 28.972 26.0809 29.3226C26.5197 29.4408 26.9626 29.5 27.4096 29.5C28.2914 29.5 29.1612 29.2675 29.9482 28.8143C31.1264 28.1367 31.9728 27.0411 32.3247 25.7289C32.6766 24.4208 32.4949 23.0493 31.8145 21.8752L21.1261 3.43034C20.7029 2.51617 20.0033 1.72011 19.0621 1.18027C18.5281 0.877027 17.9708 0.675975 17.3975 0.581189C17.3027 0.565268 17.2076 0.549717 17.1129 0.537868C17.0099 0.52602 16.9074 0.518244 16.8045 0.510469C16.6027 0.498621 16.3972 0.494548 16.1914 0.510469C16.0885 0.518244 15.9859 0.52639 15.883 0.537868C15.795 0.54887 15.7067 0.563384 15.6187 0.577852L15.5984 0.581189C15.0291 0.675605 14.4673 0.876657 13.9375 1.18027C12.9885 1.72789 12.2766 2.53579 11.8537 3.46181C11.7742 3.63473 11.707 3.81282 11.6471 3.99314C11.6361 4.02668 11.6269 4.06051 11.6177 4.09435C11.612 4.11503 11.6064 4.13579 11.6003 4.15642C11.5624 4.28601 11.5275 4.41634 11.4996 4.54853C11.4885 4.60231 11.4794 4.65668 11.4703 4.71111L11.4666 4.73329C11.4443 4.86399 11.4264 4.99543 11.4145 5.12762C11.4093 5.18686 11.4045 5.24573 11.4012 5.30534C11.3934 5.44567 11.3923 5.58637 11.3963 5.72744C11.3969 5.74403 11.3962 5.76062 11.3956 5.7772C11.3949 5.79616 11.3942 5.81512 11.3952 5.83407C11.3952 5.86184 11.3952 5.88924 11.3993 5.92071C11.3998 5.9291 11.4006 5.93736 11.4014 5.94564C11.402 5.95125 11.4026 5.95687 11.403 5.96255C11.4045 5.98181 11.4064 6.00106 11.4082 6.02031C11.4097 6.03577 11.4109 6.05122 11.4122 6.06674C11.4142 6.09134 11.4163 6.11621 11.419 6.14139L11.4428 6.32282C11.4506 6.38983 11.4625 6.46092 11.4744 6.52757C11.5063 6.68863 11.5468 6.84896 11.5936 7.0078C11.5944 7.0102 11.5949 7.0127 11.5955 7.0152C11.5958 7.01662 11.5961 7.01804 11.5965 7.01944C11.5967 7.02051 11.597 7.02157 11.5974 7.02261C11.6483 7.19293 11.7081 7.36177 11.7787 7.52838C11.8619 7.72943 11.9607 7.92641 12.0715 8.11932L12.3245 8.5566V8.56067L12.4984 8.85614L12.7199 9.24232H12.7239L12.728 9.25417L14.7802 12.7927V12.7968L14.7883 12.805V12.809L15.3576 13.7943L14.7883 14.7796L8.30344 25.9703C7.88431 26.6912 7.21216 27.2077 6.40921 27.4202C6.14019 27.4913 5.86338 27.5306 5.59474 27.5306C5.053 27.5306 4.51906 27.3888 4.04085 27.1089C3.31705 26.6953 2.79909 26.0251 2.58581 25.2213C2.36845 24.4174 2.47917 23.5821 2.89829 22.8609L11.1585 8.60473L11.186 8.56141V8.55734C11.1266 8.45478 11.0753 8.35629 11.024 8.25409C11.0105 8.22496 10.9969 8.19611 10.9834 8.16739C10.9458 8.08735 10.9086 8.00836 10.8739 7.92715C10.8718 7.92504 10.8708 7.92194 10.8698 7.91887C10.8688 7.91602 10.8679 7.91319 10.8661 7.91123V7.90346C10.8423 7.8483 10.8186 7.79311 10.7989 7.73795C10.7476 7.60799 10.7041 7.47803 10.6644 7.3477C10.6012 7.15479 10.5536 6.96152 10.518 6.76861C10.4942 6.67012 10.4786 6.5757 10.4667 6.47684C10.4667 6.47684 10.47 6.47684 10.4659 6.47277Z" fill="currentColor"></path>
+      </svg>
+    }
+    href="/integrations/agentops"
+  >
+    Monitor and analyze Mem0 operations with comprehensive AI agent analytics and LLM observability.
+  </Card>
   <Card
     title="Camel AI"
     href="/integrations/camel-ai"
@@ -86,6 +103,27 @@ Here are the available integrations for Mem0:
   >
     Build RAG applications with LlamaIndex and Mem0.
   </Card>
+  <Card
+    title="AutoGen"
+    icon={
+      <svg
+        xmlns="http://www.w3.org/2000/svg"
+        width="24"
+        height="24"
+        viewBox="0 0 96 85"
+        fill="none"
+      >
+        <rect width="96" height="85" rx="6" fill="#2D2D2F" />
+        <path
+          d="M32.6484 28.7109L23.3672 57H15.8906L28.5703 22.875H33.3281L32.6484 28.7109ZM40.3594 57L31.0547 28.7109L30.3047 22.875H35.1094L47.8594 57H40.3594ZM39.9375 44.2969V49.8047H21.9141V44.2969H39.9375ZM77.6484 39.1641V52.6875C77.1172 53.3281 76.2969 54.0234 75.1875 54.7734C74.0781 55.5078 72.6484 56.1406 70.8984 56.6719C69.1484 57.2031 67.0312 57.4688 64.5469 57.4688C62.3438 57.4688 60.3359 57.1094 58.5234 56.3906C56.7109 55.6562 55.1484 54.5859 53.8359 53.1797C52.5391 51.7734 51.5391 50.0547 50.8359 48.0234C50.1328 45.9766 49.7812 43.6406 49.7812 41.0156V38.8828C49.7812 36.2578 50.1172 33.9219 50.7891 31.875C51.4766 29.8281 52.4531 28.1016 53.7188 26.6953C54.9844 25.2891 56.4922 24.2188 58.2422 23.4844C59.9922 22.75 61.9375 22.3828 64.0781 22.3828C67.0469 22.3828 69.4844 22.8672 71.3906 23.8359C73.2969 24.7891 74.75 26.1172 75.75 27.8203C76.7656 29.5078 77.3906 31.4453 77.625 33.6328H70.8047C70.6328 32.4766 70.3047 31.4688 69.8203 30.6094C69.3359 29.75 68.6406 29.0781 67.7344 28.5938C66.8438 28.1094 65.6875 27.8672 64.2656 27.8672C63.0938 27.8672 62.0469 28.1094 61.125 28.5938C60.2188 29.0625 59.4531 29.7578 58.8281 30.6797C58.2031 31.6016 57.7266 32.7422 57.3984 34.1016C57.0703 35.4609 56.9062 37.0391 56.9062 38.8359V41.0156C56.9062 42.7969 57.0781 44.375 57.4219 45.75C57.7656 47.1094 58.2734 48.2578 58.9453 49.1953C59.6328 50.1172 60.4766 50.8125 61.4766 51.2812C62.4766 51.75 63.6406 51.9844 64.9688 51.9844C66.0781 51.9844 67 51.8906 67.7344 51.7031C68.4844 51.5156 69.0859 51.2891 69.5391 51.0234C70.0078 50.7422 70.3672 50.4766 70.6172 50.2266V44.1797H64.1953V39.1641H77.6484Z"
+          fill="white"
+        />
+      </svg>
+    }
+    href="/integrations/autogen"
+  >
+    Build multi-agent systems with persistent memory capabilities.
+  </Card>
   <Card
     title="CrewAI"
     icon={
@@ -167,6 +205,26 @@ Here are the available integrations for Mem0:
   >
     Use Mem0 with LangChain Tools for enhanced agent capabilities.
   </Card>
+  <Card
+    title="Dify"
+    icon={
+      <svg
+        xmlns="http://www.w3.org/2000/svg"
+        width="24"
+        height="24"
+        viewBox="0 0 200 200"
+        fill="none"
+      >
+        <path
+          d="M40 20 H120 C160 20, 160 180, 120 180 H40 V20"
+          fill="currentColor"
+        />
+      </svg>
+    }
+    href="/integrations/dify"
+  >
+    Build AI applications with persistent memory using Dify and Mem0.
+  </Card>
   <Card
     title="Livekit"
     icon={
@@ -232,6 +290,63 @@ Here are the available integrations for Mem0:
   >
     Build conversational AI agents with memory using Pipecat.
   </Card>
+  <Card
+    title="Agno"
+    icon={
+      <svg
+        xmlns="http://www.w3.org/2000/svg"
+        width="24"
+        height="24"
+        viewBox="0 0 24 24"
+        fill="none"
+      >
+        <path d="M8 4h8v12h8" stroke="currentColor" strokeWidth="2" fill="none" transform="rotate(15, 12, 12)"/>
+      </svg>
+    }
+    href="/integrations/agno"
+  >
+    Build autonomous agents with memory using Agno framework.
+  </Card>
+
+  <Card
+    title="Keywords AI"
+    icon={
+      <svg
+        xmlns="http://www.w3.org/2000/svg"
+        width="24"
+        height="24"
+        viewBox="0 0 24 24"
+        fill="none"
+      >
+        <path fill-rule="evenodd" clip-rule="evenodd" d="M9.07513 1.1863C9.21663 1.07722 9.39144 1.01009 9.56624 1.01009C9.83261 1.01009 10.0823 1.12756 10.2405 1.33734L15.0101 7.4964V12.4136L16.4335 13.8401C16.7582 14.1673 16.7582 14.7043 16.4335 15.0316C16.1089 15.3588 15.5762 15.3588 15.2515 15.0316L13.3453 13.1016V8.07538L8.92529 2.36944V2.36105C8.64228 2.00024 8.70887 1.4716 9.07513 1.1863ZM18.976 14.4133C18.8344 14.3778 18.7003 14.3042 18.5894 14.1925L16.9163 12.5059C16.7249 12.3129 16.6416 12.0528 16.6749 11.8094V6.88385H16.6499L11.8553 0.691225C11.7282 0.529117 11.6716 0.333133 11.6803 0.140562C11.134 0.0481292 10.5726 0 10 0C4.47715 0 0 4.47715 0 10C0 15.5228 4.47715 20 10 20C13.9387 20 17.3456 17.7229 18.976 14.4133Z" fill="currentColor"></path>
+      </svg>
+    }
+    href="/integrations/keywords"
+  >
+    Build AI applications with persistent memory and comprehensive LLM observability.
+  </Card>
+  <Card
+    title="Raycast"
+    icon={
+      <svg
+        xmlns="http://www.w3.org/2000/svg"
+        width="24"
+        height="24"
+        viewBox="0 0 24 24"
+        fill="none"
+      >
+        <path
+          d="M3 12L21 12M12 3L12 21M7.5 7.5L16.5 16.5M16.5 7.5L7.5 16.5"
+          stroke="currentColor"
+          strokeWidth="2"
+          strokeLinecap="round"
+        />
+      </svg>
+    }
+    href="/integrations/raycast"
+  >
+    Mem0 Raycast extension for intelligent memory management and retrieval.
+  </Card>
   <Card
     title="Mastra"
     icon={
@@ -280,6 +395,13 @@ Here are the available integrations for Mem0:
   >
     Integrate Mem0 with Google Agent Development Kit for persistent memory across multi-agent workflows.
   </Card>
+  <Card
+    title="Flowise"
+    icon="diagram-project"
+    href="/integrations/flowise"
+  >
+    Add persistent Mem0 memory to Flowise chatflows for context-aware conversations in the low-code builder.
+  </Card>
   <Card
     title="AWS Bedrock"
     icon="cloud"

docs/integrations/agentops.mdx

@@ -0,0 +1,175 @@
+---
+title: AgentOps
+description: "Integrate Mem0 with AgentOps for automatic monitoring, analytics, and real-time tracking of memory operations."
+---
+
+Integrate [**Mem0**](https://github.com/mem0ai/mem0) with [AgentOps](https://agentops.ai), a comprehensive monitoring and analytics platform for AI agents. This integration enables automatic tracking and analysis of memory operations, providing insights into agent performance and memory usage patterns.
+
+## Overview
+
+1. Automatic monitoring of Mem0 operations and performance metrics
+2. Real-time tracking of memory add, search, and retrieval operations
+3. Analytics dashboard with memory usage patterns and insights
+4. Error tracking and debugging capabilities for memory operations
+
+## Prerequisites
+
+Before setting up Mem0 with AgentOps, ensure you have:
+
+1. Installed the required packages:
+```bash
+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?utm_source=oss&utm_medium=integration-agentops" rel="nofollow">Mem0 API Key</a> (optional, for cloud operations)
+
+## Basic Integration Example
+
+The following example demonstrates how to integrate Mem0 with AgentOps monitoring for comprehensive memory operation tracking:
+
+```python
+#Import the required libraries for local memory management with Mem0
+from mem0 import Memory, AsyncMemory
+import os
+import asyncio
+import logging
+from dotenv import load_dotenv
+import agentops
+import openai
+
+load_dotenv()
+#Set up environment variables for API keys
+os.environ["AGENTOPS_API_KEY"] = os.getenv("AGENTOPS_API_KEY")
+os.environ["OPENAI_API_KEY"] = os.getenv("OPENAI_API_KEY")
+
+#Set up the configuration for local memory storage and define sample user data. 
+local_config = {
+    "llm": {
+        "provider": "openai",
+        "config": {
+            "model": "gpt-5-mini",
+            "temperature": 0.1,
+            "max_tokens": 2000,
+        },
+    }
+}
+user_id = "alice_demo"
+agent_id = "assistant_demo"
+run_id = "session_001"
+
+sample_messages = [
+    {"role": "user", "content": "I'm planning to watch a movie tonight. Any recommendations?"},
+    {"role": "assistant", "content": "How about a thriller? They can be quite engaging."},
+    {"role": "user", "content": "I'm not a big fan of thriller movies but I love sci-fi movies."},
+    {
+        "role": "assistant",
+        "content": "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future.",
+    },
+]
+
+sample_preferences = [
+    "I prefer dark roast coffee over light roast",
+    "I exercise every morning at 6 AM",
+    "I'm vegetarian and avoid all meat products",
+    "I love reading science fiction novels",
+    "I work in software engineering",
+]
+
+#This function demonstrates sequential memory operations using the synchronous Memory class
+def demonstrate_sync_memory(local_config, sample_messages, sample_preferences, user_id):
+    """
+    Demonstrate synchronous Memory class operations.
+    """
+
+    agentops.start_trace("mem0_memory_example", tags=["mem0_memory_example"])
+    try:
+        
+        memory = Memory.from_config(local_config)
+
+        result = memory.add(
+            sample_messages, user_id=user_id, metadata={"category": "movie_preferences", "session": "demo"}
+        )
+
+        for i, preference in enumerate(sample_preferences):
+            result = memory.add(preference, user_id=user_id, metadata={"type": "preference", "index": i})
+       
+        search_queries = [
+            "What movies does the user like?",
+            "What are the user's food preferences?",
+            "When does the user exercise?",
+        ]
+
+        for query in search_queries:
+            results = memory.search(query, filters={"user_id": user_id})
+        
+            if results and "results" in results:
+                for j, result in enumerate(results['results']): 
+                    print(f"Result {j+1}: {result.get('memory', 'N/A')}")
+            else:
+                print("No results found")
+
+        all_memories = memory.get_all(filters={"user_id": user_id})
+        if all_memories and "results" in all_memories:
+            print(f"Total memories: {len(all_memories['results'])}")
+
+        delete_all_result = memory.delete_all(user_id=user_id)
+        print(f"Delete all result: {delete_all_result}")
+
+        agentops.end_trace(end_state="success")
+    except Exception as e:
+        agentops.end_trace(end_state="error")
+
+# Execute sync demonstrations
+demonstrate_sync_memory(local_config, sample_messages, sample_preferences, user_id)
+
+```
+
+For detailed information on this integration, refer to the official [Agentops Mem0 integration documentation](https://docs.agentops.ai/v2/integrations/mem0).
+
+
+## Key Features
+
+### 1. Automatic Operation Tracking
+
+AgentOps automatically monitors all Mem0 operations:
+
+- **Memory Operations**: Track add, search, get_all, delete operations and much more
+- **Performance Metrics**: Monitor response times and success rates
+- **Error Tracking**: Capture and analyze operation failures
+
+### 2. Real-time Analytics Dashboard
+
+Access comprehensive analytics through the AgentOps dashboard:
+
+- **Usage Patterns**: Visualize memory usage trends over time
+- **User Behavior**: Analyze how different users interact with memory
+- **Performance Insights**: Identify bottlenecks and optimization opportunities
+
+### 3. Session Management
+
+Organize your monitoring with structured sessions:
+
+- **Session Tracking**: Group related operations into logical sessions
+- **Success/Failure Rates**: Track session outcomes for reliability monitoring
+- **Custom Metadata**: Add context to sessions for better analysis
+
+## Best Practices
+
+1. **Initialize Early**: Always initialize AgentOps before importing Mem0 classes
+2. **Session Management**: Use meaningful session names and end sessions appropriately
+3. **Error Handling**: Wrap operations in try-catch blocks and report failures
+4. **Tagging**: Use tags to organize different types of memory operations
+5. **Environment Separation**: Use different projects or tags for dev/staging/prod
+
+<CardGroup cols={2}>
+  <Card title="CrewAI Integration" icon="users" href="/integrations/crewai">
+    Monitor multi-agent CrewAI systems
+  </Card>
+  <Card title="LangChain Integration" icon="link" href="/integrations/langchain">
+    Track LangChain agent performance
+  </Card>
+</CardGroup>
+

docs/integrations/agno.mdx

@@ -0,0 +1,207 @@
+---
+title: Agno
+description: "Add persistent multimodal memory to Agno-based agents using Mem0 for text and image interactions."
+---
+
+This integration of [**Mem0**](https://github.com/mem0ai/mem0) with [Agno](https://github.com/agno-agi/agno) enables persistent, multimodal memory for Agno-based agents - improving personalization, context awareness, and continuity across conversations.
+
+## Overview
+
+1. Store and retrieve memories from Mem0 within Agno agents
+2. Support for multimodal interactions (text and images)
+3. Semantic search for relevant past conversations
+4. Personalized responses based on user history
+5. One-line memory integration via `Mem0Tools`
+
+## Prerequisites
+
+Before setting up Mem0 with Agno, ensure you have:
+
+1. Installed the required packages:
+```bash
+pip install agno mem0ai python-dotenv
+```
+
+2. Valid API keys:
+   - <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`)
+
+The simplest way to integrate Mem0 with Agno Agents is to use Mem0 as a tool using built-in `Mem0Tools`:
+
+```python
+from agno.agent import Agent
+from agno.models.openai import OpenAIChat
+from agno.tools.mem0 import Mem0Tools
+
+agent = Agent(
+    name="Memory Agent",
+    model=OpenAIChat(id="gpt-5-mini"),
+    tools=[Mem0Tools()],
+    description="An assistant that remembers and personalizes using Mem0 memory."
+)
+```
+
+This enables memory functionality out of the box:
+
+- **Persistent memory writing**: `Mem0Tools` uses `MemoryClient.add(...)` to store messages from user-agent interactions, including optional metadata such as user ID or session.
+- **Contextual memory search**: Compatible queries use `MemoryClient.search(...)` to retrieve relevant past messages, improving contextual understanding.
+- **Multimodal support**: Both text and image inputs are supported, allowing richer memory records.
+
+> `Mem0Tools` uses the `MemoryClient` under the hood and requires no additional setup. You can customize its behavior by modifying your tools list or extending it in code.
+
+## Full Manual Example
+
+> Note: Mem0 can also be used with Agno Agents as a separate memory layer.
+
+The following example demonstrates how to create an Agno agent with Mem0 memory integration, including support for image processing:
+
+```python
+import base64
+from pathlib import Path
+from typing import Optional
+
+from agno.agent import Agent
+from agno.media import Image
+from agno.models.openai import OpenAIChat
+from mem0 import MemoryClient
+
+# Initialize the Mem0 client
+client = MemoryClient()
+
+# Define the agent
+agent = Agent(
+    name="Personal Agent",
+    model=OpenAIChat(id="gpt-4"),
+    description="You are a helpful personal agent that helps me with day to day activities."
+                "You can process both text and images.",
+    markdown=True
+)
+
+
+def chat_user(
+    user_input: Optional[str] = None,
+    user_id: str = "alex",
+    image_path: Optional[str] = None
+) -> str:
+    """
+    Handle user input with memory integration, supporting both text and images.
+
+    Args:
+        user_input: The user's text input
+        user_id: Unique identifier for the user
+        image_path: Path to an image file if provided
+
+    Returns:
+        The agent's response as a string
+    """
+    if image_path:
+        # Convert image to base64
+        with open(image_path, "rb") as image_file:
+            base64_image = base64.b64encode(image_file.read()).decode("utf-8")
+
+        # Create message objects for text and image
+        messages = []
+
+        if user_input:
+            messages.append({
+                "role": "user",
+                "content": user_input
+            })
+
+        messages.append({
+            "role": "user",
+            "content": {
+                "type": "image_url",
+                "image_url": {
+                    "url": f"data:image/jpeg;base64,{base64_image}"
+                }
+            }
+        })
+
+        # Store messages in memory
+        client.add(messages, user_id=user_id)
+        print("✅ Image and text stored in memory.")
+
+    if user_input:
+        # Search for relevant memories
+        memories = client.search(user_input, filters={"user_id": user_id})
+        memory_context = "\n".join(f"- {m['memory']}" for m in memories['results'])
+
+        # Construct the prompt
+        prompt = f"""
+You are a helpful personal assistant who helps users with their day-to-day activities and keeps track of everything.
+
+Your task is to:
+1. Analyze the given image (if present) and extract meaningful details to answer the user's question.
+2. Use your past memory of the user to personalize your answer.
+3. Combine the image content and memory to generate a helpful, context-aware response.
+
+Here is what I remember about the user:
+{memory_context}
+
+User question:
+{user_input}
+"""
+        # Get response from agent
+        if image_path:
+            response = agent.run(prompt, images=[Image(filepath=Path(image_path))])
+        else:
+            response = agent.run(prompt)
+
+        # Store the interaction in memory
+        interaction_message = [{"role": "user", "content": f"User: {user_input}\nAssistant: {response.content}"}]
+        client.add(interaction_message, user_id=user_id)
+        return response.content
+
+    return "No user input or image provided."
+
+
+# Example Usage
+if __name__ == "__main__":
+    response = chat_user(
+        "I like to travel and my favorite destination is London",
+        image_path="travel_items.jpeg",
+        user_id="alex"
+    )
+    print(response)
+```
+
+## Key Features
+
+### 1. Multimodal Memory Storage
+
+The integration supports storing both text and image data:
+
+- **Text Storage**: Conversation history is saved in a structured format
+- **Image Analysis**: Agents can analyze images and store visual information
+- **Combined Context**: Memory retrieval combines both text and visual data
+
+### 2. Personalized Agent Responses
+
+Improve your agent's context awareness:
+
+- **Memory Retrieval**: Semantic search finds relevant past interactions
+- **User Preferences**: Personalize responses based on stored user information
+- **Continuity**: Maintain conversation threads across multiple sessions
+
+### 3. Flexible Configuration
+
+Customize the integration to your needs:
+
+- **Use `Mem0Tools()`** for drop-in memory support
+- **Use `MemoryClient` directly** for advanced control
+- **User Identification**: Organize memories by user ID
+- **Memory Search**: Configure search relevance and result count
+- **Memory Formatting**: Support for various OpenAI message formats
+
+<CardGroup cols={2}>
+  <Card title="OpenAI Agents SDK" icon="cube" href="/integrations/openai-agents-sdk">
+    Build agents with OpenAI SDK and Mem0
+  </Card>
+  <Card title="Mastra Integration" icon="star" href="/integrations/mastra">
+    Create intelligent agents with Mastra framework
+  </Card>
+</CardGroup>
+

docs/integrations/autogen.mdx

@@ -0,0 +1,142 @@
+---
+title: AutoGen
+description: "Build conversational AI agents with AutoGen and Mem0 for context-aware, personalized interactions."
+---
+
+Build conversational AI agents with memory capabilities. This integration combines AutoGen for creating AI agents with Mem0 for memory management, enabling context-aware and personalized interactions.
+
+## Overview
+
+This guide demonstrates creating a conversational AI system with memory. We'll build a customer service bot that can recall previous interactions and provide personalized responses.
+
+## Setup and Configuration
+
+Install necessary libraries:
+
+```bash
+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?utm_source=oss&utm_medium=integration-autogen" rel="nofollow">Mem0 Platform</a>.</Note>
+
+```python
+import os
+from autogen import ConversableAgent
+from mem0 import MemoryClient
+from openai import OpenAI
+from dotenv import load_dotenv
+
+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?utm_source=oss&utm_medium=integration-autogen
+USER_ID = "alice"
+
+# Set up OpenAI API key
+OPENAI_API_KEY = os.environ.get('OPENAI_API_KEY')
+# os.environ['MEM0_API_KEY'] = MEM0_API_KEY
+
+# Initialize Mem0 and AutoGen agents
+memory_client = MemoryClient()
+agent = ConversableAgent(
+    "chatbot",
+    llm_config={"config_list": [{"model": "gpt-4", "api_key": OPENAI_API_KEY}]},
+    code_execution_config=False,
+    human_input_mode="NEVER",
+)
+```
+
+## Storing Conversations in Memory
+
+Add conversation history to Mem0 for future reference:
+
+```python
+conversation = [
+    {"role": "assistant", "content": "Hi, I'm Best Buy's chatbot! How can I help you?"},
+    {"role": "user", "content": "I'm seeing horizontal lines on my TV."},
+    {"role": "assistant", "content": "I'm sorry to hear that. Can you provide your TV model?"},
+    {"role": "user", "content": "It's a Sony - 77\" Class BRAVIA XR A80K OLED 4K UHD Smart Google TV"},
+    {"role": "assistant", "content": "Thank you for the information. Let's troubleshoot this issue..."}
+]
+
+memory_client.add(messages=conversation, user_id=USER_ID)
+print("Conversation added to memory.")
+```
+
+## Retrieving and Using Memory
+
+Create a function to get context-aware responses based on user's question and previous interactions:
+
+```python
+def get_context_aware_response(question):
+    relevant_memories = memory_client.search(question, filters={"user_id": USER_ID})
+    context = "\n".join([m["memory"] for m in relevant_memories.get('results', [])])
+
+    prompt = f"""Answer the user question considering the previous interactions:
+    Previous interactions:
+    {context}
+
+    Question: {question}
+    """
+
+    reply = agent.generate_reply(messages=[{"content": prompt, "role": "user"}])
+    return reply
+
+# Example usage
+question = "What was the issue with my TV?"
+answer = get_context_aware_response(question)
+print("Context-aware answer:", answer)
+```
+
+## Multi-Agent Conversation
+
+For more complex scenarios, you can create multiple agents:
+
+```python
+manager = ConversableAgent(
+    "manager",
+    system_message="You are a manager who helps in resolving complex customer issues.",
+    llm_config={"config_list": [{"model": "gpt-4", "api_key": OPENAI_API_KEY}]},
+    human_input_mode="NEVER"
+)
+
+def escalate_to_manager(question):
+    relevant_memories = memory_client.search(question, filters={"user_id": USER_ID})
+    context = "\n".join([m["memory"] for m in relevant_memories.get('results', [])])
+
+    prompt = f"""
+    Context from previous interactions:
+    {context}
+
+    Customer question: {question}
+
+    As a manager, how would you address this issue?
+    """
+
+    manager_response = manager.generate_reply(messages=[{"content": prompt, "role": "user"}])
+    return manager_response
+
+# Example usage
+complex_question = "I'm not satisfied with the troubleshooting steps. What else can be done?"
+manager_answer = escalate_to_manager(complex_question)
+print("Manager's response:", manager_answer)
+```
+
+## Conclusion
+
+By integrating AutoGen with Mem0, you've created a conversational AI system with memory capabilities. This example demonstrates a customer service bot that can recall previous interactions and provide context-aware responses, with the ability to escalate complex issues to a manager agent.
+
+This integration enables the creation of more intelligent and personalized AI agents for various applications, such as customer support, virtual assistants, and interactive chatbots.
+
+<CardGroup cols={2}>
+  <Card title="CrewAI Integration" icon="users" href="/integrations/crewai">
+    Build multi-agent systems with CrewAI and Mem0
+  </Card>
+  <Card title="LangGraph Integration" icon="diagram-project" href="/integrations/langgraph">
+    Create stateful workflows with LangGraph
+  </Card>
+</CardGroup>
+

docs/integrations/chatdev.mdx

@@ -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
 
@@ -237,7 +237,7 @@ By adding Mem0 as a memory store in ChatDev, your multi-agent workflows gain per
   <Card title="CrewAI Integration" icon="users" href="/integrations/crewai">
     Build multi-agent systems with CrewAI and Mem0
   </Card>
-  <Card title="OpenAI Agents SDK" icon="robot" href="/integrations/openai-agents-sdk">
-    Build conversational agents with OpenAI Agents SDK and Mem0
+  <Card title="AutoGen Integration" icon="robot" href="/integrations/autogen">
+    Build conversational agents with AutoGen and Mem0
   </Card>
 </CardGroup>

docs/integrations/claude-code.mdx

@@ -17,8 +17,8 @@ Add persistent memory to [**Claude Code**](https://docs.anthropic.com/en/docs/cl
 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
 
@@ -32,12 +32,19 @@ export MEM0_API_KEY="m0-your-api-key"
 
 ### Option A — Plugin Marketplace (Recommended)
 
-Install the full plugin including MCP server, lifecycle hooks, and SDK skill:
+Install the full plugin including MCP server, lifecycle hooks, and SDK skill.
 
-```
-/plugin marketplace add mem0ai/mem0
-/plugin install mem0@mem0-plugins
-```
+1. Add the Mem0 marketplace:
+
+   ```
+   /plugin marketplace add mem0ai/mem0
+   ```
+
+2. Install the plugin:
+
+   ```
+   /plugin install mem0@mem0-plugins
+   ```
 
 **Claude Cowork desktop app:** Open the Cowork tab, click **Customize** in the sidebar, click **Browse plugins**, and install Mem0.
 

docs/integrations/codex.mdx

@@ -17,8 +17,8 @@ Add persistent memory to [**OpenAI Codex**](https://openai.com/index/codex/) wit
 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
 
@@ -30,91 +30,100 @@ export MEM0_API_KEY="m0-your-api-key"
 
 ## Installation
 
-### Option A — Repo Marketplace (Recommended for Teams)
+### Option A — Direct MCP (Recommended)
 
-Add a `.agents/plugins/marketplace.json` to your repository root:
+The fastest way to connect Codex to Mem0 — no downloads, no marketplace. Codex reads MCP servers from `~/.codex/config.toml` as TOML. Add:
 
-```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"
-    }
-  ]
-}
+```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`:
+### Option B — Sideload the Plugin (Advanced)
 
-```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"
-    }
-  ]
-}
+For the full plugin experience — MCP server **plus** the Mem0 SDK skill, memory protocol skill, and opt-in lifecycle hooks — sideload the plugin from a local clone. The Mem0 repo already ships a marketplace manifest at [`.agents/plugins/marketplace.json`](https://github.com/mem0ai/mem0/blob/main/.agents/plugins/marketplace.json), so there's no JSON to author by hand. This follows the Codex [build-plugins](https://developers.openai.com/codex/plugins/build) local-testing workflow.
+
+<Info>
+  Don't combine Option B with Option A. The plugin manifest declares its MCP server via [`.codex-mcp.json`](https://github.com/mem0ai/mem0/blob/main/mem0-plugin/.codex-mcp.json), so Codex auto-registers the `mem0` MCP server when the plugin loads. Adding the same `[mcp_servers.mem0]` block to `~/.codex/config.toml` will create a duplicate registration.
+</Info>
+
+**Step 1.** Clone the Mem0 repository anywhere on disk:
+
+```bash
+git clone https://github.com/mem0ai/mem0.git ~/codex-plugins/mem0-source
 ```
 
-### Option C — Manual MCP Configuration
+**Step 2.** Register the bundled marketplace with Codex's CLI:
 
-Add to your Codex MCP config:
-
-```json
-{
-  "mcpServers": {
-    "mem0": {
-      "type": "http",
-      "url": "https://mcp.mem0.ai/mcp/",
-      "headers": {
-        "Authorization": "Token ${MEM0_API_KEY}"
-      }
-    }
-  }
-}
+```bash
+codex plugin marketplace add ~/codex-plugins/mem0-source
 ```
 
+This points Codex at the repo's `.agents/plugins/marketplace.json`. The bundled file uses `path: "./mem0-plugin"`, which Codex resolves relative to the clone root.
+
+<Info>
+  **Why we recommend this over hand-authoring `~/.agents/plugins/marketplace.json`:** Codex requires `source.path` in any marketplace manifest to be **relative** (starting with `./`) and **inside the marketplace root**. The repo's bundled manifest already satisfies this — the marketplace root is the clone directory, and `mem0-plugin/` lives inside it. With a personal `~/.agents/plugins/marketplace.json`, the root is `~/` and the clone has to live under `~/` too. The CLI form sidesteps that constraint.
+</Info>
+
+**Step 3.** Restart Codex, run `/plugins`, browse the `Mem0 Plugins` marketplace, and install **Mem0**.
+
+**Step 4 (optional) — enable lifecycle hooks.** Codex doesn't auto-wire hooks from plugin manifests; it only reads them from `~/.codex/hooks.json` (or `<repo>/.codex/hooks.json`). Run the bundled installer once to merge the Mem0 entries into your global hooks file:
+
+```bash
+python3 ~/codex-plugins/mem0-source/mem0-plugin/scripts/install_codex_hooks.py
+```
+
+Then enable the hooks feature flag in `~/.codex/config.toml`:
+
+```toml
+[features]
+codex_hooks = true
+```
+
+Restart Codex. The installer registers three hooks pointing at scripts inside your clone:
+
+| Event | Behavior |
+|-------|----------|
+| `SessionStart` | Loads prior memories as bootstrap context |
+| `UserPromptSubmit` | Injects relevant memories before each prompt |
+| `Stop` | Reminds the agent to persist learnings at turn end |
+
+Re-running the installer is idempotent. To remove the hooks: `python3 ~/codex-plugins/mem0-source/mem0-plugin/scripts/install_codex_hooks.py --uninstall`.
+
+<Warning>
+  The hooks file stores absolute paths into your clone (e.g. `~/codex-plugins/mem0-source/mem0-plugin/scripts/...`). If you move or delete the clone, the hooks will break silently — re-run the installer from the new location, or run `--uninstall` first.
+</Warning>
+
+### Managing the Plugin
+
+Codex provides CLI commands for managing marketplaces after install:
+
+```bash
+codex plugin marketplace upgrade               # pull latest plugin versions
+codex plugin marketplace remove mem0-plugins   # unregister the marketplace
+```
+
+To pull updates to the plugin source itself, `git pull` inside your clone (`~/codex-plugins/mem0-source`) and then run `codex plugin marketplace upgrade` to refresh Codex's plugin cache. Plugins are cached at `~/.codex/plugins/cache/<marketplace>/<plugin>/<version>/`.
+
 <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
 
-| Component | Plugin Install | MCP Only |
-|-----------|:--------------:|:--------:|
+| Component | Sideloaded Plugin | Direct MCP |
+|-----------|:-----------------:|:----------:|
 | MCP Server (9 memory tools) | Yes | Yes |
 | Memory Protocol Skill | Yes | No |
 | Mem0 SDK Skill | Yes | No |
+| Lifecycle Hooks (opt-in) | Yes | No |
 
 ## Available MCP Tools
 
@@ -134,7 +143,7 @@ Once installed, the following tools are available in every Codex session:
 
 ## Memory Protocol Skill
 
-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 the plugin is sideloaded, the memory protocol skill instructs the agent to:
 
 ### On Every New Task
 1. Call `search_memories` with a query related to the current task to load relevant context
@@ -199,8 +208,12 @@ You: Add WebSocket support for real-time notification delivery.
 
 - **"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
+- **Duplicate `mem0` MCP server / "tool collision" errors** — You combined Option A (Direct MCP) with Option B (sideload). The sideloaded plugin auto-registers `mem0` from `.codex-mcp.json`, so remove the `[mcp_servers.mem0]` block from `~/.codex/config.toml`.
+- **`plugin/read failed in TUI`** — Codex can't find the plugin directory the marketplace points at. If you used `codex plugin marketplace add <path>`, confirm the path is your clone root and that `<clone>/.agents/plugins/marketplace.json` exists. If you hand-authored `~/.agents/plugins/marketplace.json`, `source.path` must be relative (start with `./`), inside the marketplace root (`~/` for personal installs), and end in `mem0-plugin` — e.g. `"./codex-plugins/mem0-source/mem0-plugin"`.
+- **Plugin not found in `/plugins`** — Run `codex plugin marketplace add ~/path/to/clone` again, or confirm the marketplace was registered with `codex plugin marketplace remove mem0-plugins` then re-add.
+- **Skills not loading** — Verify the `skills` field in `plugin.json` points to a valid directory containing `SKILL.md` files.
+- **Hooks not firing** — Confirm `codex_hooks = true` is in `~/.codex/config.toml` under `[features]`, and that `~/.codex/hooks.json` contains the Mem0 entries (re-run the installer if not). Restart Codex after enabling the flag.
+- **Hooks broke after moving the clone** — The installer bakes absolute paths into `~/.codex/hooks.json` pointing at scripts inside your clone. If you moved or renamed the clone directory, run `python3 <new-clone>/mem0-plugin/scripts/install_codex_hooks.py` from the new location — the installer is idempotent and replaces the old entries.
 
 <CardGroup cols={2}>
   <Card title="Mem0 MCP Setup" icon="puzzle-piece" href="/platform/mem0-mcp">

docs/integrations/crewai.mdx

@@ -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
@@ -162,8 +162,8 @@ if __name__ == "__main__":
 By combining CrewAI with Mem0, you can create sophisticated AI systems that maintain context and provide personalized experiences while leveraging the power of autonomous agents.
 
 <CardGroup cols={2}>
-  <Card title="OpenAI Agents SDK" icon="users" href="/integrations/openai-agents-sdk">
-    Build multi-agent systems with OpenAI Agents SDK and Mem0
+  <Card title="AutoGen Integration" icon="users" href="/integrations/autogen">
+    Build multi-agent systems with AutoGen and Mem0
   </Card>
   <Card title="LangGraph Integration" icon="diagram-project" href="/integrations/langgraph">
     Create stateful agent workflows with memory

docs/integrations/cursor.mdx

@@ -17,8 +17,8 @@ Add persistent memory to [**Cursor**](https://cursor.com) with the Mem0 plugin.
 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))
 

docs/integrations/dify.mdx

@@ -0,0 +1,42 @@
+---
+title: Dify
+description: "Integrate Mem0 as a plugin in Dify AI workflows for persistent conversation storage and retrieval."
+---
+
+# Integrating Mem0 with Dify AI
+
+Mem0 brings a robust memory layer to Dify AI, empowering your AI agents with persistent conversation storage and retrieval capabilities. With Mem0, your Dify applications gain the ability to recall past interactions and maintain context, ensuring more natural and insightful conversations.
+
+---
+
+## How to Integrate Mem0 in Your Dify Workflow
+
+1. **Install the Mem0 Plugin:**  
+   Head to the [Dify Marketplace](https://marketplace.dify.ai/plugins/yevanchen/mem0) and install the Mem0 plugin. This is your first step toward adding intelligent memory to your AI applications.
+
+2. **Create or Open Your Dify Project:**  
+   Whether you're starting fresh or updating an existing project, simply create or open your Dify workspace.
+
+3. **Add the Mem0 Plugin to Your Project:**  
+   Within your project, add the Mem0 plugin. This integration connects Mem0’s memory management capabilities directly to your Dify application.
+
+4. **Configure Your Mem0 Settings:**  
+   Customize Mem0 to suit your needs—set preferences for how conversation history is stored, the search parameters, and any other context-aware features.
+
+5. **Leverage Mem0 in Your Workflow:**  
+   Use Mem0 to store every conversation turn and retrieve past interactions seamlessly. This integration ensures that your AI agents can refer back to important context, making multi-turn dialogues more effective and user-centric.
+
+---
+
+![Mem0 Dify Integration](/images/dify-mem0-integration.png)
+
+Enhance your Dify-powered AI with Mem0 and transform your conversational experiences. Start integrating intelligent memory management today and give your agents the context they need to excel!
+
+<CardGroup cols={2}>
+  <Card title="Flowise Integration" icon="share-nodes" href="/integrations/flowise">
+    Build visual AI workflows with Flowise
+  </Card>
+  <Card title="LangChain Integration" icon="link" href="/integrations/langchain">
+    Create LangChain-powered applications
+  </Card>
+</CardGroup>

docs/integrations/flowise.mdx

@@ -0,0 +1,127 @@
+---
+title: Flowise
+description: "Add persistent Mem0 memory to Flowise chatflows for context-aware conversations in the low-code builder."
+---
+
+The [**Mem0 Memory**](https://github.com/mem0ai/mem0) integration with [Flowise](https://github.com/FlowiseAI/Flowise) enables persistent memory capabilities for your AI chatflows. [Flowise](https://flowiseai.com/) is an open-source low-code tool for developers to build customized LLM orchestration flows & AI agents using a drag & drop interface.
+
+## Overview
+
+1. Provides persistent memory storage for Flowise chatflows
+2. Seamless integration with existing Flowise templates
+3. Compatible with various LLM nodes in Flowise
+4. Supports custom memory configurations
+5. Easy to set up and manage
+
+## Prerequisites
+
+Before setting up Mem0 with Flowise, ensure you have:
+
+1. [Flowise installed](https://github.com/FlowiseAI/Flowise#⚡quick-start) (NodeJS >= 18.15.0 required):
+```bash
+npm install -g flowise
+npx flowise start
+```
+
+2. Access to the Flowise UI at http://localhost:3000
+3. Basic familiarity with [Flowise's LLM orchestration](https://flowiseai.com/#features) concepts
+
+## Setup and Configuration
+
+### 1. Set Up Flowise
+
+1. Open the Flowise application and create a new canvas, or select a template from the Flowise marketplace.
+2. In this example, we use the **Conversation Chain** template.
+3. Replace the default **Buffer Memory** with **Mem0 Memory**.
+
+![Flowise Memory Integration](https://raw.githubusercontent.com/FlowiseAI/FlowiseDocs/main/en/.gitbook/assets/mem0/flowise-flow.png)
+
+### 2. Obtain Your Mem0 API Key
+
+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)
+
+### 3. Configure Mem0 Credentials
+
+1. Enter the **Mem0 API Key** in the Mem0 Credentials section.
+2. Configure additional settings as needed:
+
+```typescript
+{
+  "apiKey": "m0-xxx",
+  "userId": "user-123",  // Optional: Specify user ID
+  "projectId": "proj-xxx",  // Optional: Specify project ID
+  "orgId": "org-xxx"  // Optional: Specify organization ID
+}
+```
+
+<figure>
+  <img src="https://raw.githubusercontent.com/FlowiseAI/FlowiseDocs/main/en/.gitbook/assets/mem0/creds.png" alt="Mem0 Credentials" />
+  <figcaption>Configure API Credentials</figcaption>
+</figure>
+
+## Memory Features
+
+### 1. Basic Memory Storage
+
+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?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)
+
+### 2. Memory Retention
+
+Validate memory persistence:
+
+1. Clear the chat history in Flowise
+2. Ask a question about previously stored information
+3. Confirm that the AI remembers the context
+
+![Testing Memory Retention](https://raw.githubusercontent.com/FlowiseAI/FlowiseDocs/main/en/.gitbook/assets/mem0/flowise-chat-2.png)
+
+## Advanced Configuration
+
+### Memory Settings
+
+![Mem0 Settings](https://raw.githubusercontent.com/FlowiseAI/FlowiseDocs/main/en/.gitbook/assets/mem0/settings.png)
+
+Available settings include:
+
+1. **Search Only Mode**: Enable memory retrieval without creating new memories
+2. **Mem0 Entities**: Configure identifiers:
+   - `user_id`: Unique identifier for each user
+   - `run_id`: Specific conversation session ID
+   - `app_id`: Application identifier
+   - `agent_id`: AI agent identifier
+3. **Project ID**: Assign memories to specific projects
+4. **Organization ID**: Organize memories by organization
+
+### Platform Configuration
+
+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
+
+![Mem0 Project Settings](https://raw.githubusercontent.com/FlowiseAI/FlowiseDocs/main/en/.gitbook/assets/mem0/mem0-settings.png)
+
+## Best Practices
+
+1. **User Identification**: Use consistent `user_id` values for reliable memory retrieval
+2. **Memory Organization**: Utilize projects and organizations for better memory management
+3. **Regular Maintenance**: Monitor and clean up unused memories periodically
+
+<CardGroup cols={2}>
+  <Card title="LangChain Integration" icon="link" href="/integrations/langchain">
+    Build LangChain-powered flows with memory
+  </Card>
+  <Card title="Dify Integration" icon="blocks" href="/integrations/dify">
+    Create AI workflows with Dify platform
+  </Card>
+</CardGroup>
+

docs/integrations/google-ai-adk.mdx

@@ -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

docs/integrations/hermes.mdx

@@ -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
 

docs/integrations/keywords.mdx

@@ -0,0 +1,142 @@
+---
+title: Keywords AI
+description: "Combine Mem0 persistent memory with Keywords AI observability for tracked, cost-optimized AI applications."
+---
+
+Build AI applications with persistent memory and comprehensive LLM observability by integrating Mem0 with Keywords AI.
+
+## Overview
+
+Mem0 is a self-improving memory layer for LLM applications, enabling personalized AI experiences that save costs and delight users. Keywords AI provides complete LLM observability.
+
+Combining Mem0 with Keywords AI allows you to:
+1. Add persistent memory to your AI applications
+2. Track interactions across sessions
+3. Monitor memory usage and retrieval with Keywords AI observability
+4. Optimize token usage and reduce costs
+
+<Note>
+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
+
+Install the necessary libraries:
+
+```bash
+pip install mem0ai keywordsai-sdk
+```
+
+Set up your environment variables:
+
+```python
+import os
+
+# Set your API keys
+os.environ["MEM0_API_KEY"] = "your-mem0-api-key"
+os.environ["KEYWORDSAI_API_KEY"] = "your-keywords-api-key"
+os.environ["KEYWORDSAI_BASE_URL"] = "https://api.keywordsai.co/api/"
+```
+
+## Basic Integration Example
+
+Here's a simple example of using Mem0 with Keywords AI:
+
+```python
+from mem0 import Memory
+import os
+
+# Configuration
+api_key = os.getenv("MEM0_API_KEY")
+keywordsai_api_key = os.getenv("KEYWORDSAI_API_KEY")
+base_url = os.getenv("KEYWORDSAI_BASE_URL") # "https://api.keywordsai.co/api/"
+
+# Set up Mem0 with Keywords AI as the LLM provider
+config = {
+    "llm": {
+        "provider": "openai",
+        "config": {
+            "model": "gpt-5-mini",
+            "temperature": 0.0,
+            "api_key": keywordsai_api_key,
+            "openai_base_url": base_url,
+        },
+    }
+}
+
+# Initialize Memory
+memory = Memory.from_config(config)
+
+# Add a memory
+result = memory.add(
+    "I like to take long walks on weekends.",
+    user_id="alice",
+    metadata={"category": "hobbies"},
+)
+
+print(result)
+```
+
+## Advanced Integration with OpenAI SDK
+
+For more advanced use cases, you can integrate Keywords AI with Mem0 through the OpenAI SDK:
+
+```python
+from openai import OpenAI
+import os
+import json
+
+# Initialize client
+client = OpenAI(
+    api_key=os.environ.get("KEYWORDSAI_API_KEY"),
+    base_url=os.environ.get("KEYWORDSAI_BASE_URL"),
+)
+
+# Sample conversation messages
+messages = [
+    {"role": "user", "content": "I'm planning to watch a movie tonight. Any recommendations?"},
+    {"role": "assistant", "content": "How about thriller movies? They can be quite engaging."},
+    {"role": "user", "content": "I'm not a big fan of thriller movies but I love sci-fi movies."},
+    {"role": "assistant", "content": "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future."}
+]
+
+# Add memory and generate a response
+response = client.chat.completions.create(
+    model="openai/gpt-4.1-nano",
+    messages=messages,
+    extra_body={
+        "mem0_params": {
+            "user_id": "test_user",
+            "api_key": os.environ.get("MEM0_API_KEY"),
+            "add_memories": {
+                "messages": messages,
+            },
+        }
+    },
+)
+
+print(json.dumps(response.model_dump(), indent=4))
+```
+
+For detailed information on this integration, refer to the official [Keywords AI Mem0 integration documentation](https://docs.keywordsai.co/integration/development-frameworks/mem0).
+
+## Key Features
+
+1. **Memory Integration**: Store and retrieve relevant information from past interactions
+2. **LLM Observability**: Track memory usage and retrieval patterns with Keywords AI
+3. **Session Persistence**: Maintain context across multiple user sessions
+4. **Cost Optimization**: Reduce token usage through efficient memory retrieval
+
+## Conclusion
+
+Integrating Mem0 with Keywords AI provides a powerful combination for building AI applications with persistent memory and comprehensive observability. This integration enables more personalized user experiences while providing insights into your application's memory usage.
+
+<CardGroup cols={2}>
+  <Card title="OpenAI Agents SDK" icon="cube" href="/integrations/openai-agents-sdk">
+    Build monitored agents with OpenAI SDK
+  </Card>
+  <Card title="AgentOps Integration" icon="chart-line" href="/integrations/agentops">
+    Monitor agent performance with AgentOps
+  </Card>
+</CardGroup>
+

docs/integrations/langchain.mdx

@@ -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

docs/integrations/langgraph.mdx

@@ -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

docs/integrations/llama-index.mdx

@@ -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

docs/integrations/mastra.mdx

@@ -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

docs/integrations/openai-agents-sdk.mdx

@@ -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

docs/integrations/openclaw.mdx

@@ -1,6 +1,6 @@
 ---
 title: OpenClaw
-description: "Add long-term memory to OpenClaw agents using the Mem0 plugin with auto-recall and auto-capture support."
+description: "Add long-term memory to OpenClaw agents using the Mem0 plugin with skills-based memory extraction and recall."
 ---
 
 Add long-term memory to [OpenClaw](https://github.com/openclaw/openclaw) agents with the `@mem0/openclaw-mem0` plugin. Your agent forgets everything between sessions — this plugin fixes that by automatically watching conversations, extracting what matters, and bringing it back when relevant.
@@ -12,11 +12,12 @@ Add long-term memory to [OpenClaw](https://github.com/openclaw/openclaw) agents
 </Frame>
 
 The plugin provides:
-1. **Auto-Recall** — Before the agent responds, memories matching the current message are injected into context
-2. **Auto-Capture** — After the agent responds, the exchange is sent to Mem0 which decides what's worth keeping
-3. **Agent Tools** — Eight tools for explicit memory operations during conversations
+1. **Triage** — The agent extracts durable facts from conversations using a structured protocol with importance gates and domain overlays
+2. **Recall** — Before each turn, relevant memories are retrieved with reranking and injected into context
+3. **Dream** — Periodic memory consolidation: merges duplicates, resolves conflicts, prunes stale entries
+4. **Agent Tools** — Eight tools for explicit memory operations during conversations
 
-Both auto-recall and auto-capture 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">

docs/integrations/raycast.mdx

@@ -0,0 +1,50 @@
+---
+title: "Raycast Extension"
+description: "Mem0 Raycast extension for intelligent memory management"
+---
+
+Mem0 is a self-improving memory layer for LLM applications, enabling personalized AI experiences that save costs and delight users. This extension lets you store and retrieve text snippets using Mem0's intelligent memory system. Find Mem0 in [Raycast Store](https://www.raycast.com/dev_khant/mem0) for using it.
+
+## Getting Started
+
+**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?utm_source=oss&utm_medium=integration-raycast" rel="nofollow">app.mem0.ai</a>
+
+b. Navigate to your API Keys page
+
+c. Copy your API key
+
+d. Enter this key in the extension preferences
+
+**Basic Usage**:
+
+- Store memories and text snippets
+- Retrieve context-aware information
+- Manage persistent user preferences
+- Search through stored memories
+
+## Features
+
+**Remember Everything**: Never lose important information. Store notes, preferences, and conversations that your AI can recall later.
+
+**Smart Connections**: Automatically links related topics, helping you discover useful connections.
+
+**Cost Saver**: Spend less on AI usage by efficiently retrieving relevant information instead of regenerating responses.
+
+## How This Helps You
+
+**More Personal Experience**: Your AI remembers your preferences and past conversations, making interactions feel more natural.
+
+**Learn Your Style**: Adapts to how you work and what you like, becoming more helpful over time.
+
+**No More Repetition**: Stop explaining the same things repeatedly. Your AI remembers your context and preferences.
+
+<CardGroup cols={2}>
+  <Card title="OpenAI Agents SDK" icon="cube" href="/integrations/openai-agents-sdk">
+    Build desktop AI agents with OpenAI SDK
+  </Card>
+  <Card title="Mastra Integration" icon="star" href="/integrations/mastra">
+    Create intelligent desktop workflows
+  </Card>
+</CardGroup>

docs/integrations/vercel-ai-sdk.mdx

@@ -29,7 +29,7 @@ npm install @mem0/vercel-ai-provider
 
 ### Setting Up Mem0
 
-1. Get your **Mem0 API Key** from the <a href="https://app.mem0.ai/dashboard/api-keys" rel="nofollow">Mem0 Dashboard</a>.
+1. Get your **Mem0 API Key** from the <a href="https://app.mem0.ai/dashboard/api-keys?utm_source=oss&utm_medium=integration-vercel-ai-sdk" rel="nofollow">Mem0 Dashboard</a>.
 
 2. Initialize the Mem0 Client in your application:
 

docs/llms.txt

@@ -11,6 +11,12 @@
 - Live MCP server: https://mcp.mem0.ai (see `platform/mem0-mcp`).
 - Source repo: https://github.com/mem0ai/mem0
 
+### Don't have a Mem0 API key?
+
+Run: `mem0 init --agent --agent-caller <your-name> --json` — replace `<your-name>` with the AI agent you are (e.g. `claude-code`, `cursor`, `codex`). If you forgot to pass `--agent-caller`, run `mem0 identify <your-name>` after init to attribute the signup.
+
+This mints an evaluation key in <5 seconds — no email, no dashboard, no OTP required. Use it immediately against the Platform API or MCP server. When the human is ready, claim with `mem0 init --email <your-email>` to transfer ownership (memories preserved, same API key, no agent disruption).
+
 ## Install
 
 - Python SDK: `pip install mem0ai`
@@ -161,6 +167,7 @@ If the user is on a pre-current major (Python < 2, TS < 3, or Platform `output_f
 - [Open Source Configuration](https://docs.mem0.ai/open-source/configuration) [OSS]: Use when configuring `Memory` - LLM, embedder, vector store, graph store.
 - [Open Source Python Quickstart](https://docs.mem0.ai/open-source/python-quickstart) [OSS]: Use for the first self-hosted Python integration.
 - [Open Source Node.js Quickstart](https://docs.mem0.ai/open-source/node-quickstart) [OSS]: Use for the first self-hosted Node integration.
+- [Self-Hosted Setup](https://docs.mem0.ai/open-source/setup) [OSS]: Use when standing up the bundled REST server and dashboard via Docker Compose, including auth, API keys, and the setup wizard.
 
 ## Core Concepts
 
@@ -184,8 +191,10 @@ If the user is on a pre-current major (Python < 2, TS < 3, or Platform `output_f
 ### Features - Advanced Retrieval
 - [Advanced Retrieval](https://docs.mem0.ai/platform/features/advanced-retrieval) [Platform]: Use when the user needs keyword search, reranking, or hybrid retrieval.
 - [Criteria-Based Retrieval](https://docs.mem0.ai/platform/features/criteria-retrieval) [Platform]: Use when targeting memories by custom criteria, not just semantic similarity.
+- [Temporal Reasoning](https://docs.mem0.ai/platform/features/temporal-reasoning) [Platform]: Use when time-aware searches like last week, upcoming, or right now need better result ordering.
 - [Contextual Add](https://docs.mem0.ai/platform/features/contextual-add) [Platform]: Use when `add()` should consider the surrounding conversation, not just the latest turn.
 - [Custom Instructions](https://docs.mem0.ai/platform/features/custom-instructions) [Platform]: Use when tailoring what Mem0 extracts and stores on Platform.
+- [Memory Decay](https://docs.mem0.ai/platform/features/memory-decay) [Platform]: Use when search results should boost recently-reinforced memories and dampen stale ones — opt-in per project, search-time only, never filters candidates out.
 - [Advanced Memory Operations](https://docs.mem0.ai/platform/advanced-memory-operations) [Platform]: Use when basic CRUD is not enough - batch ops, complex filters, workflows.
 
 ### Features - Data Management
@@ -231,6 +240,8 @@ If the user is on a pre-current major (Python < 2, TS < 3, or Platform `output_f
 - [LangChain Tools](https://docs.mem0.ai/integrations/langchain-tools) [Both]: Use when Mem0 should be exposed as a LangChain tool.
 - [LlamaIndex](https://docs.mem0.ai/integrations/llama-index) [Both]: Use when layering memory on a LlamaIndex RAG app.
 - [CrewAI](https://docs.mem0.ai/integrations/crewai) [Both]: Use when building CrewAI multi-agent systems.
+- [AutoGen](https://docs.mem0.ai/integrations/autogen) [Both]: Use when the user is on Microsoft AutoGen.
+- [Agno](https://docs.mem0.ai/integrations/agno) [Both]: Use when the user is on Agno.
 - [Camel AI](https://docs.mem0.ai/integrations/camel-ai) [Both]: Use when the user is on Camel AI.
 - [ChatDev](https://docs.mem0.ai/integrations/chatdev) [Both]: Use when the user is on ChatDev.
 - [Hermes](https://docs.mem0.ai/integrations/hermes) [Both]: Use when the user is on Hermes.
@@ -253,6 +264,12 @@ If the user is on a pre-current major (Python < 2, TS < 3, or Platform `output_f
 ### Cloud & Infrastructure
 - [AWS Bedrock](https://docs.mem0.ai/integrations/aws-bedrock) [Both]: Use when the user is on AWS Bedrock managed AI services.
 
+### Developer Tools
+- [Dify](https://docs.mem0.ai/integrations/dify) [Both]: Use when the user is on Dify LLMOps.
+- [Flowise](https://docs.mem0.ai/integrations/flowise) [Both]: Use when the user is on Flowise no-code.
+- [AgentOps](https://docs.mem0.ai/integrations/agentops) [Both]: Use when tracking agent observability with memory metadata.
+- [Keywords AI](https://docs.mem0.ai/integrations/keywords) [Both]: Use when monitoring with Keywords AI.
+- [Raycast](https://docs.mem0.ai/integrations/raycast) [Both]: Use when the user wants quick memory access via Raycast.
 
 ## Cookbooks