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Author SHA1 Message Date
Mgeeeek 805b466887 style(cli-python): ruff format agent_rush_cmd.py 2026-05-20 18:49:10 +05:30
Mgeeeek 284547e2ab ci: run mem0/embedchain build jobs on cli/** and docs/** PRs
The required status checks build_mem0 (3.10/3.11) and build_embedchain
live in ci.yml, which was path-filtered to mem0/tests/embedchain only.
PRs that touch only cli/** or docs/** could never satisfy branch
protection because the workflow never triggered.

Adds cli/**, docs/**, and .github/workflows/** to the pull_request
paths so required checks actually run on CLI and docs PRs.
2026-05-20 18:45:24 +05:30
Mgeeeek 87a492c137 chore: drop Mintlify auto-deploy workflow
Avoiding a deploy-hook secret on a public repo. Mintlify rebuilds
will continue via the GitHub App's path-detection (with the existing
"chore: trigger Mintlify redeploy" workaround when needed).
2026-05-20 18:43:01 +05:30
Mgeeeek 859c674956 chore(release): cli 0.2.7 + docs + Mintlify auto-deploy workflow
Wraps up the AGENTRUSH CLI release across both clients.

Lint:
- Node Biome: collapse multi-line printError() in whoami.ts
- Python ruff: drop unused BRAND_COLOR import; replace EN DASH with
  HYPHEN-MINUS in app.py docstring

Release:
- Bump @mem0/cli and mem0-cli from 0.2.6 → 0.2.7 (patch)
- Add CHANGELOG.md (Keep a Changelog format) to both CLIs, seeded
  with the 0.2.7 entry covering whoami, agent-rush <add|search>, the
  PII safety prompt, and the new agent_rush.acknowledged_at config field

Docs:
- docs/platform/cli.mdx: new sections for `mem0 whoami` and
  `mem0 agent-rush <add|search>` with rule table, error-code hints,
  the launch copy-paste block, and the public-memory warning
- llms.txt coverage already in sync (no new .mdx files)

Mintlify auto-deploy:
- New .github/workflows/mintlify-deploy.yml — pings the deploy hook on
  every push to main, bypassing the GitHub App's path-detection bug
  that caused docs.mem0.ai drift (the recurring "trigger redeploy"
  commits). Workflow is a clean no-op until MINTLIFY_DEPLOY_HOOK_URL
  repo secret is configured in dashboard.
2026-05-20 18:36:57 +05:30
Mgeeeek 4ca9d13c47 feat(cli): warn about public AGENTRUSH memories before first add
Adds a one-time PII warning shown before the first `mem0 agent-rush
add`. Persists acknowledgment in config so we never ask the same
machine twice.

Interactive (TTY):
  ⚠️  AGENTRUSH memories are PUBLIC — visible to any other player.
     Do not include real names, emails, secrets, work content, or PII.
     Continue? [y/N]
  → on "y" the timestamp lands in `agent_rush.acknowledged_at`.
  → anything else aborts with no add.

Non-interactive (agent invocation, no TTY): the warning prints to
stderr (visible in the agent transcript so the human notices) and
the add proceeds. Agents can't answer y/N; blocking them would defeat
the entire launch flow. Ack is intentionally not persisted in this
path so a later human run still sees the prompt.

Mirrored across Node + Python CLIs with matching JSON schema:
  config.json adds `agent_rush.acknowledged_at: ""` (ISO timestamp).
2026-05-20 18:04:24 +05:30
Mgeeeek abc57323c2 feat(cli): add mem0 whoami + mem0 agent-rush subcommands
Mirrors implementation across Node (TypeScript) and Python CLIs.

mem0 whoami:
  Prints the agent's default_user_id from local config — the AGENTRUSH
  leaderboard identifier. Used by players to cross-verify their row.

mem0 agent-rush <add|search>:
  Wraps the platform's /v1/agent-rush/{memories/, memories/search/}
  endpoints. Project routing is implicit (server-resolved); no flags.
  Pretty-prints platform error codes into actionable hints (e.g.
  agentrush_search_first → "Run 3 'mem0 agent-rush search' commands
  before adding.").

Adds X-Mem0-Mode: agent-rush header for telemetry. Reuses existing
agent-mode API key from config; surfaces a graceful error if config
is missing or the key was created outside agent-mode.

Platform PR: mem0ai/platform#2804
2026-05-20 03:35:04 +05:30
Mragank Shekhar 843ab82905 chore: trigger Mintlify redeploy for #5152 docs (#5185) 2026-05-18 16:22:48 +05:30
youneshima 79793b0d2e docs: link platform migration guide from readme (#5171) 2026-05-16 19:13:47 -07:00
Mragank Shekhar 5f7ace2aef docs: promote "Sign up as an agent" + drop plugin-sync prose (#5152) 2026-05-16 21:52:34 +05:30
rudrajmehta-mem0 219b1a6f3d docs(faqs): add self-serve account deletion FAQ (#5158)
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-16 03:16:42 +05:30
youneshima 57c8468ce6 docs: add hosted Qdrant migration script (#5156) 2026-05-16 01:46:20 +05:30
Chaithanya Kumar ddee5f8671 feat(ts): expose latestOnly on hosted memory reads (#5153) 2026-05-15 23:15:51 +05:30
Deshraj Yadav fbce5fab14 docs: remove unverified SOC2/GDPR compliance claims (#5150) 2026-05-14 23:22:37 -07:00
Mragank Shekhar 6a1597c6fb fix(plugin): drop API-key-derived user_id, restore $USER fallback (#5147) 2026-05-15 02:37:55 +05:30
Mragank Shekhar c9e8482a35 fix(docs): Mintlify <5s parse error + add Agent Mode to /platform/cli (#5145) 2026-05-14 21:49:08 +05:30
Mragank Shekhar e602923751 feat(cli): Agent Mode bootstrap + claim flow (Python + Node) (#5123) 2026-05-14 20:35:25 +05:30
Agam Pandey 70bc9e51d5 docs(readme): update LongMemEval benchmark to 94.8 and add Temporal Reasoning (#5131) 2026-05-13 14:31:15 +05:30
Agam Pandey 0107fd53b8 feat: add temporal reasoning cookbook and docs (#5061) 2026-05-13 01:59:38 +05:30
Mragank Shekhar 54a03cc721 chore(plugin): bump mem0 plugin to v0.1.2 (#5094) 2026-05-09 20:56:34 +05:30
Mragank Shekhar e95de4ca50 fix(plugin): hook cleanup + identity + compact-summary flow (#5076) 2026-05-09 19:19:30 +05:30
youneshima a623cfaf76 Oss qdrant hosted memories to platform migration (#5080) 2026-05-08 08:04:09 +05:30
Chaithanya Kumar 92491c00c2 docs(memory-decay): use SDK calls in code samples (#5079)
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-08 01:53:55 +05:30
Mragank Shekhar 9043fbf61e chore(release): bump mem0ai to 2.0.2 (py) and 3.0.3 (ts) (#5078) 2026-05-08 01:27:23 +05:30
Chaithanya Kumar c90cbc75a2 docs: memory decay v0.5 — platform feature page + API reference (#5056)
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-08 01:21:33 +05:30
Gabriel Stein 58304fc939 refactor(plugin): hand mem0 search decisions to the agent (#4992)
Co-authored-by: Mgeeeek <ms8939@bennett.edu.in>
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-07 20:41:39 +05:30
Chaithanya Kumar 397f3414ee feat(sdk): expose decay on project.update (Python + TypeScript) (#5062)
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-06 15:33:32 +05:30
Gabriel Stein a734e057cf fix (telemetry): stitch oss and platform telemetry identities for python and typescript sdk
Co-authored-by: Younes Slaoui <younes.slaoui@mem0.ai>
2026-05-05 13:48:21 -07:00
Saket Aryan 0fdaa29b4a feat(skills): add mem0-integrate + mem0-test-integration pipeline skills (#4961) 2026-05-05 18:52:22 +05:30
Kartik 6d3486ca56 docs: update changelog for v1.0.11 with new features, improvements, fixes, and dependency updates (#5022) 2026-04-29 22:45:26 +05:30
Kartik ebb9bb2b15 fix: adding skills config and updating the plugin the config (#4958) 2026-04-29 22:19:40 +05:30
Kabir Kohli 594b4e65d6 fix(openclaw): bump protobufjs to >=7.5.5 (GHSA-xq3m-2v4x-88gg) (#5012) 2026-04-29 10:43:19 +05:30
Harsh Vardhan Gupta 1b95c99db4 fix: sql injection, prompt injection (#4997)
Co-authored-by: kartik-mem0 <kartik.labhshetwar@mem0.ai>
2026-04-29 00:51:16 +05:30
Gabriel Stein b66cf0f272 docs(mcp): document list_events and get_event_status tools (#4989) 2026-04-29 00:32:48 +05:30
Gabriel Stein 72dca1cdf5 docs(codex): fix broken install instructions, lead with direct MCP (#4951) 2026-04-29 00:32:27 +05:30
Zeger Hoogeboom ece7ff6b84 (TS) Fix PGVector implementation, where vector distance was inverted. (#4944) 2026-04-28 00:39:48 +05:30
143 changed files with 10493 additions and 548 deletions
+1 -1
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@@ -12,7 +12,7 @@
"name": "mem0",
"source": "./mem0-plugin",
"description": "Mem0 memory layer for AI applications. Add persistent memory, personalization, and semantic search to Claude workflows.",
"version": "0.1.1"
"version": "0.1.3"
}
]
}
+3
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@@ -15,6 +15,9 @@ on:
- 'tests/**'
- 'embedchain/**'
- 'pyproject.toml'
- 'cli/**'
- 'docs/**'
- '.github/workflows/**'
jobs:
changelog_check:
+4 -2
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@@ -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
+45 -2
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@@ -47,7 +47,7 @@
| Benchmark | Old | New | Tokens | Latency p50 |
| --- | --- | --- | --- | --- |
| **LoCoMo** | 71.4 | **91.6** | 7.0K | 0.88s |
| **LongMemEval** | 67.8 | **93.4** | 6.8K | 1.09s |
| **LongMemEval** | 67.8 | **94.8** | 6.8K | 1.09s |
| **BEAM (1M)** | — | **64.1** | 6.7K | 1.00s |
| **BEAM (10M)** | — | **48.6** | 6.9K | 1.05s |
@@ -58,12 +58,13 @@ All benchmarks run on the same production-representative model stack. Single-pas
- **Agent-generated facts are first-class** -- when an agent confirms an action, that information is now stored with equal weight.
- **Entity linking** -- entities are extracted, embedded, and linked across memories for retrieval boosting.
- **Multi-signal retrieval** -- semantic, BM25 keyword, and entity matching scored in parallel and fused.
- **Temporal Reasoning** -- time-aware retrieval that ranks the right dated instance for queries about current state, past events, and upcoming plans.
See the [migration guide](https://docs.mem0.ai/migration/oss-v2-to-v3) for upgrade instructions. The [evaluation framework](https://github.com/mem0ai/memory-benchmarks) is open-sourced so anyone can reproduce the numbers.
## Research Highlights
- **91.6 on LoCoMo** -- +20 points over the previous algorithm
- **93.4 on LongMemEval** -- +26 points, with +53.6 on assistant memory recall
- **94.8 on LongMemEval** -- +27 points, with +53.6 on assistant memory recall
- **64.1 on BEAM (1M)** -- production-scale memory evaluation at 1M tokens
- [Read the full paper](https://mem0.ai/research)
@@ -85,6 +86,26 @@ See the [migration guide](https://docs.mem0.ai/migration/oss-v2-to-v3) for upgra
## 🚀 Quickstart Guide <a name="quickstart"></a>
### Sign up as an agent
AI agents can mint a working Mem0 API key in under five seconds — no email, no dashboard, no OTP. Four commands end-to-end:
```bash
# 1. Install
npm install -g @mem0/cli # or: pip install mem0-cli
# 2. Sign up as an agent (replace `claude-code` with your name)
mem0 init --agent --agent-caller claude-code
# 3. Add a memory
mem0 add "I am using mem0"
# 4. Search
mem0 search "am I using mem0"
```
The human owner can claim the account later with `mem0 init --email <their-email>` — same key, memories preserved. Full guide: [Sign up as an agent](https://docs.mem0.ai/platform/agent-signup).
| | Library | Self-Hosted Server | Cloud Platform |
|---|---------|-------------------|----------------|
| **Best for** | Testing, prototyping | Teams running on their own infrastructure | Zero-ops production use |
@@ -132,6 +153,7 @@ See the [self-hosted docs](https://docs.mem0.ai/open-source/overview) for config
1. Sign up on [Mem0 Platform](https://app.mem0.ai?utm_source=oss&utm_medium=readme)
2. Embed the memory layer via SDK or API keys
3. Using hosted Qdrant vectors? See the [Platform migration guide](https://docs.mem0.ai/migration/oss-to-platform) to import them into Mem0 Platform.
### CLI
@@ -147,6 +169,27 @@ mem0 search "What does Alice prefer?" --user-id alice
See the [CLI documentation](https://docs.mem0.ai/platform/cli) for the full command reference.
### Agent Skills
Teach your AI coding assistant (Claude Code, Codex, Cursor, Windsurf, OpenCode, OpenClaw, and any tool that supports the skills standard) how to build with Mem0. Two categories:
**Reference skills — always on** (SDK knowledge loaded into the assistant's context):
```bash
npx skills add https://github.com/mem0ai/mem0 --skill mem0
npx skills add https://github.com/mem0ai/mem0 --skill mem0-cli
npx skills add https://github.com/mem0ai/mem0 --skill mem0-vercel-ai-sdk
```
**Pipeline skills — run on demand** (execute an end-to-end workflow in an existing repo):
```bash
npx skills add https://github.com/mem0ai/mem0 --skill mem0-integrate
npx skills add https://github.com/mem0ai/mem0 --skill mem0-test-integration
```
Use `/mem0-integrate` to wire Mem0 into an existing repo via a test-first pipeline, then `/mem0-test-integration` to verify. See the [skills catalog](./skills/) or [Vibecoding with Mem0](https://docs.mem0.ai/vibecoding) for the full picture.
### Basic Usage
Mem0 requires an LLM to function, with `gpt-5-mini` from OpenAI as the default. However, it supports a variety of LLMs; for details, refer to our [Supported LLMs documentation](https://docs.mem0.ai/components/llms/overview).
+4 -2
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@@ -503,7 +503,7 @@
},
{
"name": "init",
"description": "Setup wizard for mem0 CLI. Supports email login (--email) or manual API key (--api-key).",
"description": "Setup wizard for mem0 CLI. Supports Agent Mode bootstrap (--agent), email login (--email), or manual API key (--api-key).",
"usage": "mem0 init [OPTIONS]",
"needsBackend": false,
"needsConfig": false,
@@ -516,7 +516,9 @@
{ "name": "user-id", "flags": ["-u", "--user-id"], "type": "string", "default": null, "help": "Default user ID (skip prompt)." },
{ "name": "email", "flags": ["--email"], "type": "string", "default": null, "help": "Login via email verification code." },
{ "name": "code", "flags": ["--code"], "type": "string", "default": null, "help": "Verification code (use with --email for non-interactive login)." },
{ "name": "force", "flags": ["--force"], "type": "boolean", "default": false, "help": "Overwrite existing config without confirmation." }
{ "name": "force", "flags": ["--force"], "type": "boolean", "default": false, "help": "Overwrite existing config without confirmation." },
{ "name": "agent", "flags": ["--agent"], "type": "boolean", "default": false, "help": "Bootstrap an unattended Agent Mode account (no email required)." },
{ "name": "source", "flags": ["--source"], "type": "string", "default": null, "help": "Channel attribution for signup (e.g. github, hn, ph)." }
]
},
{
+36
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@@ -0,0 +1,36 @@
# Changelog
All notable changes to `@mem0/cli` are documented here.
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
## [0.2.7] — 2026-05-20
### Added
- `mem0 whoami` — print the active agent's `default_user_id` (the AGENTRUSH
leaderboard identifier). Reads from local config, no network call.
- `mem0 agent-rush <add | search>` — subcommand group that wraps the new
`/v1/agent-rush/` platform endpoints for the 7-day AGENTRUSH game. Project
routing is implicit (resolved server-side); no flags exposed. Pretty-prints
platform error codes into actionable hints (e.g. `agentrush_search_first`
→ "Run 3 'mem0 agent-rush search' commands before adding.").
- PII safety prompt on first `mem0 agent-rush add`. Interactive runs require
explicit `y` to acknowledge that AGENTRUSH memories are public; the
acknowledgement is persisted in `~/.mem0/config.json` under
`agent_rush.acknowledged_at` so the prompt only appears once per machine.
Non-interactive (agent) invocations surface the warning to stderr without
blocking.
- New config schema field: `agent_rush.acknowledged_at` (ISO timestamp,
empty until first interactive acknowledgement).
### Changed
- HTTP requests from the new agent-rush commands send `X-Mem0-Mode: agent-rush`
in addition to the existing source headers, so platform telemetry can split
game traffic from regular CLI usage.
## [0.2.6] and earlier
Unlogged historical releases. See git history under `cli/node/`.
+1 -1
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@@ -1,6 +1,6 @@
{
"name": "@mem0/cli",
"version": "0.2.4",
"version": "0.2.7",
"description": "The official CLI for mem0 — the memory layer for AI agents",
"type": "module",
"bin": {
+32
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@@ -0,0 +1,32 @@
/**
* Detect whether the CLI is being invoked from inside an AI-agent context.
*
* Used by `mem0 init` to auto-enter Agent Mode (Rule 3 bootstrap) when an
* agent runtime env var is present. The return value is a context **trigger
* only** — the canonical agent identity is self-declared by the agent via
* `--agent-caller <name>` (Proof Editor-style) and never sniffed from env
* vars to fill the `agent_caller` field on the APIKey row.
*
* Returns a short name or null. Honest reporting depends on `--agent-caller`;
* this list is just enough to enable the zero-friction auto-bootstrap UX.
*/
const AGENT_CALLER_ENV: ReadonlyArray<readonly [string, readonly string[]]> = [
["claude-code", ["CLAUDECODE", "CLAUDE_CODE"]],
["cursor", ["CURSOR_AGENT", "CURSOR_SESSION_ID"]],
["codex", ["CODEX_CLI", "OPENAI_CODEX"]],
["cline", ["CLINE_AGENT", "CLINE"]],
["continue", ["CONTINUE_AGENT", "CONTINUE_SESSION"]],
["aider", ["AIDER_SESSION"]],
["goose", ["GOOSE_AGENT"]],
["windsurf", ["WINDSURF_AGENT"]],
] as const;
export function detectAgentCaller(): string | null {
for (const [name, envVars] of AGENT_CALLER_ENV) {
if (envVars.some((v) => process.env[v])) {
return name;
}
}
return null;
}
+34 -2
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@@ -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(
+285
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@@ -0,0 +1,285 @@
/**
* Agent Mode commands — bootstrap (unattended signup) and OTP-based claim.
*/
import readline from "node:readline";
import { colors, printError, printInfo, printSuccess } from "../branding.js";
import { type Mem0Config, saveConfig } from "../config.js";
const { brand, dim } = colors;
const SOURCE_HEADERS = {
"X-Mem0-Source": "cli",
"X-Mem0-Client-Language": "node",
} as const;
export interface BootstrapEnvelope {
api_key: string;
default_user_id: string;
org_id: string;
project_id: string;
mcp_url?: string;
smoke_test_url?: string;
claim_command?: string;
mem0_notice?: string;
}
function isValidEnvelope(v: unknown): v is BootstrapEnvelope {
return (
!!v &&
typeof v === "object" &&
typeof (v as BootstrapEnvelope).api_key === "string" &&
(v as BootstrapEnvelope).api_key.length > 0 &&
typeof (v as BootstrapEnvelope).default_user_id === "string" &&
(v as BootstrapEnvelope).default_user_id.length > 0
);
}
/**
* POST /api/v1/auth/agent_mode/ and mutate config in place.
*
* @param config - Mem0Config mutated in place with the new platform values.
* @param source - `--source` flag passthrough (analytics tag, free-form).
* @param agentCaller - Self-declared agent identity passed via `--agent-caller`
* (e.g. `claude-code`, `cursor`). May be null when the caller omitted the
* flag; the agent can backfill later via `mem0 identify <name>`. Sent to the
* backend in the request body and saved into `platform.agentCaller` for
* local introspection.
*/
export async function bootstrapViaBackend(
config: Mem0Config,
{
source,
agentCaller,
}: { source?: string | null; agentCaller?: string | null } = {},
): Promise<void> {
const baseUrl = (config.platform.baseUrl || "https://api.mem0.ai").replace(
/\/+$/,
"",
);
const body: Record<string, unknown> = {};
if (source) body.source = source;
if (agentCaller) body.agent_caller = agentCaller;
let resp: Response;
try {
resp = await fetch(`${baseUrl}/api/v1/auth/agent_mode/`, {
method: "POST",
headers: {
...SOURCE_HEADERS,
"Content-Type": "application/json",
},
body: JSON.stringify(body),
signal: AbortSignal.timeout(30_000),
});
} catch (err) {
printError(
`Network error contacting Mem0: ${err instanceof Error ? err.message : String(err)}`,
);
process.exit(1);
}
if (resp.status === 429) {
printError("Rate-limited. Try again in a few minutes.");
process.exit(1);
}
if (resp.status === 503) {
printError("Agent Mode is temporarily disabled. Try again later.");
process.exit(1);
}
if (!resp.ok) {
let detail: string = resp.statusText;
try {
const errBody = (await resp.json()) as {
error?: string;
detail?: string;
};
detail = errBody.error ?? errBody.detail ?? resp.statusText;
} catch {
/* leave detail as statusText */
}
// Backend's @ratelimit decorator raises PermissionDenied, which DRF
// translates to a generic 403 "You do not have permission to perform
// this action." That's opaque — surface it as the rate-limit message
// it actually is.
if (resp.status === 403 && /permission/i.test(detail)) {
printError(
"Daily Agent Mode signup limit reached for this network (5/day). Try again from a different IP or after midnight UTC.",
);
process.exit(1);
}
printError(`Bootstrap failed: ${detail}`);
process.exit(1);
}
const envelope = (await resp.json()) as BootstrapEnvelope;
if (!isValidEnvelope(envelope)) {
// Defend against partial/malformed backend responses (e.g. {api_key: null}).
// Without this guard, the typed `string` field is silently set to
// undefined/null and persisted, producing confusing downstream errors.
printError(
"Bootstrap response missing required fields — please update the CLI.",
);
process.exit(1);
}
config.platform.apiKey = envelope.api_key;
config.platform.baseUrl = baseUrl;
config.platform.agentMode = true;
config.platform.createdVia = "agent_mode";
config.platform.agentCaller = agentCaller ?? "";
config.platform.claimedAt = "";
config.platform.defaultUserId = envelope.default_user_id;
// Adopt the slug-derived user_id as the default scope for memory ops.
config.defaults.userId = envelope.default_user_id;
saveConfig(config);
printSuccess(
`Agent Mode active. Default user_id: ${envelope.default_user_id}`,
);
if (envelope.mem0_notice) {
console.log(`\n\x1b[33m🔔 ${envelope.mem0_notice}\x1b[0m\n`);
} else {
// Fallback for older backends without the unified notice field.
const claimCmd = envelope.claim_command ?? "mem0 init --email <your-email>";
console.log(` ${dim(`To claim this account later: ${claimCmd}`)}`);
}
if (!agentCaller) {
console.log(
` ${dim("If you are an AI agent, identify yourself: `mem0 identify <your-name>` (e.g. claude-code, cursor).")}`,
);
}
}
/**
* Claim an existing Agent Mode account via OTP — no browser, no polling.
*
* Hits /api/v1/auth/email_code/ to send a verification code, prompts for it
* interactively (or accepts via `code`), then sends it to /verify/ alongside
* `agent_mode_api_key`. Backend's verify_email_code runs upgrade-in-place
* inline and returns the claim result.
*/
export async function claimViaOtp(
config: Mem0Config,
{ email, code }: { email: string; code?: string },
): Promise<void> {
const baseUrl = (config.platform.baseUrl || "https://api.mem0.ai").replace(
/\/+$/,
"",
);
if (!config.platform.apiKey || !config.platform.agentMode) {
printError(
"This command requires an active Agent Mode config. Run `mem0 init` first.",
);
process.exit(1);
}
const rawKey = config.platform.apiKey;
// Step 1: request OTP (unless --code was supplied)
if (!code) {
const sendResp = await fetch(`${baseUrl}/api/v1/auth/email_code/`, {
method: "POST",
headers: { ...SOURCE_HEADERS, "Content-Type": "application/json" },
body: JSON.stringify({ email }),
signal: AbortSignal.timeout(30_000),
});
if (sendResp.status === 429) {
printError("Too many attempts. Try again in a few minutes.");
process.exit(1);
}
if (!sendResp.ok) {
let detail: string = sendResp.statusText;
try {
const errBody = (await sendResp.json()) as { error?: string };
if (errBody.error) detail = errBody.error;
} catch {
/* leave as statusText */
}
printError(`Failed to send code: ${detail}`);
process.exit(1);
}
printSuccess(`Verification code sent to ${email}. Check your inbox.`);
if (!process.stdin.isTTY) {
printError(
"No --code provided and terminal is non-interactive.",
`Re-run: mem0 init --email ${email} --code <code>`,
);
process.exit(1);
}
console.log();
code = await promptLine(` ${brand("Verification Code")}`);
if (!code) {
printError("Code is required.");
process.exit(1);
}
}
// Step 2: verify + claim atomically
const verifyResp = await fetch(`${baseUrl}/api/v1/auth/email_code/verify/`, {
method: "POST",
headers: { ...SOURCE_HEADERS, "Content-Type": "application/json" },
body: JSON.stringify({
email,
code: code.trim(),
agent_mode_api_key: rawKey,
}),
signal: AbortSignal.timeout(30_000),
});
if (!verifyResp.ok) {
let detail: string = verifyResp.statusText;
let errCode = "";
try {
const errBody = (await verifyResp.json()) as {
error?: string;
code?: string;
};
if (errBody.error) detail = errBody.error;
if (errBody.code) errCode = errBody.code;
} catch {
/* leave as statusText */
}
printError(`Claim failed: ${detail}`);
if (errCode === "email_already_claimed") {
console.log(
` ${dim("Tip: this email already has a Mem0 account. Sign in at app.mem0.ai with your existing credentials.")}`,
);
}
process.exit(1);
}
const claimBody = (await verifyResp.json()) as {
claimed?: boolean;
claimed_at?: string;
};
if (!claimBody.claimed) {
printError(`Unexpected verify response: ${JSON.stringify(claimBody)}`);
process.exit(1);
}
config.platform.agentMode = false;
config.platform.claimedAt = claimBody.claimed_at ?? new Date().toISOString();
config.platform.userEmail = email;
config.platform.createdVia = "email";
saveConfig(config);
printSuccess(`Agent claimed to ${email}. Your API key is unchanged.`);
}
function promptLine(label: string): Promise<string> {
const rl = readline.createInterface({
input: process.stdin,
output: process.stdout,
});
return new Promise((resolve) => {
rl.question(`${label}: `, (answer) => {
rl.close();
resolve(answer.trim());
});
});
}
+147
View File
@@ -0,0 +1,147 @@
/**
* `mem0 agent-rush <add|search> "..."` — wraps the AGENTRUSH platform endpoints.
* Project routing is implicit (server-side); zero flags needed.
*/
import readline from "node:readline";
import { colors, printError, printSuccess } from "../branding.js";
import { loadConfig, saveConfig } from "../config.js";
import { CLI_VERSION } from "../version.js";
const PII_WARNING = [
"",
"⚠️ AGENTRUSH memories are PUBLIC — visible to any other player.",
" Do not include real names, emails, secrets, work content, or PII.",
"",
].join("\n");
const ERROR_HINTS: Record<string, string> = {
agentrush_search_first:
"Run 3 'mem0 agent-rush search' commands before adding.",
agentrush_search_quota: "You've used your 3 lifetime searches.",
agentrush_add_quota: "You've used your 3 lifetime adds.",
agentrush_not_agent_mode:
"Re-run 'mem0 init --agent' to bootstrap an agent-mode key.",
agentrush_length: "Memory text must be 50-1000 characters.",
agentrush_no_urls: "URLs are not allowed.",
agentrush_blocklist: "Content contains a blocked term.",
agentrush_global_quota: "Event-wide cap reached. Try again later.",
agentrush_not_provisioned:
"AGENTRUSH is not provisioned in this environment.",
};
async function callEndpoint(
path: string,
body: Record<string, unknown>,
): Promise<unknown> {
const config = loadConfig();
const baseUrl = (config.platform?.baseUrl ?? "https://api.mem0.ai").replace(
/\/+$/,
"",
);
if (!config.platform?.apiKey) {
printError("Not initialized. Run `mem0 init --agent` first.");
process.exit(1);
}
const resp = await fetch(`${baseUrl}${path}`, {
method: "POST",
headers: {
Authorization: `Token ${config.platform.apiKey}`,
"Content-Type": "application/json",
"X-Mem0-Source": "cli",
"X-Mem0-Client-Language": "node",
"X-Mem0-Client-Version": CLI_VERSION,
"X-Mem0-Mode": "agent-rush",
},
body: JSON.stringify(body),
signal: AbortSignal.timeout(30_000),
});
const json = await resp.json().catch(() => ({}));
if (!resp.ok) {
const code =
(json as { error?: { code?: string } }).error?.code ?? "unknown";
printError(`AGENTRUSH error: ${code}`);
if (ERROR_HINTS[code]) {
console.log(` ${colors.dim(ERROR_HINTS[code])}`);
}
process.exit(1);
}
return json;
}
function promptLine(question: string): Promise<string> {
const rl = readline.createInterface({
input: process.stdin,
output: process.stdout,
});
return new Promise((resolve) => {
rl.question(question, (answer) => {
rl.close();
resolve(answer.trim());
});
});
}
/**
* Ensure the human has acknowledged that AGENTRUSH memories are PUBLIC.
*
* Interactive (TTY): show the prompt; on "y" persist `agentRush.acknowledgedAt`
* so we never ask the same machine twice. On anything else, abort.
*
* Non-interactive (agent invocation, no TTY): print the warning to stderr
* for the human reading the agent's transcript and proceed — agents can't
* answer y/N prompts.
*/
async function ensureWarningAcknowledged(): Promise<void> {
const config = loadConfig();
if (config.agentRush?.acknowledgedAt) return;
if (!process.stdin.isTTY || !process.stdout.isTTY) {
// Agent context: surface the warning to stderr, don't block.
console.error(PII_WARNING);
return;
}
console.log(PII_WARNING);
const answer = (await promptLine(" Continue? [y/N]: ")).toLowerCase();
if (answer !== "y" && answer !== "yes") {
printError("Aborted.");
process.exit(1);
}
config.agentRush.acknowledgedAt = new Date().toISOString();
saveConfig(config);
}
export async function cmdAgentRushAdd(content: string): Promise<void> {
await ensureWarningAcknowledged();
const result = await callEndpoint("/v1/agent-rush/memories/", { content });
printSuccess(
`Memory submitted (event_id: ${(result as { event_id?: string }).event_id ?? "?"})`,
);
}
export async function cmdAgentRushSearch(query: string): Promise<void> {
const result = (await callEndpoint("/v1/agent-rush/memories/search/", {
query,
})) as {
results?: Array<{ memory?: string }>;
memories?: Array<{ memory?: string }>;
};
const memories = result.results ?? result.memories ?? [];
if (memories.length === 0) {
console.log(colors.dim("(no results)"));
return;
}
memories.slice(0, 5).forEach((m, i) => {
console.log(` ${i + 1}. ${m.memory ?? JSON.stringify(m)}`);
});
}
+75
View File
@@ -0,0 +1,75 @@
/**
* mem0 identify — declare which agent owns the current agent-mode key.
*
* Used when `mem0 init --agent` ran without --agent-caller, so the backend
* saved agent_caller=NULL. The agent re-runs `mem0 identify <name>` to PATCH
* its own row with its real identity. Idempotent.
*/
import { printError, printSuccess } from "../branding.js";
import { loadConfig, saveConfig } from "../config.js";
const SOURCE_HEADERS = {
"X-Mem0-Source": "cli",
"X-Mem0-Client-Language": "node",
} as const;
export async function runIdentify(name: string): Promise<void> {
const config = loadConfig();
if (!config.platform.apiKey) {
printError("No API key configured. Run `mem0 init --agent` first.");
process.exit(1);
}
if (!config.platform.agentMode) {
printError("This command only works on unclaimed agent-mode keys.");
process.exit(1);
}
const clean = (name ?? "").trim();
if (!clean) {
printError("Agent name is required.");
process.exit(1);
}
const baseUrl = (config.platform.baseUrl || "https://api.mem0.ai").replace(
/\/+$/,
"",
);
let resp: Response;
try {
resp = await fetch(`${baseUrl}/api/v1/auth/agent_mode/caller/`, {
method: "PATCH",
headers: {
...SOURCE_HEADERS,
Authorization: `Token ${config.platform.apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({ agent_caller: clean }),
signal: AbortSignal.timeout(30_000),
});
} catch (err) {
printError(
`Network error: ${err instanceof Error ? err.message : String(err)}`,
);
process.exit(1);
}
if (!resp.ok) {
let detail: string = resp.statusText;
try {
const body = (await resp.json()) as { error?: string };
if (body.error) detail = body.error;
} catch {
/* leave as statusText */
}
printError(`Identify failed: ${detail}`);
process.exit(1);
}
const body = (await resp.json()) as { agent_caller?: string };
const canonical = body.agent_caller ?? clean;
config.platform.agentCaller = canonical;
saveConfig(config);
printSuccess(`Identified as ${canonical}.`);
}
+167 -1
View File
@@ -21,6 +21,8 @@ import {
redactKey,
saveConfig,
} from "../config.js";
import { formatJsonEnvelope } from "../output.js";
import { isAgentMode } from "../state.js";
const { brand, dim } = colors;
@@ -33,6 +35,65 @@ function validateEmail(email: string): void {
}
}
/** @internal — exported for unit tests. */
export async function pingKey(
apiKey: string,
baseUrl: string,
timeoutMs = 5000,
): Promise<boolean> {
// Returns false ONLY on a definitive "invalid key" signal (HTTP 401/403).
// Network errors, timeouts, and 5xx responses return true so we prefer
// reusing an existing key over silently minting a new shadow on a transient
// blip (which would also clobber config + plugin-sync targets).
try {
const resp = await fetch(`${baseUrl.replace(/\/+$/, "")}/v1/ping/`, {
headers: { Authorization: `Token ${apiKey}` },
signal: AbortSignal.timeout(timeoutMs),
});
return resp.status !== 401 && resp.status !== 403;
} catch {
return true; // unknown — prefer reuse
}
}
async function maybeIdentify(
key: string,
baseUrl: string,
agentCaller: string | undefined,
): Promise<void> {
// Best-effort PATCH agent_caller when --agent-caller is supplied on a
// reused key. Silent no-op on any failure — reuse must not break.
if (!agentCaller) return;
try {
const resp = await fetch(
`${baseUrl.replace(/\/+$/, "")}/api/v1/auth/agent_mode/caller/`,
{
method: "PATCH",
headers: {
Authorization: `Token ${key}`,
"Content-Type": "application/json",
},
body: JSON.stringify({ agent_caller: agentCaller }),
signal: AbortSignal.timeout(10_000),
},
);
if (resp.ok) {
try {
const body = (await resp.json()) as { agent_caller?: string };
if (fs.existsSync(CONFIG_FILE)) {
const cfg = loadConfig();
cfg.platform.agentCaller = body.agent_caller ?? agentCaller;
saveConfig(cfg);
}
} catch {
/* swallow — best effort */
}
}
} catch {
/* swallow — best effort */
}
}
async function emailLogin(
email: string,
code: string | undefined,
@@ -196,6 +257,7 @@ async function setupPlatform(config: Mem0Config): Promise<void> {
process.exit(1);
}
config.platform.apiKey = apiKey;
config.platform.createdVia = "api_key";
}
async function setupDefaults(config: Mem0Config): Promise<void> {
@@ -249,14 +311,35 @@ export async function runInit(
email?: string;
code?: string;
force?: boolean;
agent?: boolean;
source?: string;
agentCaller?: string;
} = {},
): Promise<void> {
const { detectAgentCaller } = await import("../agent-detect.js");
const { bootstrapViaBackend, claimViaOtp } = await import("./agent-mode.js");
const { isAgentMode } = await import("../state.js");
const { captureEvent } = await import("../telemetry.js");
const fireInit = (
mode: "agent" | "email" | "api_key" | "existing_key",
claimed = false,
) => {
const props: Record<string, unknown> = { command: "init", mode };
// Self-declared via --agent-caller; not sniffed from env vars.
if (opts.agentCaller) props.agent_caller = opts.agentCaller;
if (opts.source) props.signup_source = opts.source;
if (claimed) props.claimed_agent_mode = true;
captureEvent("cli.init", props);
};
const config = createDefaultConfig();
const savedConfig = loadConfig();
const baseUrl =
process.env.MEM0_BASE_URL ||
savedConfig.platform.baseUrl ||
DEFAULT_BASE_URL;
config.platform.baseUrl = baseUrl;
// Guards
if (opts.code && !opts.email) {
@@ -268,6 +351,84 @@ export async function runInit(
process.exit(1);
}
// ── Claim flow: --email against an existing agent-mode config ───────────
if (
opts.email &&
fs.existsSync(CONFIG_FILE) &&
savedConfig.platform.agentMode &&
savedConfig.platform.apiKey
) {
const email = opts.email.trim().toLowerCase();
validateEmail(email);
printInfo(`Claiming Agent Mode account to ${email}...`);
await claimViaOtp(savedConfig, { email, code: opts.code });
fireInit("email", true);
return;
}
// ── Agent Mode path runs BEFORE the existing-config guard ──────────────
// Rule 1/2 will REUSE a valid existing key (not overwrite), so we must
// short-circuit before the guard prompts the user about overwriting.
// Rule 3 only mints when there's no valid key to reuse — in that case
// overwriting is what the user wants.
const agentCtx =
opts.agent === true || isAgentMode() || detectAgentCaller() !== null;
if (!opts.apiKey && !opts.email && agentCtx) {
const emitReuseEnvelope = (source: "env" | "config") => {
if (isAgentMode()) {
formatJsonEnvelope({
command: "init",
data: {
api_key_saved: false,
api_key_source: source,
agent_mode: false,
message:
"Existing Mem0 API key found and reused. No Agent Mode key was created.",
},
});
} else {
printSuccess(
source === "env"
? "Existing MEM0_API_KEY is valid; reusing it. No new Agent Mode key was minted."
: "Existing API key in config is valid; reusing it. No new Agent Mode key was minted.",
);
}
};
// Rule 1: env MEM0_API_KEY valid → reuse, no new key.
const envKey = (process.env.MEM0_API_KEY || "").trim();
if (envKey && (await pingKey(envKey, baseUrl))) {
await maybeIdentify(envKey, baseUrl, opts.agentCaller);
emitReuseEnvelope("env");
fireInit("existing_key");
return;
}
// Rule 2: existing config api_key valid → reuse.
if (
savedConfig.platform.apiKey &&
(await pingKey(savedConfig.platform.apiKey, baseUrl))
) {
await maybeIdentify(
savedConfig.platform.apiKey,
baseUrl,
opts.agentCaller,
);
emitReuseEnvelope("config");
fireInit("existing_key");
return;
}
// Rule 3: mint a fresh shadow (no valid key to reuse).
// agent_caller is self-declared via --agent-caller (Proof Editor-style),
// not derived from env-var sniffing. detectAgentCaller() above is still
// used as a context trigger (does this look like an agent?) but never
// to fill identity.
await bootstrapViaBackend(config, {
source: opts.source ?? null,
agentCaller: opts.agentCaller ?? null,
});
fireInit("agent");
return;
}
// Warn if an existing config with an API key would be overwritten
if (
!opts.force &&
@@ -324,6 +485,7 @@ export async function runInit(
config.platform.apiKey = apiKeyVal;
config.platform.baseUrl = baseUrl;
config.platform.userEmail = email;
config.platform.createdVia = "email";
config.defaults.userId =
opts.userId || process.env.USER || process.env.USERNAME || "mem0-cli";
@@ -339,13 +501,15 @@ export async function runInit(
}
// ── API key flow ──────────────────────────────────────────────────────────
// (Agent Mode branch runs earlier — see above, before the existing-config
// guard, so Rules 1/2 can REUSE a valid key without prompting overwrite.)
// Non-TTY: resolve defaults so partial flags work in pipelines / CI
if (!process.stdin.isTTY) {
if (!opts.apiKey) {
printError(
"Non-interactive terminal detected and --api-key is required.",
"Usage: mem0 init --api-key <key> [--user-id <id>]",
"Usage: mem0 init --api-key <key>, --email <addr>, or --agent for unattended Agent Mode bootstrap.",
);
process.exit(1);
}
@@ -356,6 +520,7 @@ export async function runInit(
// Non-interactive: both flags provided
if (opts.apiKey && opts.userId) {
config.platform.apiKey = opts.apiKey;
config.platform.createdVia = "api_key";
config.defaults.userId = opts.userId;
await validatePlatform(config);
saveConfig(config);
@@ -403,6 +568,7 @@ export async function runInit(
config.platform.apiKey = apiKeyVal;
config.platform.baseUrl = baseUrl;
config.platform.userEmail = email;
config.platform.createdVia = "email";
config.defaults.userId =
opts.userId || process.env.USER || process.env.USERNAME || "mem0-cli";
+18
View File
@@ -0,0 +1,18 @@
/**
* `mem0 whoami` — print the active agent's default_user_id (AGENTRUSH identifier).
* Reads from local config; no network call.
*/
import { colors, printError, printInfo } from "../branding.js";
import { loadConfig } from "../config.js";
export async function cmdWhoami(): Promise<void> {
const config = loadConfig();
const sessionId = config.platform?.defaultUserId;
if (!sessionId) {
printError("No default_user_id found. Run `mem0 init --agent` first.");
process.exit(1);
}
console.log(`Your AGENTRUSH identifier: ${colors.brand(sessionId)}`);
printInfo("Find your row at https://mem0.ai/agentrush");
}
+50
View File
@@ -21,6 +21,12 @@ export interface PlatformConfig {
apiKey: string;
baseUrl: string;
userEmail: string;
// Agent Mode (unclaimed-shadow signup)
agentMode: boolean; // true while the key is an unclaimed agent-mode key
createdVia: string; // "agent_mode" | "email" | "api_key" | "existing_key"
agentCaller: string; // canonical agent name when createdVia === "agent_mode" (e.g. "claude-code")
claimedAt: string; // ISO timestamp once the agent has been claimed
defaultUserId: string; // `user_<slug>` returned by bootstrap; auto-default scope
}
export interface DefaultsConfig {
@@ -34,11 +40,18 @@ export interface TelemetryConfig {
anonymousId: string;
}
export interface AgentRushConfig {
// ISO timestamp the human acknowledged the "memories are public" warning.
// Empty until first interactive `mem0 agent-rush add`.
acknowledgedAt: string;
}
export interface Mem0Config {
version: number;
defaults: DefaultsConfig;
platform: PlatformConfig;
telemetry: TelemetryConfig;
agentRush: AgentRushConfig;
}
export function createDefaultConfig(): Mem0Config {
@@ -54,10 +67,18 @@ export function createDefaultConfig(): Mem0Config {
apiKey: "",
baseUrl: DEFAULT_BASE_URL,
userEmail: "",
agentMode: false,
createdVia: "",
agentCaller: "",
claimedAt: "",
defaultUserId: "",
},
telemetry: {
anonymousId: "",
},
agentRush: {
acknowledgedAt: "",
},
};
}
@@ -79,6 +100,11 @@ export function loadConfig(): Mem0Config {
config.platform.apiKey = plat.api_key ?? "";
config.platform.baseUrl = plat.base_url ?? DEFAULT_BASE_URL;
config.platform.userEmail = plat.user_email ?? "";
config.platform.agentMode = Boolean(plat.agent_mode ?? false);
config.platform.createdVia = plat.created_via ?? "";
config.platform.agentCaller = plat.agent_caller ?? "";
config.platform.claimedAt = plat.claimed_at ?? "";
config.platform.defaultUserId = plat.default_user_id ?? "";
const defaults = data.defaults ?? {};
config.defaults.userId = defaults.user_id ?? "";
@@ -87,6 +113,8 @@ export function loadConfig(): Mem0Config {
config.defaults.runId = defaults.run_id ?? "";
const telemetry = data.telemetry ?? {};
config.telemetry.anonymousId = telemetry.anonymous_id ?? "";
const agentRush = data.agent_rush ?? {};
config.agentRush.acknowledgedAt = agentRush.acknowledged_at ?? "";
}
// Environment variable overrides
@@ -118,14 +146,36 @@ export function saveConfig(config: Mem0Config): void {
api_key: config.platform.apiKey,
base_url: config.platform.baseUrl,
user_email: config.platform.userEmail,
agent_mode: config.platform.agentMode,
created_via: config.platform.createdVia,
agent_caller: config.platform.agentCaller,
claimed_at: config.platform.claimedAt,
default_user_id: config.platform.defaultUserId,
},
telemetry: {
anonymous_id: config.telemetry.anonymousId,
},
agent_rush: {
acknowledged_at: config.agentRush.acknowledgedAt,
},
};
fs.writeFileSync(CONFIG_FILE, JSON.stringify(data, null, 2));
fs.chmodSync(CONFIG_FILE, 0o600);
// Propagate api_key to ecosystem touchpoints (Claude plugin env injection,
// shell rc exports). Idempotent — updates only EXISTING entries; never
// creates new ones. Best-effort: errors swallowed so config.json is
// always authoritative, never blocked by plugin-state issues.
if (config.platform.apiKey) {
try {
// eslint-disable-next-line @typescript-eslint/no-require-imports
const { syncApiKey } = require("./plugin-sync.js");
syncApiKey(config.platform.apiKey);
} catch {
/* swallow */
}
}
}
export function redactKey(key: string): string {
+112 -4
View File
@@ -13,7 +13,12 @@ import { colors, printError, printWarning } from "./branding.js";
import type { Mem0Config } from "./config.js";
import { loadConfig, saveConfig } from "./config.js";
import { richFormatHelp } from "./help.js";
import { setAgentMode } from "./state.js";
import {
isAgentMode,
setAgentMode,
setCurrentCommand,
takeNotice,
} from "./state.js";
import { captureEvent } from "./telemetry.js";
import { CLI_VERSION } from "./version.js";
@@ -141,6 +146,11 @@ program
.description(
`◆ Mem0 CLI v${CLI_VERSION} · Node.js SDK\n\nThe Memory Layer for AI Agents`,
)
// Positional options: flags AFTER a subcommand name belong to that
// subcommand, not the global program. Without this, `mem0 init --agent`
// routes `--agent` to the program-level alias (for --json) and init's own
// `--agent` (Agent Mode bootstrap) silently never fires.
.enablePositionalOptions()
.option("--version", "Show version and exit.")
.on("option:version", () => {
console.log(` ${colors.brand("◆ Mem0")} CLI v${CLI_VERSION}`);
@@ -149,7 +159,7 @@ program
.option("--json", "Output as JSON for agent/programmatic use.")
.option(
"--agent",
"Output as JSON for agent/programmatic use. (alias: --json)",
"Output as JSON for agent/programmatic use. (alias: --json) Place BEFORE the subcommand: `mem0 --agent <cmd>`. On `init`, `mem0 init --agent` is the Agent Mode bootstrap flag instead.",
)
.usage("<command> [options]")
.helpOption("--help", "Show this message and exit.")
@@ -166,6 +176,14 @@ program.hook("preAction", (_thisCommand, actionCommand) => {
parentName && parentName !== "mem0"
? `${parentName}.${commandName}`
: commandName;
// Stash the active command name in shared state so the JSON
// error envelope (printError) can report which command failed
// instead of an empty `"command": ""` field.
setCurrentCommand(fullCommand);
// init fires its own telemetry from runInit with full M1-M6 props
// (mode/agent_caller/signup_source/claimed_agent_mode); skip the
// auto-fire here so we don't double-count.
if (fullCommand === "init") return;
const isAgent = !!(program.opts().json || program.opts().agent);
captureEvent(
`cli.${fullCommand}`,
@@ -193,11 +211,32 @@ program
"Verification code (use with --email for non-interactive login).",
)
.option("--force", "Overwrite existing config without confirmation.", false)
.option(
"--agent",
"Bootstrap an unattended Agent Mode account (no email required).",
false,
)
.option(
"--source <channel>",
"Channel attribution for signup (e.g. github, hn, ph).",
)
.option(
"--agent-caller <name>",
"Self-declared agent identity (e.g. claude-code, cursor). Used with --agent to attribute Agent Mode signups.",
)
// Accept `--json` at the init level too so the PRD-documented form
// `mem0 init --agent --json` works without requiring users to move it
// before the subcommand. Effect is identical to the global `--json`:
// flip agent-mode output state.
.option("--json", "Output as JSON (alias for global `--json`).", false)
.addHelpText(
"after",
"\nExamples:\n $ mem0 init\n $ mem0 init --api-key m0-xxx --user-id alice\n $ mem0 init --email you@example.com\n $ mem0 init --email you@example.com --code 123456",
"\nExamples:\n $ mem0 init\n $ mem0 init --api-key m0-xxx --user-id alice\n $ mem0 init --email you@example.com\n $ mem0 init --email you@example.com --code 123456\n $ mem0 init --agent # Bootstrap an Agent Mode account (unattended)\n $ mem0 init --email you@example.com # Claims an existing Agent Mode key when one is present",
)
.action(async (opts) => {
// `--json` at init level mirrors the global flag — flip agent_mode
// state so downstream formatters use JSON envelopes.
if (opts.json) setAgentMode(true);
const { runInit } = await import("./commands/init.js");
await runInit({
apiKey: opts.apiKey,
@@ -205,9 +244,66 @@ program
email: opts.email,
code: opts.code,
force: opts.force,
agent: opts.agent,
source: opts.source,
agentCaller: opts.agentCaller,
});
});
// ── Setup: identify (post-bootstrap agent self-tag) ──────────────────────
program
.command("identify <name>")
.description(
"Tag your active Agent Mode key with the AI agent that's using it (e.g. claude-code, cursor).",
)
.action(async (name: string) => {
const { runIdentify } = await import("./commands/identify.js");
await runIdentify(name);
});
// ── Setup: whoami (print active agent identifier) ────────────────────────
program
.command("whoami")
.description("Print the active agent's AGENTRUSH identifier.")
.action(async () => {
const { cmdWhoami } = await import("./commands/whoami.js");
await cmdWhoami();
});
// ── AGENTRUSH subcommand group ────────────────────────────────────────────
const agentRush = program
.command("agent-rush")
.description("AGENTRUSH game commands.")
.addHelpCommand(false)
.configureHelp({ formatHelp: richFormatHelp });
agentRush
.command("add <content...>")
.description("Submit a memory to AGENTRUSH.")
.addHelpText(
"after",
'\nExamples:\n $ mem0 agent-rush add "I used mem0 to build a coding agent"\n $ mem0 agent-rush add "Agents that remember are better agents"',
)
.action(async (parts: string[]) => {
const { cmdAgentRushAdd } = await import("./commands/agent-rush.js");
await cmdAgentRushAdd(parts.join(" "));
});
agentRush
.command("search <query...>")
.description("Search AGENTRUSH memories.")
.addHelpText(
"after",
'\nExamples:\n $ mem0 agent-rush search "agents and memory and tools"\n $ mem0 agent-rush search "coding assistant"',
)
.action(async (parts: string[]) => {
const { cmdAgentRushSearch } = await import("./commands/agent-rush.js");
await cmdAgentRushSearch(parts.join(" "));
});
// ── Memory: add ───────────────────────────────────────────────────────────
program
@@ -769,4 +865,16 @@ program
// ── Entrypoint ────────────────────────────────────────────────────────────
program.parse();
// Surface any unclaimed Agent Mode notice once per command, after the primary
// output. In JSON/agent mode the notice is folded into the envelope by
// formatJsonEnvelope, so skip the stderr banner there to avoid duplication.
function surfaceNotice(): void {
const notice = takeNotice();
if (notice && !isAgentMode()) {
process.stderr.write(`\n\x1b[33m🔔 ${notice}\x1b[0m\n\n`);
}
}
program.parseAsync().finally(() => {
surfaceNotice();
});
+16
View File
@@ -5,6 +5,7 @@
import boxen from "boxen";
import Table from "cli-table3";
import { colors, sym } from "./branding.js";
import { takeNotice } from "./state.js";
const { brand, accent, success, error: errorColor, dim } = colors;
@@ -244,6 +245,15 @@ export function formatJsonEnvelope(opts: {
if (opts.count !== undefined) envelope.count = opts.count;
if (opts.error) envelope.error = opts.error;
envelope.data = opts.data;
// If the platform flagged this as an unclaimed Agent Mode account, surface
// the notice inside the JSON envelope so an agent consuming the output
// sees it without needing to inspect HTTP headers.
// eslint-disable-next-line @typescript-eslint/no-require-imports
const { takeNotice } = require("./state.js");
const notice = takeNotice();
if (notice) envelope.mem0_notice = notice;
console.log(JSON.stringify(envelope, null, 2));
}
@@ -356,6 +366,12 @@ export function formatAgentEnvelope(opts: {
}
if (opts.count !== undefined) envelope.count = opts.count;
envelope.data = sanitizeAgentData(opts.command, opts.data);
// Surface the unclaimed-Agent-Mode notice (if any) in the envelope so an
// agent reading the JSON output sees it without inspecting HTTP headers.
const notice = takeNotice();
if (notice) envelope.mem0_notice = notice;
console.log(JSON.stringify(envelope, null, 2));
}
+120
View File
@@ -0,0 +1,120 @@
/**
* Sync the active Mem0 API key into other ecosystem touchpoints.
*
* Why: the CLI canonical state is ~/.mem0/config.json. MCP servers
* (Claude Code plugin, Codex plugin) read MEM0_API_KEY from env or
* their own config files. Without a sync, agent-mode bootstrap mints a
* new key into config.json but the plugin's MCP keeps using the old
* key from env — silent surprise.
*
* Design:
* - Update ONLY entries that already exist; never create new ones
* - Preserve surrounding content, formatting, other keys
* - Atomic writes (tmp + rename) so a crash mid-write doesn't corrupt
* - Idempotent — re-running with the same key is a no-op
*
* Targets:
* - ~/.claude/settings.json::env::MEM0_API_KEY (Claude Code env injection)
* - ~/.zshrc / ~/.bashrc `export MEM0_API_KEY="..."` lines
*
* Out of scope: Codex / Cursor MCP configs and the plugin's own
* <plugin-dir>/.api_key file (plugin-managed, different schema).
*/
import fs from "node:fs";
import os from "node:os";
import path from "node:path";
const CLAUDE_SETTINGS = path.join(os.homedir(), ".claude", "settings.json");
const SHELL_RCS = [
path.join(os.homedir(), ".zshrc"),
path.join(os.homedir(), ".bashrc"),
path.join(os.homedir(), ".bash_profile"),
];
// Use [ \t]* (not \s*) so a trailing newline at end-of-file is preserved
// when the MEM0_API_KEY export is the last line of the rc file.
const RC_LINE_RE =
/^([ \t]*export[ \t]+MEM0_API_KEY[ \t]*=[ \t]*)(["']?)([^"'\n]*)(["']?)[ \t]*$/m;
export function syncApiKey(apiKey: string): string[] {
if (!apiKey) return [];
const updated: string[] = [];
if (updateClaudeSettings(CLAUDE_SETTINGS, apiKey)) {
updated.push(CLAUDE_SETTINGS);
}
for (const rc of SHELL_RCS) {
if (updateShellRc(rc, apiKey)) updated.push(rc);
}
return updated;
}
/** @internal — exported for unit tests; consumers should use {@link syncApiKey}. */
export function updateClaudeSettings(
filePath: string,
apiKey: string,
): boolean {
if (!fs.existsSync(filePath)) return false;
let raw: string;
let data: Record<string, unknown>;
try {
raw = fs.readFileSync(filePath, "utf-8");
data = JSON.parse(raw);
} catch {
return false;
}
const env = data.env;
if (!env || typeof env !== "object" || !("MEM0_API_KEY" in env)) {
return false; // no existing entry — don't create one
}
const envObj = env as Record<string, string>;
if (envObj.MEM0_API_KEY === apiKey) return false; // already in sync
envObj.MEM0_API_KEY = apiKey;
atomicWriteText(filePath, `${JSON.stringify(data, null, 2)}\n`);
return true;
}
/** @internal — exported for unit tests; consumers should use {@link syncApiKey}. */
export function updateShellRc(filePath: string, apiKey: string): boolean {
if (!fs.existsSync(filePath)) return false;
let text: string;
try {
text = fs.readFileSync(filePath, "utf-8");
} catch {
return false;
}
const match = text.match(RC_LINE_RE);
if (!match) return false; // no existing line
if (match[3] === apiKey) return false;
const newText = text.replace(
RC_LINE_RE,
(_full, prefix) => `${prefix}"${apiKey}"`,
);
atomicWriteText(filePath, newText);
return true;
}
function atomicWriteText(filePath: string, content: string): void {
const dir = path.dirname(filePath);
const tmp = path.join(dir, `.${path.basename(filePath)}.${process.pid}.tmp`);
try {
fs.writeFileSync(tmp, content, "utf-8");
// Preserve permissions if original existed.
if (fs.existsSync(filePath)) {
try {
const mode = fs.statSync(filePath).mode & 0o777;
fs.chmodSync(tmp, mode);
} catch {
/* best-effort */
}
}
fs.renameSync(tmp, filePath);
} catch (err) {
try {
fs.unlinkSync(tmp);
} catch {
/* ignore */
}
throw err;
}
}
+17
View File
@@ -5,6 +5,7 @@
let _agentMode = false;
let _currentCommand = "";
let _pendingNotice = "";
export function isAgentMode(): boolean {
return _agentMode;
@@ -21,3 +22,19 @@ export function getCurrentCommand(): string {
export function setCurrentCommand(name: string): void {
_currentCommand = name;
}
/**
* Stash a Mem0 backend notice (Agent Mode unclaimed reminder) for end-of-
* command surfacing. Called from the platform backend after each response so
* the notice prints once per command regardless of how many sub-requests
* fired. Last-write-wins is fine — the message text is identical.
*/
export function captureNotice(notice: string | null | undefined): void {
if (notice) _pendingNotice = notice;
}
export function takeNotice(): string {
const msg = _pendingNotice;
_pendingNotice = "";
return msg;
}
+4
View File
@@ -115,6 +115,9 @@ export function captureEvent(
}
}
// M4: every cli.* event carries agent_mode based on the config flag
// (unclaimed Agent Mode key). This is the growth-doc property used to
// join init → add → search funnels in PostHog.
const payload = {
api_key: POSTHOG_API_KEY,
distinct_id: distinctId,
@@ -123,6 +126,7 @@ export function captureEvent(
source: "CLI",
language: "node",
cli_version: CLI_VERSION,
agent_mode: Boolean(config.platform.agentMode),
node_version: process.version,
os: process.platform,
...properties,
+141
View File
@@ -0,0 +1,141 @@
/**
* Parity tests for `mem0 init --agent` (Agent Mode bootstrap).
*
* Mirror of `cli/python/tests/test_agent_mode.py` — both files MUST stay
* in sync so that the Python and Node CLIs expose an identical surface
* for the Agent Mode entrypoint. If you add a flag here, add the same
* assertion on the Python side (and vice versa).
*
* Network-bound bootstrap is covered by the platform-side E2E suite
* (`backend/tests/e2e/test_05_agent_mode.py`); these tests only verify
* the CLI surface that ships in the binary.
*/
import { describe, it, expect } from "vitest";
import { execSync } from "node:child_process";
import fs from "node:fs";
import os from "node:os";
import path from "node:path";
function run(
args: string[],
opts: { home?: string; env?: Record<string, string> } = {},
): { stdout: string; stderr: string; exitCode: number } {
const env = { ...process.env };
for (const key of Object.keys(env)) {
if (key.startsWith("MEM0_")) delete env[key];
}
if (opts.home) env.HOME = opts.home;
if (opts.env) Object.assign(env, opts.env);
try {
const stdout = execSync(`npx tsx src/index.ts ${args.join(" ")}`, {
cwd: path.join(__dirname, ".."),
env,
encoding: "utf-8",
timeout: 15000,
});
return { stdout, stderr: "", exitCode: 0 };
} catch (e: any) {
return {
stdout: e.stdout ?? "",
stderr: e.stderr ?? "",
exitCode: e.status ?? 1,
};
}
}
function cleanHome(): string {
return fs.mkdtempSync(path.join(os.tmpdir(), "mem0-test-"));
}
describe("init flag surface", () => {
it("init --help lists --agent", () => {
const result = run(["init", "--help"]);
expect(result.exitCode).toBe(0);
expect(result.stdout).toContain("--agent");
});
it("init --help describes Agent Mode", () => {
const result = run(["init", "--help"]);
expect(result.exitCode).toBe(0);
// Description must mention what --agent actually does so an agent
// reading the help can self-discover the bootstrap entrypoint.
expect(
result.stdout.includes("Agent Mode") ||
result.stdout.toLowerCase().includes("unattended"),
).toBe(true);
});
it("init --help lists --source", () => {
const result = run(["init", "--help"]);
expect(result.exitCode).toBe(0);
expect(result.stdout).toContain("--source");
});
it("init --help lists --email and --code", () => {
const result = run(["init", "--help"]);
expect(result.exitCode).toBe(0);
expect(result.stdout).toContain("--email");
expect(result.stdout).toContain("--code");
});
});
describe("argv preprocessing — --agent reaches init subcommand", () => {
// Regression for the bug where the global --agent JSON-alias swallowed
// the init-level --agent flag, making `mem0 init --agent` behave like
// the plain interactive wizard.
it("init --agent triggers bootstrap branch (not the wizard)", () => {
const home = cleanHome();
const result = run(["init", "--agent"], {
home,
env: {
MEM0_BASE_URL: "http://127.0.0.1:1", // blackhole
FORCE_COLOR: "0",
},
});
const combined = (result.stdout + result.stderr).toLowerCase();
// Either bootstrap-attempt error, or a connection/network error —
// both prove the --agent path executed (the wizard would prompt for
// input and succeed/hang, not surface a network error).
expect(
combined.includes("agent") ||
combined.includes("connect") ||
combined.includes("network") ||
combined.includes("fetch") ||
combined.includes("bootstrap"),
).toBe(true);
fs.rmSync(home, { recursive: true, force: true });
});
});
describe("JSON envelope on network failure", () => {
it("init --agent --json does not leak a stack trace when backend is unreachable", () => {
const home = cleanHome();
const result = run(["init", "--agent", "--json"], {
home,
env: {
MEM0_BASE_URL: "http://127.0.0.1:1",
FORCE_COLOR: "0",
},
});
const combined = result.stdout + result.stderr;
// No raw Node stack should escape the agent-mode handler.
expect(combined).not.toMatch(/at \w+\s*\(.+\.ts:\d+/);
expect(combined).not.toContain("UnhandledPromiseRejection");
expect(result.exitCode).not.toBe(0);
fs.rmSync(home, { recursive: true, force: true });
});
});
describe("top-level help lists init", () => {
// `mem0 --help` must list `init` so agents walking the top-level help
// can discover the Agent Mode entrypoint without prior knowledge.
it("--help lists init", () => {
const result = run(["--help"]);
expect(result.exitCode).toBe(0);
expect(result.stdout).toContain("init");
});
});
+168
View File
@@ -0,0 +1,168 @@
/**
* Unit tests for init internals — decision tree primitives + plugin sync.
*
* Mirror of `cli/python/tests/test_init_internals.py`. Both files MUST stay
* in sync — if you add a behavioral assertion here, mirror it on the Python
* side and vice versa.
*
* - `pingKey` must NOT treat network errors as "invalid key" (else a VPN
* flap silently mints a new shadow over a working key).
* - `plugin_sync` must only update entries that already exist, preserve
* trailing newlines, and never mangle other lines.
*/
import fs from "node:fs";
import os from "node:os";
import path from "node:path";
import { afterEach, beforeEach, describe, expect, it, vi } from "vitest";
import { pingKey } from "../src/commands/init.js";
import { updateClaudeSettings, updateShellRc } from "../src/plugin-sync.js";
// ── pingKey ──────────────────────────────────────────────────────────────
describe("pingKey — network vs auth distinction", () => {
const origFetch = globalThis.fetch;
afterEach(() => {
globalThis.fetch = origFetch;
vi.restoreAllMocks();
});
it("returns true for 200", async () => {
globalThis.fetch = vi.fn().mockResolvedValue({ status: 200 } as Response);
await expect(pingKey("k", "http://x")).resolves.toBe(true);
});
it("returns false for 401 (definitively invalid)", async () => {
globalThis.fetch = vi.fn().mockResolvedValue({ status: 401 } as Response);
await expect(pingKey("k", "http://x")).resolves.toBe(false);
});
it("returns false for 403 (definitively invalid)", async () => {
globalThis.fetch = vi.fn().mockResolvedValue({ status: 403 } as Response);
await expect(pingKey("k", "http://x")).resolves.toBe(false);
});
it("returns true for 5xx (transient upstream — prefer reuse)", async () => {
globalThis.fetch = vi.fn().mockResolvedValue({ status: 503 } as Response);
await expect(pingKey("k", "http://x")).resolves.toBe(true);
});
it("returns true on network error (prefer reuse over re-mint)", async () => {
globalThis.fetch = vi.fn().mockRejectedValue(new Error("ECONNREFUSED"));
await expect(pingKey("k", "http://x")).resolves.toBe(true);
});
it("returns true on timeout (prefer reuse)", async () => {
globalThis.fetch = vi.fn().mockRejectedValue(new Error("aborted"));
await expect(pingKey("k", "http://x")).resolves.toBe(true);
});
});
// ── updateShellRc ────────────────────────────────────────────────────────
describe("updateShellRc — exists-only contract", () => {
let tmpDir: string;
beforeEach(() => {
tmpDir = fs.mkdtempSync(path.join(os.tmpdir(), "mem0-test-"));
});
afterEach(() => {
fs.rmSync(tmpDir, { recursive: true, force: true });
});
it("updates existing export and preserves trailing newline", () => {
const rc = path.join(tmpDir, ".zshrc");
fs.writeFileSync(rc, 'export MEM0_API_KEY="old"\n');
expect(updateShellRc(rc, "newkey")).toBe(true);
expect(fs.readFileSync(rc, "utf-8")).toBe('export MEM0_API_KEY="newkey"\n');
});
it("does NOT create a new export when none exists", () => {
const rc = path.join(tmpDir, ".zshrc");
fs.writeFileSync(rc, "alias ll='ls -la'\n");
expect(updateShellRc(rc, "newkey")).toBe(false);
expect(fs.readFileSync(rc, "utf-8")).toBe("alias ll='ls -la'\n");
});
it("preserves surrounding content", () => {
const rc = path.join(tmpDir, ".zshrc");
const original =
"# my zshrc\n" +
"alias ll='ls -la'\n" +
"export MEM0_API_KEY='old'\n" +
"export OTHER=keepme\n";
fs.writeFileSync(rc, original);
updateShellRc(rc, "newkey");
const after = fs.readFileSync(rc, "utf-8");
expect(after).toContain("alias ll='ls -la'\n");
expect(after).toContain("export OTHER=keepme\n");
expect(after).toContain("# my zshrc\n");
expect(after).toContain('export MEM0_API_KEY="newkey"\n');
});
it("is idempotent when value already matches", () => {
const rc = path.join(tmpDir, ".zshrc");
fs.writeFileSync(rc, 'export MEM0_API_KEY="same"\n');
expect(updateShellRc(rc, "same")).toBe(false);
});
it("is a no-op for missing files", () => {
const rc = path.join(tmpDir, ".zshrc"); // does not exist
expect(updateShellRc(rc, "x")).toBe(false);
});
});
// ── updateClaudeSettings ─────────────────────────────────────────────────
describe("updateClaudeSettings — never creates entries", () => {
let tmpDir: string;
beforeEach(() => {
tmpDir = fs.mkdtempSync(path.join(os.tmpdir(), "mem0-test-"));
});
afterEach(() => {
fs.rmSync(tmpDir, { recursive: true, force: true });
});
it("does not create env block when none exists", () => {
const settings = path.join(tmpDir, "settings.json");
fs.writeFileSync(settings, JSON.stringify({ otherKey: 1 }));
expect(updateClaudeSettings(settings, "newkey")).toBe(false);
expect(JSON.parse(fs.readFileSync(settings, "utf-8"))).toEqual({
otherKey: 1,
});
});
it("does not create MEM0_API_KEY entry in existing env block", () => {
const settings = path.join(tmpDir, "settings.json");
fs.writeFileSync(settings, JSON.stringify({ env: { OTHER_KEY: "x" } }));
expect(updateClaudeSettings(settings, "newkey")).toBe(false);
});
it("updates existing entry and preserves siblings", () => {
const settings = path.join(tmpDir, "settings.json");
fs.writeFileSync(
settings,
JSON.stringify({ env: { MEM0_API_KEY: "old", OTHER: "y" } }, null, 2),
);
expect(updateClaudeSettings(settings, "fresh")).toBe(true);
const data = JSON.parse(fs.readFileSync(settings, "utf-8"));
expect(data.env.MEM0_API_KEY).toBe("fresh");
expect(data.env.OTHER).toBe("y");
});
it("is idempotent when value already matches", () => {
const settings = path.join(tmpDir, "settings.json");
fs.writeFileSync(
settings,
JSON.stringify({ env: { MEM0_API_KEY: "same" } }),
);
expect(updateClaudeSettings(settings, "same")).toBe(false);
});
it("is a no-op for malformed JSON", () => {
const settings = path.join(tmpDir, "settings.json");
fs.writeFileSync(settings, "{ this is not json");
expect(updateClaudeSettings(settings, "x")).toBe(false);
});
});
+36
View File
@@ -0,0 +1,36 @@
# Changelog
All notable changes to `mem0-cli` (Python) are documented here.
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
## [0.2.7] — 2026-05-20
### Added
- `mem0 whoami` — print the active agent's `default_user_id` (the AGENTRUSH
leaderboard identifier). Reads from local config, no network call.
- `mem0 agent-rush <add | search>` — subcommand group that wraps the new
`/v1/agent-rush/` platform endpoints for the 7-day AGENTRUSH game. Project
routing is implicit (resolved server-side); no flags exposed. Pretty-prints
platform error codes into actionable hints (e.g. `agentrush_search_first`
→ "Run 3 'mem0 agent-rush search' commands before adding.").
- PII safety prompt on first `mem0 agent-rush add`. Interactive runs require
explicit `y` to acknowledge that AGENTRUSH memories are public; the
acknowledgement is persisted in `~/.mem0/config.json` under
`agent_rush.acknowledged_at` so the prompt only appears once per machine.
Non-interactive (agent) invocations surface the warning to stderr without
blocking.
- New config schema field: `agent_rush.acknowledged_at` (ISO timestamp,
empty until first interactive acknowledgement).
### Changed
- HTTP requests from the new agent-rush commands send `X-Mem0-Mode: agent-rush`
in addition to the existing source headers, so platform telemetry can split
game traffic from regular CLI usage.
## [0.2.6] and earlier
Unlogged historical releases. See git history under `cli/python/`.
+1 -1
View File
@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
[project]
name = "mem0-cli"
version = "0.2.4"
version = "0.2.7"
description = "The official CLI for mem0 — the memory layer for AI agents"
readme = "README.md"
license = "Apache-2.0"
+36
View File
@@ -0,0 +1,36 @@
"""Detect whether the CLI is being invoked from inside an AI-agent context.
Used by `mem0 init` to auto-enter Agent Mode (Rule 3 bootstrap) when an
agent runtime env var is present. The return value is a context **trigger
only** — the canonical agent identity is self-declared by the agent via
``--agent-caller <name>`` (Proof Editor-style) and never sniffed from env
vars to fill the ``agent_caller`` field on the APIKey row.
Returns a short name or None. The list is curated, not exhaustive — env
vars we don't recognise fall through to None (caller treated as
non-agent). Honest reporting depends on ``--agent-caller``; this list is
just enough to enable the zero-friction auto-bootstrap UX.
"""
from __future__ import annotations
import os
_AGENT_CALLER_ENV: tuple[tuple[str, tuple[str, ...]], ...] = (
("claude-code", ("CLAUDECODE", "CLAUDE_CODE")),
("cursor", ("CURSOR_AGENT", "CURSOR_SESSION_ID")),
("codex", ("CODEX_CLI", "OPENAI_CODEX")),
("cline", ("CLINE_AGENT", "CLINE")),
("continue", ("CONTINUE_AGENT", "CONTINUE_SESSION")),
("aider", ("AIDER_SESSION",)),
("goose", ("GOOSE_AGENT",)),
("windsurf", ("WINDSURF_AGENT",)),
)
def detect_agent_caller() -> str | None:
"""Return a canonical agent name if any agent env var is set, else None."""
for name, env_vars in _AGENT_CALLER_ENV:
if any(os.environ.get(v) for v in env_vars):
return name
return None
+130 -5
View File
@@ -237,6 +237,14 @@ def main_callback(
cmd_version()
raise typer.Exit()
if ctx.invoked_subcommand:
# Stash the active subcommand name so the JSON error envelope
# (print_error in agent mode) can report which command failed
# instead of an empty `"command": ""` field.
from mem0_cli.state import set_current_command
set_current_command(ctx.invoked_subcommand)
if ctx.invoked_subcommand and ctx.invoked_subcommand != "init":
# init fires its own telemetry from init_cmd.run_init with full M1-M6 props.
_fire_telemetry(ctx.invoked_subcommand)
@@ -851,6 +859,19 @@ def init(
force: bool = typer.Option(
False, "--force", help="Overwrite existing config without confirmation."
),
agent_signal: bool = typer.Option(
False, "--agent", help="Bootstrap an unattended Agent Mode account (no email required)."
),
source: str | None = typer.Option(
None,
"--source",
help="Channel attribution for signup (e.g. github, hn, ph).",
),
agent_caller: str | None = typer.Option(
None,
"--agent-caller",
help="Self-declared agent identity (e.g. claude-code, cursor). Used with --agent to attribute Agent Mode signups.",
),
) -> None:
"""Interactive setup wizard for mem0 CLI.
@@ -859,10 +880,97 @@ def init(
mem0 init --api-key m0-xxx --user-id alice
mem0 init --email alice@company.com
mem0 init --email alice@company.com --code 482901
mem0 init --agent --agent-caller claude-code # AI agent self-identifies on Agent Mode bootstrap
mem0 init --email alice@company.com # Claims an existing Agent Mode key when one is present
"""
from mem0_cli.commands.init_cmd import run_init
run_init(api_key=api_key, user_id=user_id, email=email, code=code, force=force)
run_init(
api_key=api_key,
user_id=user_id,
email=email,
code=code,
force=force,
source=source,
agent=agent_signal,
agent_caller=agent_caller,
)
@app.command(rich_help_panel="Setup")
def identify(
name: str = typer.Argument(..., help="Agent identity (e.g. claude-code, cursor, my-bot)."),
) -> None:
"""Tag your active Agent Mode key with the AI agent that's using it.
Run this once after `mem0 init --agent` if you didn't pass --agent-caller.
Idempotent — re-running just overwrites the value.
Example:
mem0 identify claude-code
"""
from mem0_cli.commands.identify_cmd import run_identify
run_identify(name)
@app.command(name="whoami", rich_help_panel="Setup")
def whoami_cmd() -> None:
"""Print your AGENTRUSH identifier (default_user_id).
Example:
mem0 whoami
"""
from mem0_cli.commands.whoami_cmd import run_whoami
run_whoami()
# ── AGENTRUSH sub-app ─────────────────────────────────────────────────────
agent_rush_app = typer.Typer(
name="agent-rush",
help="AGENTRUSH game commands",
no_args_is_help=True,
rich_markup_mode="rich",
)
@agent_rush_app.callback(invoke_without_command=True)
def _agent_rush_callback(ctx: typer.Context) -> None:
if ctx.invoked_subcommand:
_fire_telemetry(f"agent-rush.{ctx.invoked_subcommand}")
@agent_rush_app.command(name="add")
def agent_rush_add(
content: str = typer.Argument(..., help="Memory content (50-1000 characters, no URLs)."),
) -> None:
"""Submit a memory to AGENTRUSH.
Example:
mem0 agent-rush add "I enjoy solving constraint-satisfaction problems."
"""
from mem0_cli.commands.agent_rush_cmd import run_agent_rush_add
run_agent_rush_add(content)
@agent_rush_app.command(name="search")
def agent_rush_search(
query: str = typer.Argument(..., help="Search query."),
) -> None:
"""Search AGENTRUSH memories.
Example:
mem0 agent-rush search "constraint satisfaction"
"""
from mem0_cli.commands.agent_rush_cmd import run_agent_rush_search
run_agent_rush_search(query)
app.add_typer(agent_rush_app, name="agent-rush", rich_help_panel="Setup")
# (entity_app registered at module level, below sub-group definitions)
@@ -1198,11 +1306,28 @@ def main() -> None:
import sys
# Allow --json/--agent anywhere in the command line (not just before subcommand).
_json_flags = {"--json", "--agent"}
if any(a in _json_flags for a in sys.argv[1:]):
# Special case: `mem0 init --agent` is a subcommand flag (Agent Mode bootstrap)
# consumed by init_cmd, not a global JSON-output toggle — leave it in argv.
argv_rest = sys.argv[1:]
is_init = "init" in argv_rest
_global_flags = {"--json"} if is_init else {"--json", "--agent"}
if any(a in _global_flags for a in argv_rest):
from mem0_cli.state import set_agent_mode
set_agent_mode(True)
sys.argv = [sys.argv[0]] + [a for a in sys.argv[1:] if a not in _json_flags]
sys.argv = [sys.argv[0]] + [a for a in argv_rest if a not in _global_flags]
app()
try:
app()
finally:
# Surface any unclaimed Agent Mode notice once per command, after the
# primary output. In JSON/agent mode the notice is folded into the
# envelope by format_json_envelope, so skip the stderr banner there
# to avoid duplicate output.
from mem0_cli.state import is_agent_mode, take_notice
notice = take_notice()
if notice and not is_agent_mode():
from rich.console import Console
Console(stderr=True).print(f"\n[yellow]🔔 {notice}[/yellow]\n")
+21 -2
View File
@@ -30,7 +30,7 @@ class PlatformBackend(Backend):
)
def _request(self, method: str, path: str, **kwargs: Any) -> Any:
from mem0_cli.state import is_agent_mode
from mem0_cli.state import capture_notice, is_agent_mode
self._client.headers["X-Mem0-Caller-Type"] = "agent" if is_agent_mode() else "user"
resp = self._client.request(method, path, **kwargs)
@@ -48,7 +48,26 @@ class PlatformBackend(Backend):
resp.raise_for_status()
if resp.status_code == 204:
return {}
return resp.json()
data = resp.json()
# Pull the unclaimed-Agent-Mode notice out of the body (or the header
# fallback for endpoints that return non-dict / non-dict-leading
# payloads) and stash it for end-of-command surfacing.
notice = None
if isinstance(data, dict) and "mem0_notice" in data:
notice = data.pop("mem0_notice")
elif (
isinstance(data, list)
and data
and isinstance(data[0], dict)
and "mem0_notice" in data[0]
):
notice = data[0].pop("mem0_notice")
if notice is None:
notice = resp.headers.get("X-Mem0-Notice-Message") or None
capture_notice(notice)
return data
def add(
self,
+4 -2
View File
@@ -87,10 +87,12 @@ def print_error(console: Console, message: str, hint: str | None = None) -> None
}
print(_json.dumps(envelope))
return
from rich.markup import escape
sym = _sym("✗", "[error]")
console.print(f"[{ERROR_COLOR}]{sym} Error:[/] {message}")
console.print(f"[{ERROR_COLOR}]{sym} Error:[/] {escape(str(message))}")
if hint:
console.print(f" [{DIM_COLOR}]{hint}[/]")
console.print(f" [{DIM_COLOR}]{escape(str(hint))}[/]")
def print_warning(console: Console, message: str) -> None:
@@ -0,0 +1,239 @@
"""Agent Mode commands — bootstrap (unattended signup) and claim (OTP-based human upgrade)."""
from __future__ import annotations
import json
import sys
from datetime import datetime, timezone
from typing import Any
import httpx
import typer
from rich.console import Console
from rich.prompt import Prompt
from mem0_cli.branding import (
BRAND_COLOR,
DIM_COLOR,
print_error,
print_success,
)
from mem0_cli.config import Mem0Config, save_config
console = Console()
err_console = Console(stderr=True)
_SOURCE_HEADERS = {
"X-Mem0-Source": "cli",
"X-Mem0-Client-Language": "python",
}
def _validate_envelope(envelope: Any) -> None:
"""Defend against partial/malformed backend responses.
A backend regression that returns ``{"api_key": null}`` would otherwise be
silently persisted, producing confusing downstream errors far from the
source. Fail fast with a clear message if the required fields are missing.
"""
if not isinstance(envelope, dict):
print_error(err_console, "Bootstrap response was not a JSON object.")
raise typer.Exit(1)
for field in ("api_key", "default_user_id"):
value = envelope.get(field)
if not isinstance(value, str) or not value:
print_error(
err_console,
f"Bootstrap response missing required field {field!r} — please update the CLI.",
)
raise typer.Exit(1)
def bootstrap_via_backend(
config: Mem0Config,
*,
source: str | None = None,
agent_caller: str | None = None,
) -> None:
"""POST /api/v1/auth/agent_mode/ and mutate config in place.
Args:
config: Mem0Config mutated in place with the new platform values.
source: ``--source`` flag passthrough (analytics tag, free-form).
agent_caller: Self-declared agent identity passed via ``--agent-caller``
(e.g. ``claude-code``, ``cursor``). May be None when the caller
omitted the flag; the agent can backfill later via
``mem0 identify <name>``. Sent to the backend in the request body
and saved into ``platform.agent_caller`` for local introspection.
Raises typer.Exit(1) on failure.
"""
base_url = (config.platform.base_url or "https://api.mem0.ai").rstrip("/")
body: dict[str, Any] = {}
if source:
body["source"] = source
if agent_caller:
body["agent_caller"] = agent_caller
try:
with httpx.Client(timeout=30.0) as client:
resp = client.post(
f"{base_url}/api/v1/auth/agent_mode/",
headers={**_SOURCE_HEADERS, "Content-Type": "application/json"},
json=body,
)
except httpx.HTTPError as exc:
print_error(err_console, f"Network error contacting Mem0: {exc}")
raise typer.Exit(1) from exc
if resp.status_code == 429:
print_error(err_console, "Rate-limited. Try again in a few minutes.")
raise typer.Exit(1)
if resp.status_code == 503:
print_error(err_console, "Agent Mode is temporarily disabled. Try again later.")
raise typer.Exit(1)
if resp.status_code != 200:
detail = resp.text
try:
err_body = resp.json()
detail = err_body.get("error") or err_body.get("detail") or resp.text
except (json.JSONDecodeError, ValueError, AttributeError):
pass
# Backend's @ratelimit decorator raises PermissionDenied, which DRF
# translates to a generic 403 "You do not have permission to perform
# this action." That's opaque — surface as the rate-limit it actually is.
if resp.status_code == 403 and "permission" in str(detail).lower():
print_error(
err_console,
"Daily Agent Mode signup limit reached for this network (5/day). Try again from a different IP or after midnight UTC.",
)
raise typer.Exit(1)
print_error(err_console, f"Bootstrap failed: {detail}")
raise typer.Exit(1)
envelope = resp.json()
_validate_envelope(envelope)
config.platform.api_key = envelope["api_key"]
config.platform.base_url = base_url
config.platform.agent_mode = True
config.platform.created_via = "agent_mode"
config.platform.agent_caller = agent_caller or ""
config.platform.claimed_at = ""
config.platform.default_user_id = envelope["default_user_id"]
# Adopt the slug-derived user_id as the default scope for memory ops.
config.defaults.user_id = envelope["default_user_id"]
save_config(config)
print_success(console, f"Agent Mode active. Default user_id: {envelope['default_user_id']}")
notice = envelope.get("mem0_notice")
if notice:
console.print(f"\n[yellow]🔔 {notice}[/yellow]\n")
else:
# Fallback if the backend hasn't deployed the unified notice yet.
claim_cmd = envelope.get("claim_command", "mem0 init --email <your-email>")
console.print(f" [{DIM_COLOR}]To claim this account later: {claim_cmd}[/]")
if not agent_caller:
console.print(
f" [{DIM_COLOR}]If you are an AI agent, identify yourself: "
f"`mem0 identify <your-name>` (e.g. claude-code, cursor).[/]"
)
def claim_via_otp(config: Mem0Config, *, email: str, code: str | None = None) -> None:
"""Claim an existing Agent Mode account via OTP — no browser, no polling.
Reuses the standard email-code flow (`/api/v1/auth/email_code/` then
`/.../verify/`) and adds the local agent-mode API key in the verify body
as `agent_mode_api_key`. Backend's `verify_email_code` runs the
upgrade-in-place transaction inline and returns claim result.
On success: flips `platform.agent_mode=false`, sets `claimed_at`, stamps
`user_email`. The api_key value itself never changes.
"""
base_url = (config.platform.base_url or "https://api.mem0.ai").rstrip("/")
if not config.platform.api_key or not config.platform.agent_mode:
print_error(
err_console,
"This command requires an active Agent Mode config. Run `mem0 init` first.",
)
raise typer.Exit(1)
raw_key = config.platform.api_key
with httpx.Client(timeout=30.0) as client:
# Step 1: request OTP (unless --code provided)
if not code:
send = client.post(
f"{base_url}/api/v1/auth/email_code/",
headers={**_SOURCE_HEADERS, "Content-Type": "application/json"},
json={"email": email},
)
if send.status_code == 429:
print_error(err_console, "Too many attempts. Try again in a few minutes.")
raise typer.Exit(1)
if send.status_code != 200:
try:
detail = send.json().get("error", send.text)
except Exception:
detail = send.text
print_error(err_console, f"Failed to send code: {detail}")
raise typer.Exit(1)
print_success(console, f"Verification code sent to {email}. Check your inbox.")
if not sys.stdin.isatty():
print_error(
err_console,
"No --code provided and terminal is non-interactive.",
hint=f"Re-run: mem0 init --email {email} --code <code>",
)
raise typer.Exit(1)
console.print()
code = Prompt.ask(f" [{BRAND_COLOR}]Verification Code[/]")
if not code:
print_error(err_console, "Code is required.")
raise typer.Exit(1)
# Step 2: verify + claim in one shot
verify = client.post(
f"{base_url}/api/v1/auth/email_code/verify/",
headers={**_SOURCE_HEADERS, "Content-Type": "application/json"},
json={
"email": email,
"code": code.strip(),
"agent_mode_api_key": raw_key,
},
)
if verify.status_code != 200:
try:
err_body = verify.json()
detail = err_body.get("error", verify.text)
code_str = err_body.get("code", "")
except (json.JSONDecodeError, ValueError, AttributeError):
detail = verify.text
code_str = ""
print_error(err_console, f"Claim failed: {detail}")
if code_str == "email_already_claimed":
console.print(
f" [{DIM_COLOR}]Tip: this email already has a Mem0 account. Sign in at app.mem0.ai with your existing credentials.[/]"
)
raise typer.Exit(1)
claim_body = verify.json()
if not claim_body.get("claimed"):
print_error(err_console, f"Unexpected verify response: {claim_body}")
raise typer.Exit(1)
config.platform.agent_mode = False
config.platform.claimed_at = claim_body.get("claimed_at") or _utcnow_iso()
config.platform.user_email = email
config.platform.created_via = "email"
save_config(config)
print_success(console, f"Agent claimed to {email}. Your API key is unchanged.")
def _utcnow_iso() -> str:
return datetime.now(timezone.utc).isoformat()
@@ -0,0 +1,132 @@
"""mem0 agent-rush — AGENTRUSH game commands.
Wraps the platform's /v1/agent-rush/{memories/, memories/search/} endpoints.
Hardcoded routing; no flags needed.
"""
from __future__ import annotations
import sys
from datetime import datetime, timezone
import httpx
import typer
from rich.console import Console
from mem0_cli.branding import print_error, print_success
from mem0_cli.config import load_config, save_config
console = Console()
err_console = Console(stderr=True)
_PII_WARNING_LINES = (
"",
"[yellow]⚠️ AGENTRUSH memories are PUBLIC — visible to any other player.[/yellow]",
"[yellow] Do not include real names, emails, secrets, work content, or PII.[/yellow]",
"",
)
_SOURCE_HEADERS = {
"X-Mem0-Source": "cli",
"X-Mem0-Client-Language": "python",
"X-Mem0-Mode": "agent-rush",
}
_ERROR_HINTS = {
"agentrush_search_first": "Run 3 'mem0 agent-rush search' commands before adding.",
"agentrush_search_quota": "You've used your 3 lifetime searches.",
"agentrush_add_quota": "You've used your 3 lifetime adds.",
"agentrush_not_agent_mode": "Re-run 'mem0 init --agent' to bootstrap an agent-mode key.",
"agentrush_length": "Memory text must be 50-1000 characters.",
"agentrush_no_urls": "URLs are not allowed.",
"agentrush_blocklist": "Content contains a blocked term.",
"agentrush_global_quota": "Event-wide cap reached. Try again later.",
"agentrush_not_provisioned": "AGENTRUSH is not provisioned in this environment.",
}
def _call(path: str, body: dict) -> dict:
config = load_config()
if not config.platform.api_key:
print_error(err_console, "Not initialized. Run `mem0 init --agent` first.")
raise typer.Exit(1)
base_url = (config.platform.base_url or "https://api.mem0.ai").rstrip("/")
try:
with httpx.Client(timeout=30.0) as client:
resp = client.post(
f"{base_url}{path}",
headers={
**_SOURCE_HEADERS,
"Authorization": f"Token {config.platform.api_key}",
"Content-Type": "application/json",
},
json=body,
)
except httpx.HTTPError as exc:
print_error(err_console, f"Network error: {exc}")
raise typer.Exit(1) from exc
try:
data = resp.json()
except Exception:
data = {}
if resp.status_code >= 400:
code = (
(data.get("error") or {}).get("code", "unknown")
if isinstance(data, dict)
else "unknown"
)
print_error(err_console, f"AGENTRUSH error: {code}")
hint = _ERROR_HINTS.get(code)
if hint:
console.print(f" [dim]{hint}[/dim]")
raise typer.Exit(1)
return data
def _ensure_warning_acknowledged() -> None:
"""Block the first interactive add on the PII warning; pass-through for agents.
Interactive (TTY): show prompt, require explicit 'y', persist
`agent_rush.acknowledged_at` so we never ask the same machine twice.
Non-interactive (no TTY — typical when an agent runs the CLI): surface
the warning to stderr for the human reading the agent transcript and
proceed without prompting (agents can't answer y/N).
"""
config = load_config()
if config.agent_rush.acknowledged_at:
return
is_tty = sys.stdin.isatty() and sys.stdout.isatty()
if not is_tty:
for line in _PII_WARNING_LINES:
err_console.print(line)
return
for line in _PII_WARNING_LINES:
console.print(line)
answer = typer.prompt(" Continue? [y/N]", default="N", show_default=False).strip().lower()
if answer not in ("y", "yes"):
print_error(err_console, "Aborted.")
raise typer.Exit(1)
config.agent_rush.acknowledged_at = datetime.now(timezone.utc).isoformat()
save_config(config)
def run_agent_rush_add(content: str) -> None:
_ensure_warning_acknowledged()
result = _call("/v1/agent-rush/memories/", {"content": content})
event_id = result.get("event_id", "?")
print_success(console, f"Memory submitted (event_id: {event_id})")
def run_agent_rush_search(query: str) -> None:
result = _call("/v1/agent-rush/memories/search/", {"query": query})
memories = result.get("results") or result.get("memories") or []
if not memories:
console.print("[dim](no results)[/dim]")
return
for i, m in enumerate(memories[:5], start=1):
text = m.get("memory") if isinstance(m, dict) else str(m)
console.print(f" {i}. {text}")
@@ -0,0 +1,75 @@
"""mem0 identify — declare which agent owns the current agent-mode key.
Used when `mem0 init --agent` ran without --agent-caller, so the backend
saved agent_caller=NULL. The agent re-runs `mem0 identify <name>` to PATCH
its own row with its real identity. Idempotent — running it again just
overwrites.
"""
from __future__ import annotations
import httpx
import typer
from rich.console import Console
from mem0_cli.branding import print_error, print_success
from mem0_cli.config import load_config, save_config
console = Console()
err_console = Console(stderr=True)
_SOURCE_HEADERS = {
"X-Mem0-Source": "cli",
"X-Mem0-Client-Language": "python",
}
def run_identify(name: str) -> None:
"""PATCH the active agent-mode key's agent_caller field."""
config = load_config()
if not config.platform.api_key:
print_error(
err_console,
"No API key configured. Run `mem0 init --agent` first.",
)
raise typer.Exit(1)
if not config.platform.agent_mode:
print_error(
err_console,
"This command only works on unclaimed agent-mode keys.",
)
raise typer.Exit(1)
name = (name or "").strip()
if not name:
print_error(err_console, "Agent name is required.")
raise typer.Exit(1)
base_url = (config.platform.base_url or "https://api.mem0.ai").rstrip("/")
try:
with httpx.Client(timeout=30.0) as client:
resp = client.patch(
f"{base_url}/api/v1/auth/agent_mode/caller/",
headers={
**_SOURCE_HEADERS,
"Authorization": f"Token {config.platform.api_key}",
"Content-Type": "application/json",
},
json={"agent_caller": name},
)
except httpx.HTTPError as exc:
print_error(err_console, f"Network error: {exc}")
raise typer.Exit(1) from exc
if resp.status_code != 200:
try:
detail = resp.json().get("error", resp.text)
except Exception:
detail = resp.text
print_error(err_console, f"Identify failed: {detail}")
raise typer.Exit(1)
canonical = resp.json().get("agent_caller", name)
config.platform.agent_caller = canonical
save_config(config)
print_success(console, f"Identified as {canonical}.")
+149 -1
View File
@@ -103,6 +103,25 @@ def _validate_email(email: str) -> None:
raise typer.Exit(1)
def _ping_key(api_key: str, base_url: str, timeout: float = 5.0) -> bool:
"""Validate api_key against /v1/ping/.
Returns False ONLY on a definitive "invalid key" signal (HTTP 401 / 403).
Network errors, timeouts, and 5xx responses return True so we prefer
reusing an existing key over silently minting a new shadow on a transient
blip (which would also clobber config + plugin-sync targets).
"""
try:
resp = httpx.get(
f"{base_url.rstrip('/')}/v1/ping/",
headers={"Authorization": f"Token {api_key}"},
timeout=timeout,
)
except httpx.HTTPError:
return True # unknown — prefer reuse
return resp.status_code not in (401, 403)
def _email_login(
email: str,
code: str | None,
@@ -182,21 +201,143 @@ def run_init(
email: str | None = None,
code: str | None = None,
force: bool = False,
source: str | None = None,
agent: bool = False,
agent_caller: str | None = None,
) -> None:
"""Interactive setup wizard for mem0 CLI.
When both *api_key* and *user_id* are supplied, all prompts are skipped
(non-interactive mode). When running in a non-TTY without the required
flags, an error message is printed.
Agent Mode dispatch (no email/api-key flags):
- If existing config has an active API key → reuse (existing_key path).
- Else if any positive agent signal (--agent, --json global, agent env
var, or `agent` flag) → POST /api/v1/auth/agent_mode/ and write config.
- Else fall through to the interactive wizard.
Claim dispatch:
- If `--email` is set AND existing config has `agent_mode=true`, run the
claim device-flow against the existing key instead of minting a new
email-based key.
"""
from mem0_cli.agent_detect import detect_agent_caller
from mem0_cli.commands.agent_mode_cmd import bootstrap_via_backend, claim_via_otp
from mem0_cli.state import is_agent_mode as _global_agent_mode
from mem0_cli.telemetry import capture_event
def _fire_init(mode: str, *, claimed: bool = False) -> None:
"""Fire cli.init telemetry with M1-M6 properties."""
props: dict = {"command": "init", "mode": mode}
if agent_caller:
# Self-declared via --agent-caller; not sniffed from env vars.
props["agent_caller"] = agent_caller
if source:
props["signup_source"] = source
if claimed:
props["claimed_agent_mode"] = True
capture_event("cli.init", props)
config = Mem0Config()
base_url = os.environ.get("MEM0_BASE_URL", config.platform.base_url or DEFAULT_BASE_URL)
config.platform.base_url = base_url
if code and not email:
print_error(err_console, "--code requires --email.")
raise typer.Exit(1)
# ── Email + existing agent-mode config → claim flow ─────────────────
if email and CONFIG_FILE.exists():
existing = load_config()
if existing.platform.agent_mode and existing.platform.api_key:
email = email.strip().lower()
_validate_email(email)
print_info(console, f"Claiming Agent Mode account to {email}...")
claim_via_otp(existing, email=email, code=code)
_fire_init("email", claimed=True)
return
# ── Agent Mode path runs BEFORE the existing-config guard ──────────
# Rules 1/2 REUSE a valid existing key (not overwrite), so we must
# short-circuit before the guard prompts. Rule 3 mints only when there
# is no valid key to reuse — in that case overwriting is correct.
_agent_ctx = agent or _global_agent_mode() or (detect_agent_caller() is not None)
if not api_key and not email and _agent_ctx:
from mem0_cli.output import format_json_envelope
from mem0_cli.state import is_agent_mode as _is_json_mode
def _emit_reuse(source: str) -> None:
if _is_json_mode():
format_json_envelope(
console,
command="init",
data={
"api_key_saved": False,
"api_key_source": source,
"agent_mode": False,
"message": "Existing Mem0 API key found and reused. No Agent Mode key was created.",
},
)
else:
msg = (
"Existing MEM0_API_KEY is valid; reusing it. No new Agent Mode key was minted."
if source == "env"
else "Existing API key in config is valid; reusing it. No new Agent Mode key was minted."
)
print_success(console, msg)
def _maybe_identify(key: str) -> None:
"""Best-effort PATCH agent_caller when --agent-caller is supplied on a
reused key. Silent no-op on any failure — reuse must not break.
"""
if not agent_caller:
return
try:
resp = httpx.patch(
f"{base_url.rstrip('/')}/api/v1/auth/agent_mode/caller/",
headers={
"Authorization": f"Token {key}",
"Content-Type": "application/json",
},
json={"agent_caller": agent_caller},
timeout=10.0,
)
# Also reflect in local config so introspection matches backend.
if resp.status_code == 200 and CONFIG_FILE.exists():
try:
cfg = load_config()
cfg.platform.agent_caller = resp.json().get("agent_caller", agent_caller)
save_config(cfg)
except Exception:
pass
except httpx.HTTPError:
pass
# Rule 1: env MEM0_API_KEY valid → reuse, no new key.
_env_key = (os.environ.get("MEM0_API_KEY") or "").strip()
if _env_key and _ping_key(_env_key, base_url):
_maybe_identify(_env_key)
_emit_reuse("env")
_fire_init("existing_key")
return
# Rule 2: existing config api_key valid → reuse.
if CONFIG_FILE.exists():
_existing = load_config()
if _existing.platform.api_key and _ping_key(_existing.platform.api_key, base_url):
_maybe_identify(_existing.platform.api_key)
_emit_reuse("config")
_fire_init("existing_key")
return
# Rule 3: mint a fresh shadow (no valid key to reuse).
# agent_caller is the agent's self-declared identity from --agent-caller
# (Proof Editor-style). Env-var auto-detect is still used above to
# decide we're in an agent context, but never to fill identity.
bootstrap_via_backend(config, source=source, agent_caller=agent_caller)
_fire_init("agent")
return
# Warn if an existing config with an API key would be overwritten
if not force and CONFIG_FILE.exists():
existing = load_config()
@@ -242,6 +383,7 @@ def run_init(
config.platform.api_key = api_key_val
config.platform.base_url = base_url
config.platform.user_email = email
config.platform.created_via = "email"
config.defaults.user_id = (
user_id or os.environ.get("USER") or os.environ.get("USERNAME") or "mem0-cli"
)
@@ -258,6 +400,8 @@ def run_init(
return
# ── API key flow (existing) ───────────────────────────────────────
# (Agent Mode branch runs earlier — see above, before the existing-config
# guard, so Rules 1/2 can REUSE a valid key without prompting overwrite.)
# Non-TTY: resolve defaults so partial flags work in pipelines / CI
if not sys.stdin.isatty():
@@ -265,7 +409,7 @@ def run_init(
print_error(
err_console,
"Non-interactive terminal detected and --api-key is required.",
hint="Run: mem0 init --api-key <key> [--user-id <id>]",
hint="Run: mem0 init --api-key <key>, --email <addr>, or --agent for unattended Agent Mode bootstrap.",
)
raise typer.Exit(1)
user_id = user_id or os.environ.get("USER") or os.environ.get("USERNAME") or "mem0-cli"
@@ -273,6 +417,7 @@ def run_init(
# Fully non-interactive when both flags provided
if api_key and user_id:
config.platform.api_key = api_key
config.platform.created_via = "api_key"
config.defaults.user_id = user_id
_validate_platform(config)
save_config(config)
@@ -313,6 +458,7 @@ def run_init(
config.platform.api_key = api_key_val
config.platform.base_url = base_url
config.platform.user_email = email_addr
config.platform.created_via = "email"
config.defaults.user_id = (
user_id or os.environ.get("USER") or os.environ.get("USERNAME") or "mem0-cli"
)
@@ -331,6 +477,7 @@ def run_init(
# API key flow
if api_key:
config.platform.api_key = api_key
config.platform.created_via = "api_key"
else:
_setup_platform(config)
@@ -370,6 +517,7 @@ def _setup_platform(config: Mem0Config) -> None:
raise typer.Exit(1)
config.platform.api_key = api_key
config.platform.created_via = "api_key"
def _setup_defaults(config: Mem0Config) -> None:
@@ -0,0 +1,25 @@
"""mem0 whoami — print the active agent's default_user_id (AGENTRUSH identifier)."""
from __future__ import annotations
import typer
from rich.console import Console
from mem0_cli.branding import BRAND_COLOR, print_error, print_info
from mem0_cli.config import load_config
console = Console()
err_console = Console(stderr=True)
def run_whoami() -> None:
config = load_config()
session_id = config.platform.default_user_id if config.platform else None
if not session_id:
print_error(
err_console,
"No default_user_id found. Run `mem0 init --agent` first.",
)
raise typer.Exit(1)
console.print(f"Your AGENTRUSH identifier: [{BRAND_COLOR}]{session_id}[/{BRAND_COLOR}]")
print_info(console, "Find your row at https://mem0.ai/agentrush")
+45
View File
@@ -28,6 +28,14 @@ class PlatformConfig:
api_key: str = ""
base_url: str = DEFAULT_BASE_URL
user_email: str = ""
# Agent Mode (unclaimed-shadow signup)
agent_mode: bool = False # True while the key is an unclaimed agent-mode key
created_via: str = "" # "agent_mode" | "email" | "api_key" | "existing_key"
agent_caller: str = (
"" # canonical agent name when created_via == "agent_mode" (e.g. "claude-code")
)
claimed_at: str = "" # ISO timestamp once the agent has been claimed by a human
default_user_id: str = "" # `user_<slug>` returned by bootstrap; used as auto-default
@dataclass
@@ -43,12 +51,20 @@ class TelemetryConfig:
anonymous_id: str = ""
@dataclass
class AgentRushConfig:
# ISO timestamp the human acknowledged the "memories are public" warning.
# Empty until first interactive `mem0 agent-rush add`.
acknowledged_at: str = ""
@dataclass
class Mem0Config:
version: int = CONFIG_VERSION
defaults: DefaultsConfig = field(default_factory=DefaultsConfig)
platform: PlatformConfig = field(default_factory=PlatformConfig)
telemetry: TelemetryConfig = field(default_factory=TelemetryConfig)
agent_rush: AgentRushConfig = field(default_factory=AgentRushConfig)
SHORT_KEY_ALIASES: dict[str, str] = {
@@ -83,6 +99,11 @@ def load_config() -> Mem0Config:
config.platform.api_key = plat.get("api_key", "")
config.platform.base_url = plat.get("base_url", DEFAULT_BASE_URL)
config.platform.user_email = plat.get("user_email", "")
config.platform.agent_mode = bool(plat.get("agent_mode", False))
config.platform.created_via = plat.get("created_via", "")
config.platform.agent_caller = plat.get("agent_caller", "")
config.platform.claimed_at = plat.get("claimed_at", "")
config.platform.default_user_id = plat.get("default_user_id", "")
defaults = data.get("defaults", {})
config.defaults.user_id = defaults.get("user_id", "")
@@ -92,6 +113,9 @@ def load_config() -> Mem0Config:
telemetry = data.get("telemetry", {})
config.telemetry.anonymous_id = telemetry.get("anonymous_id", "")
agent_rush = data.get("agent_rush", {})
config.agent_rush.acknowledged_at = agent_rush.get("acknowledged_at", "")
# Environment variable overrides
env_key = os.environ.get("MEM0_API_KEY")
if env_key:
@@ -136,10 +160,18 @@ def save_config(config: Mem0Config) -> None:
"api_key": config.platform.api_key,
"base_url": config.platform.base_url,
"user_email": config.platform.user_email,
"agent_mode": config.platform.agent_mode,
"created_via": config.platform.created_via,
"agent_caller": config.platform.agent_caller,
"claimed_at": config.platform.claimed_at,
"default_user_id": config.platform.default_user_id,
},
"telemetry": {
"anonymous_id": config.telemetry.anonymous_id,
},
"agent_rush": {
"acknowledged_at": config.agent_rush.acknowledged_at,
},
}
with open(CONFIG_FILE, "w") as f:
@@ -147,6 +179,19 @@ def save_config(config: Mem0Config) -> None:
os.chmod(CONFIG_FILE, stat.S_IRUSR | stat.S_IWUSR) # 0600
# Propagate the active api_key to ecosystem touchpoints (Claude Code
# plugin env injection, shell rc exports). Idempotent — only updates
# EXISTING entries; never creates new ones. Best-effort: any IOError
# in the sync is swallowed so config.json is always the authoritative
# write, never blocked by plugin-state issues.
if config.platform.api_key:
try:
from mem0_cli.plugin_sync import sync_api_key
sync_api_key(config.platform.api_key)
except Exception:
pass
def redact_key(key: str) -> str:
"""Redact an API key for display: m0-xxx...xxx"""
+19
View File
@@ -229,6 +229,16 @@ def format_json_envelope(
if error:
envelope["error"] = error
envelope["data"] = data
# If the platform flagged this as an unclaimed Agent Mode account, surface
# the notice inside the JSON envelope so an agent consuming the output
# sees it without needing to inspect HTTP headers.
from mem0_cli.state import take_notice
notice = take_notice()
if notice:
envelope["mem0_notice"] = notice
console.print_json(json.dumps(envelope, default=str))
@@ -323,6 +333,15 @@ def format_agent_envelope(
if count is not None:
envelope["count"] = count
envelope["data"] = sanitize_agent_data(command, data)
# Surface the unclaimed-Agent-Mode notice (if any) in the envelope so an
# agent reading the JSON output sees it without inspecting HTTP headers.
from mem0_cli.state import take_notice
notice = take_notice()
if notice:
envelope["mem0_notice"] = notice
console.print_json(json.dumps(envelope, default=str))
+119
View File
@@ -0,0 +1,119 @@
"""Sync the active Mem0 API key into other ecosystem touchpoints.
Why this exists:
The CLI canonical state lives in ``~/.mem0/config.json``. But MCP servers
(Claude Code plugin, Codex plugin, etc.) read ``MEM0_API_KEY`` from env
vars or their own config files. Without a sync, an agent-mode bootstrap
mints a new key into config.json but the plugin's MCP keeps using the
old key from env — silent surprise.
Design:
- Update ONLY entries that already exist (never create new ones)
- Preserve all surrounding content / formatting / other keys
- Atomic writes (tmpfile + rename) so a crash mid-write doesn't corrupt
- Idempotent — re-running with the same key is a no-op
- Skip on dry_run
Targets currently handled:
- ``~/.claude/settings.json::env::MEM0_API_KEY`` (Claude Code env injection)
- ``~/.zshrc`` / ``~/.bashrc`` ``export MEM0_API_KEY="..."`` lines
Out of scope (deliberately not touched):
- Codex / Cursor MCP configs — would require schema-aware edits and
those tools don't have mem0 entries by default
- Plugin's own ``<plugin-dir>/.api_key`` file — plugin-managed
"""
from __future__ import annotations
import contextlib
import json
import os
import re
import tempfile
from pathlib import Path
# Files we know how to update safely.
_CLAUDE_SETTINGS = Path.home() / ".claude" / "settings.json"
_SHELL_RCS = [Path.home() / ".zshrc", Path.home() / ".bashrc", Path.home() / ".bash_profile"]
def sync_api_key(api_key: str) -> list[str]:
"""Propagate ``api_key`` into known ecosystem touchpoints.
Returns the list of paths actually updated. Empty list means nothing
needed updating (either targets didn't exist or already had this value).
"""
if not api_key:
return []
updated: list[str] = []
if _update_claude_settings(_CLAUDE_SETTINGS, api_key):
updated.append(str(_CLAUDE_SETTINGS))
for rc in _SHELL_RCS:
if _update_shell_rc(rc, api_key):
updated.append(str(rc))
return updated
def _update_claude_settings(path: Path, api_key: str) -> bool:
"""Update ``env.MEM0_API_KEY`` in path. Returns True if file was changed."""
if not path.is_file():
return False
try:
with path.open("r", encoding="utf-8") as f:
data = json.load(f)
except (json.JSONDecodeError, OSError):
return False
env = data.get("env")
if not isinstance(env, dict) or "MEM0_API_KEY" not in env:
# No existing entry — don't create one.
return False
if env["MEM0_API_KEY"] == api_key:
return False # already in sync
env["MEM0_API_KEY"] = api_key
_atomic_write_text(path, json.dumps(data, indent=2, ensure_ascii=False) + "\n")
return True
# Match `export MEM0_API_KEY="..."` (or single quotes, or no quotes).
# Use [ \t]* (not \s*) for trailing whitespace so a trailing newline at
# end-of-file is preserved when MEM0_API_KEY is the last line.
_RC_LINE = re.compile(
r'^([ \t]*export[ \t]+MEM0_API_KEY[ \t]*=[ \t]*)(["\']?)([^"\'\n]*)(["\']?)[ \t]*$',
re.MULTILINE,
)
def _update_shell_rc(path: Path, api_key: str) -> bool:
"""Update an existing ``export MEM0_API_KEY=...`` line in path."""
if not path.is_file():
return False
try:
text = path.read_text(encoding="utf-8")
except OSError:
return False
match = _RC_LINE.search(text)
if not match:
return False # no existing line
if match.group(3) == api_key:
return False
new_text = _RC_LINE.sub(lambda m: f'{m.group(1)}"{api_key}"', text, count=1)
_atomic_write_text(path, new_text)
return True
def _atomic_write_text(path: Path, content: str) -> None:
"""Write content to path atomically (temp + rename)."""
dirname = path.parent
fd, tmp_path = tempfile.mkstemp(prefix=f".{path.name}.", suffix=".tmp", dir=dirname)
try:
with os.fdopen(fd, "w", encoding="utf-8") as f:
f.write(content)
# Preserve mode if the original existed.
if path.exists():
os.chmod(tmp_path, path.stat().st_mode & 0o777)
os.replace(tmp_path, path)
except Exception:
with contextlib.suppress(OSError):
os.unlink(tmp_path)
raise
+21
View File
@@ -4,6 +4,7 @@ from __future__ import annotations
_agent_mode: bool = False
_current_command: str = ""
_pending_notice: str = ""
def is_agent_mode() -> bool:
@@ -22,3 +23,23 @@ def get_current_command() -> str:
def set_current_command(name: str) -> None:
global _current_command
_current_command = name
def capture_notice(notice: str | None) -> None:
"""Stash a Mem0 backend notice for end-of-command surfacing.
Called from the platform backend after each response so the notice can
be printed once per command (regardless of how many sub-requests fired).
Last-write-wins is fine — the message text is identical across requests.
"""
global _pending_notice
if notice:
_pending_notice = notice
def take_notice() -> str:
"""Return and clear the pending notice."""
global _pending_notice
msg = _pending_notice
_pending_notice = ""
return msg
+4 -2
View File
@@ -87,7 +87,6 @@ def capture_event(
try:
from mem0_cli import __version__
from mem0_cli.config import CONFIG_FILE, load_config, save_config
from mem0_cli.state import is_agent_mode
config = load_config()
distinct_id = pre_resolved_email or _get_distinct_id()
@@ -107,6 +106,9 @@ def capture_event(
with contextlib.suppress(Exception):
save_config(config)
# M4: every cli.* event carries agent_mode based on the config flag
# (unclaimed Agent Mode key). This is the growth-doc property used to
# join init → add → search funnels in PostHog.
payload = {
"api_key": POSTHOG_API_KEY,
"distinct_id": distinct_id,
@@ -115,7 +117,7 @@ def capture_event(
"source": "CLI",
"language": "python",
"cli_version": __version__,
"agent_mode": is_agent_mode(),
"agent_mode": bool(config.platform.agent_mode),
"python_version": sys.version,
"os": sys.platform,
"os_version": platform.version(),
+157
View File
@@ -0,0 +1,157 @@
"""Parity tests for `mem0 init --agent` (Agent Mode bootstrap).
Mirror of ``cli/node/tests/agent-mode.test.ts`` — both files MUST stay in
sync so that the Python and Node CLIs expose an identical surface for the
Agent Mode entrypoint. If you add a flag here, add the same assertion on
the Node side (and vice versa).
Network-bound bootstrap is covered by the platform-side E2E suite
(``backend/tests/e2e/test_05_agent_mode.py``); these tests only verify
the CLI surface that ships in the binary.
"""
from __future__ import annotations
import os
import re
import subprocess
import sys
import pytest
_ANSI_RE = re.compile(r"\x1b\[[0-9;]*[mKJHABCDfsu]")
def _strip_ansi(text: str) -> str:
return _ANSI_RE.sub("", text)
def _run(args: list[str], home_dir: str | None = None) -> subprocess.CompletedProcess:
env = os.environ.copy()
for key in list(env.keys()):
if key.startswith("MEM0_"):
del env[key]
env.pop("FORCE_COLOR", None)
if home_dir:
env["HOME"] = home_dir
result = subprocess.run(
[sys.executable, "-m", "mem0_cli", *args],
capture_output=True,
text=True,
env=env,
timeout=15,
)
return subprocess.CompletedProcess(
args=result.args,
returncode=result.returncode,
stdout=_strip_ansi(result.stdout),
stderr=_strip_ansi(result.stderr),
)
@pytest.fixture
def clean_home(tmp_path):
return str(tmp_path)
class TestInitFlagSurface:
"""`mem0 init --help` must expose the Agent Mode flags."""
def test_init_help_lists_agent_flag(self):
result = _run(["init", "--help"])
assert result.returncode == 0
assert "--agent" in result.stdout
def test_init_help_describes_agent_mode(self):
result = _run(["init", "--help"])
assert result.returncode == 0
# Description must mention what --agent actually does so an agent
# reading the help can self-discover the bootstrap entrypoint.
assert "Agent Mode" in result.stdout or "unattended" in result.stdout.lower()
def test_init_help_lists_source_flag(self):
result = _run(["init", "--help"])
assert result.returncode == 0
assert "--source" in result.stdout
def test_init_help_lists_email_and_code(self):
# Claim flow flags must remain present alongside Agent Mode flags.
result = _run(["init", "--help"])
assert result.returncode == 0
assert "--email" in result.stdout
assert "--code" in result.stdout
class TestArgvPreprocessing:
"""`--agent` on `init` must reach init_cmd, not be eaten by the global preprocessor.
Regression for the bug where the top-level `--agent` JSON-alias was
stripped from ``sys.argv`` before Typer could bind it to the init
subcommand, making ``mem0 init --agent`` indistinguishable from a
plain ``mem0 init`` (interactive wizard).
"""
def test_init_with_agent_reaches_subcommand(self, clean_home):
# We can't hit a real backend in unit tests, so we point the CLI at
# a guaranteed-dead URL and assert the failure is the bootstrap
# request failing — proving the --agent flag was honored and the
# bootstrap branch ran, not the interactive wizard.
result = subprocess.run(
[sys.executable, "-m", "mem0_cli", "init", "--agent"],
capture_output=True,
text=True,
env={
**{k: v for k, v in os.environ.items() if not k.startswith("MEM0_")},
"HOME": clean_home,
"MEM0_BASE_URL": "http://127.0.0.1:1", # blackhole
"FORCE_COLOR": "0",
},
timeout=15,
)
combined = _strip_ansi(result.stdout + result.stderr).lower()
# Either we got a connection/network error from the bootstrap POST,
# or the CLI surfaced an Agent Mode-specific failure message.
assert (
"agent" in combined
or "connect" in combined
or "network" in combined
or "fetch" in combined
or "bootstrap" in combined
), f"Expected bootstrap attempt, got: {combined!r}"
class TestJsonEnvelopeParity:
"""`mem0 init --agent --json` should produce a JSON envelope on success.
Without a live backend we can only assert the failure shape: when the
backend is unreachable, the CLI must still exit non-zero AND not crash
on a Python traceback (which would mean we leaked an exception past
the agent-mode handler).
"""
def test_init_agent_json_no_traceback_on_network_failure(self, clean_home):
result = subprocess.run(
[sys.executable, "-m", "mem0_cli", "init", "--agent", "--json"],
capture_output=True,
text=True,
env={
**{k: v for k, v in os.environ.items() if not k.startswith("MEM0_")},
"HOME": clean_home,
"MEM0_BASE_URL": "http://127.0.0.1:1",
"FORCE_COLOR": "0",
},
timeout=15,
)
combined = _strip_ansi(result.stdout + result.stderr)
assert "Traceback (most recent call last)" not in combined
assert result.returncode != 0
class TestInitInCommandList:
"""`mem0 --help` must list `init` so agents walking the top-level help
can discover the Agent Mode entrypoint without prior knowledge."""
def test_top_level_help_lists_init(self):
result = _run(["--help"])
assert result.returncode == 0
assert "init" in result.stdout
+206
View File
@@ -0,0 +1,206 @@
"""Unit tests for init internals — decision tree primitives + plugin sync.
These tests exercise the units that the high-level subprocess parity tests in
``test_agent_mode.py`` deliberately can't reach:
- ``_ping_key`` must NOT treat network errors as "invalid key" (else a VPN
flap silently mints a new shadow over a working key).
- ``plugin_sync`` must only update entries that already exist, preserve
trailing newlines, and never mangle other lines.
- The 403→ratelimit translation in ``bootstrap_via_backend`` surfaces the
real cause instead of DRF's opaque "You do not have permission" string.
Mirror surface lives in ``cli/node/tests/agent-mode.test.ts``; if you add a
behavioral assertion here, mirror it on the Node side and vice versa.
"""
from __future__ import annotations
from unittest.mock import MagicMock
import httpx
import pytest
from mem0_cli.commands.init_cmd import _ping_key
from mem0_cli.plugin_sync import _update_claude_settings, _update_shell_rc
# ── _ping_key ──────────────────────────────────────────────────────────────
class _Resp:
def __init__(self, status_code: int) -> None:
self.status_code = status_code
def test_ping_key_200_is_valid(monkeypatch: pytest.MonkeyPatch) -> None:
monkeypatch.setattr(httpx, "get", lambda *a, **kw: _Resp(200))
assert _ping_key("k", "http://x") is True
def test_ping_key_401_is_invalid(monkeypatch: pytest.MonkeyPatch) -> None:
monkeypatch.setattr(httpx, "get", lambda *a, **kw: _Resp(401))
assert _ping_key("k", "http://x") is False
def test_ping_key_403_is_invalid(monkeypatch: pytest.MonkeyPatch) -> None:
monkeypatch.setattr(httpx, "get", lambda *a, **kw: _Resp(403))
assert _ping_key("k", "http://x") is False
def test_ping_key_5xx_is_not_definitively_invalid(monkeypatch: pytest.MonkeyPatch) -> None:
# Transient upstream failure must NOT cause a shadow to be minted.
monkeypatch.setattr(httpx, "get", lambda *a, **kw: _Resp(503))
assert _ping_key("k", "http://x") is True
def test_ping_key_connect_error_prefers_reuse(monkeypatch: pytest.MonkeyPatch) -> None:
# Network blip (DNS, captive portal, etc.) — must NOT trigger a re-mint.
def boom(*a, **kw):
raise httpx.ConnectError("nope")
monkeypatch.setattr(httpx, "get", boom)
assert _ping_key("k", "http://x") is True
def test_ping_key_timeout_prefers_reuse(monkeypatch: pytest.MonkeyPatch) -> None:
def boom(*a, **kw):
raise httpx.ReadTimeout("slow")
monkeypatch.setattr(httpx, "get", boom)
assert _ping_key("k", "http://x") is True
# ── plugin_sync._update_shell_rc ──────────────────────────────────────────
def test_shell_rc_updates_existing_export_preserves_trailing_newline(tmp_path) -> None:
rc = tmp_path / ".zshrc"
rc.write_text('export MEM0_API_KEY="old"\n', encoding="utf-8")
changed = _update_shell_rc(rc, "newkey")
assert changed is True
assert rc.read_text(encoding="utf-8") == 'export MEM0_API_KEY="newkey"\n'
def test_shell_rc_does_not_create_new_export(tmp_path) -> None:
rc = tmp_path / ".zshrc"
rc.write_text("alias ll='ls -la'\n", encoding="utf-8")
changed = _update_shell_rc(rc, "newkey")
assert changed is False
assert rc.read_text(encoding="utf-8") == "alias ll='ls -la'\n"
def test_shell_rc_preserves_surrounding_content(tmp_path) -> None:
rc = tmp_path / ".zshrc"
original = "# my zshrc\nalias ll='ls -la'\nexport MEM0_API_KEY='old'\nexport OTHER=keepme\n"
rc.write_text(original, encoding="utf-8")
_update_shell_rc(rc, "newkey")
after = rc.read_text(encoding="utf-8")
assert "alias ll='ls -la'\n" in after
assert "export OTHER=keepme\n" in after
assert "# my zshrc\n" in after
assert 'export MEM0_API_KEY="newkey"\n' in after
def test_shell_rc_idempotent_when_already_matching(tmp_path) -> None:
rc = tmp_path / ".zshrc"
rc.write_text('export MEM0_API_KEY="same"\n', encoding="utf-8")
assert _update_shell_rc(rc, "same") is False
def test_shell_rc_missing_file_is_noop(tmp_path) -> None:
rc = tmp_path / ".zshrc" # does not exist
assert _update_shell_rc(rc, "x") is False
# ── plugin_sync._update_claude_settings ────────────────────────────────────
def test_claude_settings_does_not_create_env_block(tmp_path) -> None:
import json
settings = tmp_path / "settings.json"
settings.write_text(json.dumps({"otherKey": 1}), encoding="utf-8")
changed = _update_claude_settings(settings, "newkey")
assert changed is False
# Original content unchanged.
assert json.loads(settings.read_text(encoding="utf-8")) == {"otherKey": 1}
def test_claude_settings_does_not_create_mem0_entry_in_existing_env(tmp_path) -> None:
import json
settings = tmp_path / "settings.json"
settings.write_text(json.dumps({"env": {"OTHER_KEY": "x"}}), encoding="utf-8")
changed = _update_claude_settings(settings, "newkey")
assert changed is False
def test_claude_settings_updates_existing_entry(tmp_path) -> None:
import json
settings = tmp_path / "settings.json"
settings.write_text(
json.dumps({"env": {"MEM0_API_KEY": "old", "OTHER": "y"}}, indent=2),
encoding="utf-8",
)
changed = _update_claude_settings(settings, "fresh")
assert changed is True
data = json.loads(settings.read_text(encoding="utf-8"))
assert data["env"]["MEM0_API_KEY"] == "fresh"
assert data["env"]["OTHER"] == "y" # other keys preserved
def test_claude_settings_idempotent(tmp_path) -> None:
import json
settings = tmp_path / "settings.json"
settings.write_text(json.dumps({"env": {"MEM0_API_KEY": "same"}}), encoding="utf-8")
assert _update_claude_settings(settings, "same") is False
def test_claude_settings_malformed_json_is_noop(tmp_path) -> None:
settings = tmp_path / "settings.json"
settings.write_text("{ this is not json", encoding="utf-8")
assert _update_claude_settings(settings, "x") is False
# ── bootstrap rate-limit translation ──────────────────────────────────────
def test_bootstrap_403_permission_surfaces_ratelimit(monkeypatch, capsys) -> None:
"""DRF 403 'You do not have permission' must be translated to the daily limit message."""
from mem0_cli.commands.agent_mode_cmd import bootstrap_via_backend
from mem0_cli.config import Mem0Config
fake_resp = MagicMock()
fake_resp.status_code = 403
fake_resp.text = '{"detail": "You do not have permission to perform this action."}'
fake_resp.json = MagicMock(
return_value={"detail": "You do not have permission to perform this action."}
)
class _Client:
def __init__(self, *a, **kw):
pass
def __enter__(self):
return self
def __exit__(self, *a):
return False
def post(self, *a, **kw):
return fake_resp
monkeypatch.setattr(httpx, "Client", _Client)
cfg = Mem0Config()
cfg.platform.base_url = "https://api.mem0.ai"
import typer
with pytest.raises(typer.Exit):
bootstrap_via_backend(cfg)
captured = capsys.readouterr()
combined = captured.out + captured.err
assert "Daily Agent Mode signup limit reached" in combined
assert "permission to perform this action" not in combined
+2
View File
@@ -5,3 +5,5 @@ openapi: get /v1/event/{event_id}/
---
Retrieve details about a specific event by passing its `event_id`. This endpoint is particularly helpful for tracking the status, payload, and completion details of asynchronous memory operations.
For `POST /v3/memories/add/`, the event confirms that the write pipeline completed. Temporal reasoning enrichment runs asynchronously by default, so the event may be `SUCCEEDED` slightly before temporal ranking signals are available to subsequent `search` calls.
@@ -83,4 +83,3 @@ The request is queued for background processing. The response contains an `event
<Info>
Poll the event status via `GET /v1/event/{event_id}/`. Status will be `SUCCEEDED` or `FAILED` once processing completes.
</Info>
@@ -64,4 +64,3 @@ memories = client.get_all(
<Info>
The response is a paginated envelope with `count`, `next`, `previous`, and `results`. Use `page` and `page_size` query params to step through results.
</Info>
@@ -49,6 +49,7 @@ related_memories = client.search(
{
"id": "ea925981-272f-40dd-b576-be64e4871429",
"memory": "Likes to play cricket and plays cricket on weekends.",
"user_id": "alice",
"metadata": {
"category": "hobbies"
},
@@ -109,6 +109,19 @@ client.project.update(
)
```
#### Toggle Memory Decay
`decay` is a per-project boolean that turns on [Memory Decay](/platform/features/memory-decay) — a search-time ranking bias that reinforces recently-accessed memories and gently dampens stale ones. The flag is `false` by default; set it via the same project-update endpoint:
```bash cURL
curl -X PATCH https://api.mem0.ai/api/v1/orgs/organizations/$ORG_ID/projects/$PROJECT_ID/ \
-H "Authorization: Token $MEM0_API_KEY" \
-H "Content-Type: application/json" \
-d '{"decay": true}'
```
The current state is returned on every project read (and supports `?fields=decay` for a minimal response). Toggling has no effect on stored memories, only on how v3 search ranks them.
### Delete Project
<Warning>
+29 -1
View File
@@ -4,6 +4,34 @@ description: "Major product launches, headline features, and milestones for Mem0
mode: "wide"
---
<Update label="2026-05-13" description="Temporal Reasoning for Mem0 Platform v3">
**Temporal Reasoning — Time-Aware Retrieval for Platform v3**
Mem0 Platform v3 can now interpret time-aware memories and queries so assistants retrieve the right information for questions about the past, upcoming plans, and current state.
- **Time-aware search intent** — Queries like `last week`, `upcoming`, `right now`, and `as of March 2025` return contextually appropriate results automatically
- **Enabled by default** — No per-request toggle required for v3 writes or searches
- **Anchored relative queries** — `reference_date` anchors relative search phrases for tests, backfills, and reproducible demos
- **Normal response shape** — Temporal reasoning affects ranking while preserving existing client response patterns
See [Temporal Reasoning](/platform/features/temporal-reasoning) for usage details.
</Update>
<Update label="2026-05-08" description="Memory Decay">
**Memory Decay — Recently-Used Memories Surface Higher, Automatically**
Per-project search-time ranking bias that boosts recently-touched memories and gently dampens stale ones. Off by default; opt in per project via the `decay` field on the project endpoint, or via `client.project.update(decay=True)` in the SDKs (Python `v2.0.2` / TypeScript `v3.0.3`).
- **Soft bias, never a filter.** The scaling factor stays in `0.3×–1.5×`. Decay can reorder candidates but never zeros them out — anything that surfaced before decay can still surface after.
- **Reinforcement loop.** Every memory returned in a search has its access history updated, so frequently-used facts naturally float to the top over time.
- **Public score still clamped to `[0, 1]`.** Existing API contract preserved; no client-side changes needed.
- **v3 search only**, fully reversible. See [Memory Decay docs](/platform/features/memory-decay).
</Update>
<Update label="2026-04-14" description="Mem0 SDK v2.0.0 / v3.0.0">
**New Memory Algorithm — State-of-the-Art Accuracy at ~3-4x Lower Cost**
@@ -99,4 +127,4 @@ Major expansion of the provider ecosystem:
First skill launch — a dedicated Mem0 skill providing platform API reference, quickstart patterns, and integration examples directly inside agent sessions. Available on [skills.sh](https://skills.sh) for any compatible AI coding agent.
</Update>
</Update>
+30
View File
@@ -4,6 +4,36 @@ description: "Release notes for the OpenClaw plugin and agent harness."
mode: "wide"
---
<Update label="2026-04-29" description="v1.0.11">
**New Features:**
- **Skills-mode auto-setup:** `enableSkillsConfig()` now runs automatically after onboarding — enables triage, recall (with reranking + keyword search), and dream consolidation with `tools.profile = "full"` and disables the built-in session-memory hook to avoid conflicts
- **Memory runtime capability:** Plugin now exposes `runtime.getMemorySearchManager()` and `resolveMemoryBackendConfig()` on the registered memory capability, enabling OpenClaw gateway to query memory status and backend config directly
- **Dimension-aware collections:** OSS wizard detects embedder dimension changes and creates a new collection (`mem0_<dims>d`) automatically, with a warning about old memories being inaccessible under the new embedder
- **Tool documentation in skills:** Both `memory-triage` and `memory-dream` SKILL.md files now include full tool reference sections listing all available tools with parameters
**Improvements:**
- **Auto-capture and auto-recall default to enabled:** `autoCapture` and `autoRecall` now default to `true` (was `false`). Manifest descriptions updated accordingly. Ignored in skills mode
- **`memory_update` over delete+add:** Skills now prefer `memory_update` for in-place edits — atomic and preserves edit history. Consolidation pattern updated: update best memory, delete redundant ones
- **Search threshold lowered:** Default `searchThreshold` reduced from `0.5` to `0.1` for broader recall. Removed hardcoded `0.6` recall-specific override — all searches now use the configured threshold
- **Embedder dimension propagation:** Vector store config auto-resolves dimensions from embedder config when not explicitly set. Syncs `dimension` and `embeddingModelDims` fields for Qdrant/PGVector compatibility
- **Config file write safety:** `writeFullConfig()` now re-reads and deep-merges the `plugins` section before writing, preserving `installs` and `slots` written by the OpenClaw gateway
- **Additional embedder models:** Added `mxbai-embed-large` (1024), `all-minilm` (384), and `snowflake-arctic-embed` (1024) to known embedder dimensions
**Security:**
- Bumped `protobufjs` to `>=7.5.5` via pnpm overrides (GHSA-xq3m-2v4x-88gg) ([#5012](https://github.com/mem0ai/mem0/pull/5012))
**Fixes:**
- Moved `bootstrapTelemetryFlag()` and removed `ensureInstallRecord()` from module-level side effects — both now run inside `register()` to avoid crashes when loaded outside OpenClaw gateway
- Fixed OSS history DB path resolution: absolute paths no longer passed through `resolvePath()`, preventing double-prefix bugs
- Manifest `providerAuthEnvVars` replaced with spec-compliant `setup.providers` format using `id` + `envVars`
**Dependencies:**
- Bumped `mem0ai` from `3.0.1` to `3.0.2`
- Bumped `pluginApi` and `minGatewayVersion` compat to `>=2026.4.24`
</Update>
<Update label="2026-04-23" description="v1.0.10">
**Security:**
+18 -1
View File
@@ -4,6 +4,24 @@ description: "Release notes for the Mem0 hosted platform — backend, dashboard,
mode: "wide"
---
<Update label="2026-05-13" description="">
**New Features:**
- **Memory:** Added Temporal Reasoning for Platform v3 to improve ranking for time-aware queries such as `last week`, `upcoming`, `right now`, and `as of ...`
- **Search:** Added `reference_date` support to anchor relative temporal queries for tests, backfills, and reproducible demos
**Improvements:**
- **API:** Temporal reasoning preserves the normal client response shape for search and get-all results
</Update>
<Update label="2026-05-04" description="">
**New Features:**
- **Memory Decay:** Per-project search-time ranking bias that boosts recently-used memories and gently dampens stale ones. Opt-in via `decay` on the project endpoint; off by default. The scaling factor stays in `0.3×–1.5×`, the public `score` remains clamped to `[0, 1]`, and the bias never filters a candidate out. See [Memory Decay docs](/platform/features/memory-decay).
</Update>
<Update label="2026-04-16" description="">
**Improvements:**
@@ -294,4 +312,3 @@ mode: "wide"
- **Core:** Fixed unicode error in user_id, agent_id, run_id and app_id
</Update>
+51 -1
View File
@@ -7,6 +7,20 @@ 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:**
@@ -41,7 +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))
@@ -910,6 +924,18 @@ 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:**
@@ -1297,6 +1323,30 @@ See the [TypeScript SDK migration guide](https://docs.mem0.ai/migration/ts-v2-to
<Tab title="CLI">
<Update label="2026-05-16" description="Python v0.2.6 / Node v0.2.6">
**Bug Fixes:**
- **Claim flow error message:** The `email_already_claimed` tip in `mem0 init --email` previously suggested running `mem0 link <key>` — a command that doesn't exist. Replaced with honest copy pointing the user to sign in at app.mem0.ai with their existing credentials ([#5152](https://github.com/mem0ai/mem0/pull/5152))
</Update>
<Update label="2026-05-14" description="Python v0.2.5 / Node v0.2.5">
**New Features:**
- **Agent Mode (`mem0 init --agent`):** Zero-friction signup for AI agents — mints a working Mem0 API key in under 5 seconds with no email, no dashboard, no OTP. Returns an unclaimed shadow account the human can later claim with `mem0 init --email <their-email>` (memories preserved, same key keeps working) ([#5123](https://github.com/mem0ai/mem0/pull/5123))
- **Self-declared agent identity:** Agents pass `--agent-caller <name>` (e.g. `claude-code`, `cursor`, `codex`) on `mem0 init --agent` so signups attribute to the right tool in analytics. Proof Editor-style — the agent declares itself rather than the CLI sniffing it from env vars ([#5123](https://github.com/mem0ai/mem0/pull/5123))
- **`mem0 identify <name>`:** New subcommand to self-tag an Agent Mode key after the fact when the agent forgot to pass `--agent-caller` on init. Idempotent — re-running just overwrites ([#5123](https://github.com/mem0ai/mem0/pull/5123))
- **Plugin sync:** `~/.claude/settings.json::env::MEM0_API_KEY` and `~/.zshrc`/`.bashrc` `export MEM0_API_KEY=` lines stay in sync with `~/.mem0/config.json` automatically. Idempotent — only updates EXISTING entries, never creates new ones ([#5123](https://github.com/mem0ai/mem0/pull/5123))
- **Claim flow:** `mem0 init --email <email>` claims an existing Agent Mode shadow via OTP. Upgrade-in-place — the API key never changes, memories transfer to the human's account ([#5123](https://github.com/mem0ai/mem0/pull/5123))
**Bug Fixes:**
- **Decision tree network resilience:** `pingKey` now distinguishes network errors from invalid keys — returns false ONLY on HTTP 401/403, returns true on connection failures / timeouts / 5xx. Prevents a VPN flap from silently rotating the user's API key and rewriting plugin-sync targets ([#5123](https://github.com/mem0ai/mem0/pull/5123))
- **Rate-limit error clarity:** DRF's opaque `"You do not have permission"` 403 from Agent Mode rate limits is now translated to `"Daily Agent Mode signup limit reached for this network (5/day). Try again from a different IP or after midnight UTC."` ([#5123](https://github.com/mem0ai/mem0/pull/5123))
- **JSON envelope `command` field:** `mem0 init --agent --json` error envelopes now populate the `command` field correctly instead of returning an empty string ([#5123](https://github.com/mem0ai/mem0/pull/5123))
- **Bootstrap envelope validation:** Defends against partial/malformed backend responses (e.g. `{api_key: null}`) silently persisting null/undefined into typed string fields ([#5123](https://github.com/mem0ai/mem0/pull/5123))
</Update>
<Update label="2026-04-22" description="Python v0.2.4 / Node v0.2.4">
**New Features:**
@@ -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>
+6 -3
View File
@@ -40,6 +40,7 @@
"icon": "rocket",
"pages": [
"platform/overview",
"platform/agent-signup",
"vibecoding",
"platform/mem0-mcp",
"platform/cli",
@@ -72,7 +73,8 @@
"platform/features/entity-scoped-memory",
"platform/features/async-client",
"platform/features/multimodal-support",
"platform/features/custom-categories"
"platform/features/custom-categories",
"platform/features/temporal-reasoning"
]
},
{
@@ -83,7 +85,8 @@
"platform/advanced-memory-operations",
"platform/features/criteria-retrieval",
"platform/features/contextual-add",
"platform/features/custom-instructions"
"platform/features/custom-instructions",
"platform/features/memory-decay"
]
},
{
@@ -1143,4 +1146,4 @@
"destination": "/introduction"
}
]
}
}
+32 -17
View File
@@ -1,6 +1,6 @@
---
title: OpenClaw
description: "Add long-term memory to OpenClaw agents using the Mem0 plugin with auto-recall and auto-capture support."
description: "Add long-term memory to OpenClaw agents using the Mem0 plugin with skills-based memory extraction and recall."
---
Add long-term memory to [OpenClaw](https://github.com/openclaw/openclaw) agents with the `@mem0/openclaw-mem0` plugin. Your agent forgets everything between sessions — this plugin fixes that by automatically watching conversations, extracting what matters, and bringing it back when relevant.
@@ -12,11 +12,12 @@ Add long-term memory to [OpenClaw](https://github.com/openclaw/openclaw) agents
</Frame>
The plugin provides:
1. **Auto-Recall** — Before the agent responds, memories matching the current message are injected into context
2. **Auto-Capture** — After the agent responds, the exchange is sent to Mem0 which decides what's worth keeping
3. **Agent Tools** — Eight tools for explicit memory operations during conversations
1. **Triage** — The agent extracts durable facts from conversations using a structured protocol with importance gates and domain overlays
2. **Recall** — Before each turn, relevant memories are retrieved with reranking and injected into context
3. **Dream** — Periodic memory consolidation: merges duplicates, resolves conflicts, prunes stale entries
4. **Agent Tools** — Eight tools for explicit memory operations during conversations
Both auto-recall and auto-capture are opt-in (`autoRecall: true`, `autoCapture: true` in config). Once enabled, they run silently with no manual intervention required.
Skills mode, `autoRecall`, and `autoCapture` are all enabled by default during `openclaw mem0 init`.
## Requirements
@@ -24,12 +25,12 @@ Check your OpenClaw version:
```bash
openclaw --version
# OpenClaw 2026.4.15 (041266a)
# OpenClaw 2026.4.25 (aa36ee6)
```
| OpenClaw Version | Plugin Support |
|------------------|----------------|
| `>= 2026.4.15` | Fully supported |
| `>= 2026.4.25` | Fully supported |
## Installation
@@ -100,9 +101,9 @@ You no longer need manual config editing to get started. Everything happens insi
</Step>
</Steps>
That's it. No API key, no config file editing, no environment variables. The plugin is now active and auto-capture and auto-recall are running on every turn.
That's it. No API key, no config file editing, no environment variables. The plugin is now active with skills-based memory (triage, recall, and dream) running automatically.
<Note>The chat flow uses the same underlying config as manual setup — it writes `apiKey` and `userId` into `openclaw.json` for you. You can still open the file to inspect or override values afterward.</Note>
<Note>The chat flow uses the same underlying config as manual setup — it writes `apiKey`, `userId`, and `skills` config into `openclaw.json` for you. You can still open the file to inspect or override values afterward.</Note>
#### Option 2: Manual Config
@@ -131,7 +132,19 @@ That's it. No API key, no config file editing, no environment variables. The plu
"enabled": true,
"config": {
"apiKey": "${MEM0_API_KEY}",
"userId": "alice" // any unique identifier you choose for this user
"userId": "alice", // any unique identifier you choose for this user
"skills": {
"triage": { "enabled": true },
"recall": {
"enabled": true,
"tokenBudget": 1500,
"rerank": true,
"keywordSearch": true,
"identityAlwaysInclude": true
},
"dream": { "enabled": true },
"domain": "companion"
}
}
}
}
@@ -328,8 +341,8 @@ openclaw mem0 status --json
|-----|------|---------|-------------|
| `mode` | `"platform"` \| `"open-source"` | `"platform"` | Which backend to use |
| `userId` | `string` | OS username | Scope memories per user |
| `autoRecall` | `boolean` | `false` | Inject memories before each turn (opt-in) |
| `autoCapture` | `boolean` | `false` | Store facts after each turn (opt-in) |
| `autoRecall` | `boolean` | `true` | Inject memories before each turn. Ignored when `skills` is configured. |
| `autoCapture` | `boolean` | `true` | Store facts after each turn. Ignored when `skills` is configured. |
| `topK` | `number` | `5` | Max memories per recall |
| `searchThreshold` | `number` | `0.3` | Min similarity (0–1) |
@@ -426,9 +439,11 @@ If `openclaw plugins update` fails:
| **Platform** | Conversations sent to `api.mem0.ai` for extraction and storage | Mem0 cloud |
| **Open-source** | Embeddings generated via configured provider (default: OpenAI API). Vectors stored locally. | `~/.mem0/vector_store.db` (SQLite) |
### Enabling Auto-Capture and Auto-Recall
### Auto-Capture and Auto-Recall
Auto-capture and auto-recall are disabled by default (opt-in). To enable either or both:
Auto-capture and auto-recall are **enabled by default**. When skills mode is configured (the default after `openclaw mem0 init`), these are ignored in favor of the skills-based triage/recall/dream protocol.
To disable either:
```json5
{
@@ -436,8 +451,8 @@ Auto-capture and auto-recall are disabled by default (opt-in). To enable either
"entries": {
"openclaw-mem0": {
"config": {
"autoCapture": true, // send conversations to Mem0 for extraction
"autoRecall": true // inject relevant memories into context
"autoCapture": false, // disable automatic fact extraction
"autoRecall": false // disable automatic memory injection
}
}
}
@@ -445,7 +460,7 @@ Auto-capture and auto-recall are disabled by default (opt-in). To enable either
}
```
Without these enabled, the agent can still use memory tools (`memory_add`, `memory_search`, etc.) explicitly — only the automatic background behavior is off.
The agent can always use memory tools (`memory_add`, `memory_search`, etc.) explicitly regardless of these settings.
### Credential Protection
+5 -5
View File
@@ -157,27 +157,27 @@ mode: "custom"
</a>
<a
href="/platform/cli"
href="/platform/agent-signup"
className="group flex h-full flex-col overflow-hidden rounded-2xl border border-gray-200 dark:border-zinc-800/40 bg-white dark:bg-zinc-900/40 transition hover:border-primary/60 hover:bg-gray-50 dark:hover:bg-zinc-900"
>
<img
className="block dark:hidden aspect-[2/1] w-full object-cover"
src="/images/docs thumbnails/light/CLI.png"
alt="CLI thumbnail"
alt="Sign up as an agent thumbnail"
style={{pointerEvents: "none"}}
/>
<img
className="hidden dark:block aspect-[2/1] w-full object-cover"
src="/images/docs thumbnails/dark/CLI.png"
alt="CLI thumbnail"
alt="Sign up as an agent thumbnail"
style={{pointerEvents: "none"}}
/>
<div className="flex flex-1 flex-col gap-2 px-4 pb-4 pt-3 text-left">
<h3 className="text-base font-semibold text-gray-900 dark:text-zinc-100 group-hover:text-primary">
CLI
Sign up as an agent
</h3>
<p className="text-sm text-gray-600 dark:text-zinc-400">
Manage memories directly from your terminal. Built for developers and AI agents.
For AI agents: mint a Mem0 API key in under five seconds — no email, no dashboard. Four commands to your first memory.
</p>
</div>
</a>
+9
View File
@@ -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`
@@ -153,6 +159,7 @@ If the user is on a pre-current major (Python < 2, TS < 3, or Platform `output_f
- [Introduction](https://docs.mem0.ai/introduction) [Both]: Use when the user wants a one-page overview of how memory fits between the LLM and the app.
- [Vibe Code with Mem0](https://docs.mem0.ai/vibecoding) [Both]: Use when the user is in Claude Code, Cursor, or Windsurf and wants memory wired into their editor.
- [Platform Overview](https://docs.mem0.ai/platform/overview) [Platform]: Use when the user picks the managed product - 4-line integration, sub-50ms retrieval, dashboard.
- [Sign up as an agent](https://docs.mem0.ai/platform/agent-signup) [Platform]: Use when an AI agent needs to mint a Mem0 API key autonomously - four commands, no email or dashboard, human claims ownership later.
- [Platform vs Open Source](https://docs.mem0.ai/platform/platform-vs-oss) [Both]: Use when the user is deciding between managed and self-hosted.
- [Platform Quickstart](https://docs.mem0.ai/platform/quickstart) [Platform]: Use for the first Platform integration - API key plus `MemoryClient.add/search`.
- [Platform CLI](https://docs.mem0.ai/platform/cli) [Platform]: Use when the user wants to manage Platform memories from the terminal.
@@ -185,8 +192,10 @@ 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
+22 -4
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@@ -14,11 +14,15 @@ Move your Mem0 implementation to managed infrastructure with enterprise features
| --------------------- | -------------- | ---------------------------- |
| Infrastructure & Code | Low (~30 mins) | None (Parallel run possible) |
<Info>
Using Mem0 Open Source with **hosted Qdrant**? You can migrate your existing memories to Mem0 Platform with a one-line script below.
</Info>
<Info>
**Why migrate to Platform?**
- **Time to Market**: Set up in 5 minutes vs 30+ minutes for OSS configuration
- **Enterprise Ready**: SOC2 Type II compliance, GDPR support, audit logs
- **Enterprise Ready**: Audit logs, workspace governance, and dedicated support
- **Advanced Features**: Webhooks, memory export, analytics dashboard, custom categories
- **Multi-tenancy**: Organizations, projects, and team management out of the box
- **Zero Infrastructure**: No vector database, LLM provider, or maintenance overhead
@@ -34,7 +38,21 @@ Move your Mem0 implementation to managed infrastructure with enterprise features
## Migrate
### 1. Install or Update SDK
### 1. Import Memories Into Platform
If your Mem0 Open Source setup uses **hosted Qdrant** as the vector store, you can import your existing memories to Mem0 Platform with one command:
```bash
curl -fsSL https://raw.githubusercontent.com/mem0ai/mem0/main/scripts/oss-to-platform-migrate.sh | bash
```
<Note>
This migration script currently supports **hosted Qdrant only**. Support for local Qdrant, pgvector, and other vector stores is coming soon.
</Note>
If you are using a different vector store and want to migrate to Platform, please contact Mem0 support and we’ll send you a custom migration script for your setup.
### 2. Install or Update SDK
Ensure you have the latest version of the SDK, which supports both OSS and Platform clients.
@@ -42,7 +60,7 @@ Ensure you have the latest version of the SDK, which supports both OSS and Platf
pip install mem0ai --upgrade
```
### 2. Update Initialization
### 3. Update Initialization
Switch from the local `Memory` class to the managed `MemoryClient`.
@@ -75,7 +93,7 @@ client = MemoryClient(api_key="m0-...")
Run `client.get_all(filters={"user_id": "test_connection"})` to verify your API key works. It should return an empty list or valid results.
</Info>
### 3. Update Retrieval Calls (Critical)
### 4. Update Retrieval Calls (Critical)
<Warning>
**Critical Change**: Platform uses v2 endpoints that require filtering parameters to be nested inside a `filters` dictionary.
+3 -2
View File
@@ -42,7 +42,7 @@ Previously, when an agent said something like "I've booked your flight for March
### Retrieval is hybrid now
Search now uses hybrid retrieval, which improves ranking quality — especially for queries involving exact keywords, proper nouns, or entities that appear across multiple memories. The response shape is unchanged:
Search now uses hybrid retrieval, which improves ranking quality — especially for queries involving exact keywords, proper nouns, entities that appear across multiple memories, and time-aware queries (via Temporal Reasoning). The response shape is unchanged:
```json
{
@@ -58,7 +58,7 @@ Search now uses hybrid retrieval, which improves ranking quality — especially
}
```
The top-level `score` remains a `[0, 1]` value. Relative ranking between results stays comparable to v2, but absolute numbers shift since the scoring method changed — retune any hard thresholds in your app against representative queries.
The top-level `score` remains a `[0, 1]` value. Relative ranking between results stays comparable to v2, but absolute numbers shift since the scoring method changed — retune any hard thresholds in your app against representative queries. Temporal signals are applied internally during ranking and are not returned as extra client-facing fields.
## API Changes
@@ -289,6 +289,7 @@ If your application previously read graph relations from the API response (`rela
- **V1 and V2 endpoints continue to work.** There is no requirement to migrate to V3 endpoints immediately.
- **Existing memories are preserved.** The new algorithm does not modify or re-process previously stored memories.
- **Search response shape is unchanged.** The top-level `score` and `results[]` array are the same; existing code that reads `score` continues to work. What changed is the scoring method behind the number (multi-signal fusion instead of pure cosine), so the absolute values shift even when ranking stays comparable.
- **Search remains backward-compatible at the top level.** Existing code that reads `results[]` and `score` continues to work. Temporal signals are applied internally during retrieval and do not change the client response shape.
- **List response shape changed.** `get_all` now returns a paginated envelope (`{count, next, previous, results}`) instead of a bare `{results: [...]}`. Update code that reads `response["results"]` to continue working, or switch to the client SDKs which handle both shapes.
## Performance Improvements
+17 -2
View File
@@ -419,7 +419,7 @@
},
"results": {
"type": "array",
"description": "Array of results produced by the event."
"description": "Array of results produced by the event. For add events, this confirms the write completed; temporal reasoning enrichment runs asynchronously by default."
},
"created_at": {
"type": "string",
@@ -2071,7 +2071,7 @@
"memories"
],
"summary": "Search memories (V3)",
"description": "Relevance-ranked search across stored memories. V3 uses hybrid retrieval — the returned `score` is a combined `[0, 1]` value; per-signal component scores are not exposed on the response. Entity IDs **must** be passed inside the `filters` object — top-level `user_id` / `agent_id` / `run_id` are rejected with 400. At least one entity ID is required.",
"description": "Relevance-ranked search across stored memories. V3 uses hybrid retrieval and can also apply temporal reasoning for time-aware queries. Entity IDs **must** be passed inside the `filters` object — top-level `user_id` / `agent_id` / `run_id` are rejected with 400. At least one entity ID is required.",
"operationId": "memories_search_v3",
"requestBody": {
"required": true,
@@ -2112,6 +2112,21 @@
"type": "boolean",
"default": false,
"description": "Apply the managed reranker for better ordering (adds latency)."
},
"reference_date": {
"oneOf": [
{
"type": "integer"
},
{
"type": "number"
},
{
"type": "string"
}
],
"nullable": true,
"description": "Optional query anchor time for relative temporal interpretation. Accepts Unix epoch, YYYY-MM-DD, or ISO datetime."
}
}
},
+106
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@@ -0,0 +1,106 @@
---
title: Sign up as an agent
description: "Zero-friction signup for AI agents — mint a working Mem0 API key in under five seconds. No email, no dashboard, no OTP."
icon: "robot"
iconType: "solid"
---
If you're an AI agent (Claude Code, Cursor, Codex, Cline, Aider, Windsurf, or any other autonomous coding tool), you don't need a human to set up Mem0 for you. Four commands — install, sign up, push a memory, search it — and you have persistent memory.
## The 4-command demo
<CodeGroup>
```bash npm
# 1. Install
npm install -g @mem0/cli
# 2. Sign up as an agent (replace `claude-code` with your name)
mem0 init --agent --agent-caller claude-code
# 3. Push a memory
mem0 add "I am using mem0"
# 4. Verify
mem0 search "am I using mem0"
```
```bash pip
# 1. Install
pip install mem0-cli
# 2. Sign up as an agent (replace `claude-code` with your name)
mem0 init --agent --agent-caller claude-code
# 3. Push a memory
mem0 add "I am using mem0"
# 4. Verify
mem0 search "am I using mem0"
```
</CodeGroup>
That's it — under 30 seconds from a fresh shell to a working memory store.
## Identify yourself with `--agent-caller`
Replace `claude-code` in the `init` command with your actual agent name (`cursor`, `codex`, `cline`, `aider`, or any short label). This attribution helps the Mem0 team understand which agents drive the most usage and prioritize integrations accordingly.
<Tip>
**Forgot `--agent-caller` on init?** Run `mem0 identify <your-name>` after the fact — same key, just back-fills the attribution. Idempotent.
</Tip>
## What happened when you ran `mem0 init --agent`?
- A **shadow account** was minted on the Mem0 backend with a fresh API key.
- The key was saved to `~/.mem0/config.json` (mode 0600) on the machine you ran the command on.
- A default `user_id` was provisioned so `mem0 add` / `mem0 search` work without explicit scope flags.
- The account is **unclaimed** — no human owns it yet.
Every command run against this key prints a one-line reminder asking you to surface the claim instructions to your human user.
## Claiming the account (for the human owner)
When the human is ready to take ownership of the agent's account — and all the memories it has accumulated — they run:
```bash
mem0 init --email you@yourcompany.com
```
The CLI detects the existing Agent Mode config, sends a verification code, and upgrades the shadow account in-place:
- **The API key never changes** — the agent isn't disrupted.
- **All memories transfer** to the human's account.
- **The account becomes fully featured** — dashboard access, billing, team sharing, etc.
Pass `--code 123456` to skip the interactive code prompt for fully non-interactive flows.
## Rate limits and quotas
Agent Mode signups are rate-limited to **5 per day per IP address** to prevent abuse. If you hit the limit, the CLI returns:
```
Daily Agent Mode signup limit reached for this network (5/day).
Try again from a different IP or after midnight UTC.
```
Unclaimed agent accounts get the standard Mem0 free-tier quotas. The human owner can upgrade after claiming.
## What's next
<CardGroup cols={2}>
<Card title="CLI Reference" icon="terminal" href="/platform/cli">
Full command-by-command reference for `mem0 add`, `mem0 search`, `mem0 list`, and the rest.
</Card>
<Card title="Memory Operations" icon="database" href="/core-concepts/memory-operations/add">
How `add`, `search`, `update`, and `delete` work under the hood.
</Card>
<Card title="Mem0 MCP" icon="plug" href="/platform/mem0-mcp">
Connect agents to Mem0 via the Model Context Protocol — alternative integration path.
</Card>
<Card title="Platform Overview" icon="star" href="/platform/overview">
The full Mem0 Platform feature set once you claim your account.
</Card>
</CardGroup>
+94
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@@ -25,6 +25,10 @@ pip install mem0-cli
```
</CodeGroup>
<Tip>
**Looking for Agent Mode signup?** See [Sign up as an agent](/platform/agent-signup) — install, signup, first memory in four commands.
</Tip>
## Authentication
Run the interactive setup wizard to configure your API key:
@@ -95,6 +99,10 @@ mem0 init --api-key m0-xxx --user-id alice --force
| `--code` | Verification code (use with `--email` for non-interactive login) |
| `--force` | Overwrite existing config without confirmation |
<Note>
AI agents should use `mem0 init --agent` — see [Sign up as an agent](/platform/agent-signup).
</Note>
### `mem0 add`
Add a memory from text, a JSON messages array, a file, or stdin.
@@ -263,6 +271,92 @@ Print the CLI version.
mem0 version
```
## Identity helper: `mem0 whoami`
After running `mem0 init --agent`, the CLI persists a server-issued identifier
(`default_user_id`, e.g. `user_a1b2c3d4e5f6`) in `~/.mem0/config.json`. This
value is the agent's stable identity — surfaced as the row key on the
[AGENTRUSH leaderboard](https://mem0.ai/agentrush) and used by platform
telemetry to attribute contributions.
Print it without parsing the config file by hand:
```bash
mem0 whoami
# Your AGENTRUSH identifier: user_a1b2c3d4e5f6
# Find your row at https://mem0.ai/agentrush
```
No network call. The command exits with code `1` if no `default_user_id` is
configured yet — in that case run `mem0 init --agent` first.
## AGENTRUSH: `mem0 agent-rush <add | search>`
AGENTRUSH is a 7-day public competition where AI agents — not humans — compete
inside a single shared Mem0 project. Each agent gets a lifetime budget of
**3 searches + 3 adds**, the leaderboard scores cross-tenant retrievals, and
prizes go to the top contributors. See [mem0.ai/agentrush](https://mem0.ai/agentrush)
for current event details.
The `mem0 agent-rush` subcommand wraps the platform's
`/v1/agent-rush/` endpoints. Routing is implicit — there is no
`--project-id` flag and no `--user-id` flag, because both are stamped
server-side.
### Bootstrap once, then play
```bash
# 1. Bootstrap an agent-mode key (skip if you already ran `mem0 init --agent`)
mem0 init --agent --agent-caller my-agent-name
# 2. Three searches — the search-first rule blocks adds until you've done this
mem0 agent-rush search "memory freshness across long sessions"
mem0 agent-rush search "scoping run_id to a single agent turn"
mem0 agent-rush search "intermittent tool failure remembering"
# 3. Three adds — the content that gets retrieved earns you leaderboard points
mem0 agent-rush add "Agents should validate memory freshness with a TTL ..."
mem0 agent-rush add "Scoping memories by run_id avoids cross-session ..."
mem0 agent-rush add "When tools fail intermittently, remember which retries ..."
# 4. Check your row
mem0 whoami
# Then visit https://mem0.ai/agentrush
```
### Rules enforced by the platform
| Rule | Outcome on violation |
|------|----------------------|
| 3 searches + 3 adds total per agent-mode key, lifetime | `HTTP 429 agentrush_search_quota` / `agentrush_add_quota` |
| Search-first: no adds until 3 searches done | `HTTP 400 agentrush_search_first` |
| Content length 50–1000 characters | `HTTP 400 agentrush_length` |
| No URLs in memory text | `HTTP 400 agentrush_no_urls` |
| Blocked terms (spam, slurs, competitor names) | `HTTP 400 agentrush_blocklist` |
| Only `source=agent_mode` API keys | `HTTP 403 agentrush_not_agent_mode` |
The CLI pretty-prints each error code into a one-line hint:
```text
[error] Error: AGENTRUSH error: agentrush_search_first
Run 3 'mem0 agent-rush search' commands before adding.
```
### Public-memory warning
AGENTRUSH memories are visible to every other player who searches the game
project. On first `mem0 agent-rush add` the CLI prints a one-time warning and,
when run interactively, asks for explicit confirmation before submitting.
**Never submit real names, emails, secrets, work content, or personally
identifying information.** The acknowledgement is stored under
`agent_rush.acknowledged_at` in `~/.mem0/config.json` so you are only asked
once per machine.
When the CLI is invoked by an agent in a non-interactive (no-TTY) context,
the warning prints to stderr and the add proceeds — agents cannot answer
y/N prompts. Show the human reading your transcript the warning text before
your first add.
## Output formats
All commands support the `--output` flag to control how results are displayed:
+18
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@@ -142,6 +142,24 @@ iconType: "solid"
Setting this environment variable will prevent Mem0 from collecting and sending any usage data, ensuring complete privacy for your application.
</Accordion>
<Accordion title="How do I delete my Mem0 account?">
You can delete your Mem0 account at any time directly from the dashboard:
1. Sign in at [app.mem0.ai](https://app.mem0.ai).
2. Go to **Settings → Account**.
3. Click **Delete account** and confirm.
Deletion is immediate and irreversible. The following is removed:
- Your user profile and login credentials
- All memories, agents, and runs you created
- API keys and access tokens issued to your account
- Organizations you solely own, along with their data
- Your membership in any shared organizations (the orgs themselves are not affected)
Any application still using your old API keys will start receiving `401 Unauthorized` responses immediately. If you'd like to use Mem0 again later, you can create a new account at any time — it will start fresh with no data carried over.
</Accordion>
</AccordionGroup>
+3 -1
View File
@@ -53,7 +53,7 @@ For detailed per-client instructions, see the [Mem0 MCP Quickstart](/platform/me
## Available tools
The MCP server exposes 9 memory tools to your AI client:
The MCP server exposes 11 memory tools to your AI client:
| Tool | Purpose |
|------|---------|
@@ -66,6 +66,8 @@ The MCP server exposes 9 memory tools to your AI client:
| `delete_entities` | Remove user/agent/app entities |
| `get_memory` | Retrieve single memory by ID |
| `list_entities` | View stored entities |
| `list_events` | List memory operation events with filters and pagination |
| `get_event_status` | Check the status of an async memory operation by `event_id` |
## How it works
+191
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@@ -0,0 +1,191 @@
---
title: Memory Decay
description: "Boost recently-used memories and gently dampen stale ones at search time, without filtering anything out."
---
# Memory Decay
Older memories drift in relevance at different speeds. A user's coffee order matters every morning; a one-off project name from last quarter rarely matters again. Memory Decay makes that intuition explicit at search time: every time a memory is returned in a search it gets a small reinforcement, and memories that haven't been touched in a while have their ranking score gently dampened.
It is **a soft ranking bias, never a filter.** Decay never zeroes a candidate out — at worst it scales its score by `0.3×`. Anything that would have surfaced without decay can still surface with decay on, just with a different ranking among similarly-scored results.
<Info>
**Use Memory Decay when…**
- Search results are crowded with old facts the user no longer cares about.
- You want recently-used memories to drift to the top automatically — without writing custom scoring logic.
- You want this preference applied per project so cohorts can be compared side-by-side.
</Info>
<Warning>
Memory Decay is **opt-in per project** and **off by default**. Search behavior is bit-identical to today until you turn it on. The toggle applies to v3 search only.
</Warning>
## How it works
Every memory carries a small piece of bookkeeping: when was it last retrieved, and how often. Memory Decay turns that history into a *scaling factor* in the range `0.3×` to `1.5×` and multiplies it into the ranking score at search time.
| Memory state | Scaling factor | Ranking effect |
|---|---|---|
| Just accessed | ≈ **1.5×** | Strong boost |
| Touched today | 1.2 – 1.4× | Mild boost |
| Idle for a few days | 0.6 – 1.0× | Mild dampening |
| Idle for weeks | 0.4 – 0.6× | Stronger dampening |
| Idle for many months / years | ≈ **0.3×** | Floor — never lower |
The bounds matter: `0.3` is the floor and `1.5` is the ceiling, so decay can meaningfully reorder candidates without ever dominating the underlying relevance score.
At search time the pipeline:
1. Widens the candidate pool (`top_k × 3`, with a floor of 50) so reordering has room.
2. Multiplies each candidate's score by its scaling factor.
3. Sorts on the unclamped product so the full `0.3×–1.5×` range can rearrange candidates.
4. Returns the public `score` clamped to `[0, 1]` so the API contract is preserved.
5. Truncates to the `top_k` you requested.
6. Records a fire-and-forget reinforcement against each returned memory — its access history grows by one, capped at the most recent 20 touches.
Memories created before decay was enabled don't yet have an access history. They use a sensible fallback: their `updated_at` is treated as a single past touch, so the same scale above applies based on how stale that update is — a recently-updated legacy memory enters near the neutral band, a long-stale one sits closer to the floor. Once surfaced in a search after decay is on, they accumulate access history naturally and behave like any other memory.
## Configure access
- Set `MEM0_API_KEY` in your environment, or pass it to the SDK constructor.
- Initialize the client with the organization and project you want to scope to.
The toggle lives on the project. You enable decay by patching the project's `decay` field; everything else — your `add` calls, your `search` calls, your application code — stays exactly the same.
## Enable decay for a project
### 1. Turn the flag on
The toggle is exposed on the standard project-update endpoint, the same place where `multilingual` and `custom_categories` live.
<CodeGroup>
```python Python
client.project.update(decay=True)
```
```javascript JavaScript
await client.project.update({ decay: true });
```
```bash cURL
curl -X PATCH https://api.mem0.ai/api/v1/orgs/organizations/$ORG_ID/projects/$PROJECT_ID/ \
-H "Authorization: Token $MEM0_API_KEY" \
-H "Content-Type: application/json" \
-d '{"decay": true}'
```
```json Response
{ "message": "Updated decay" }
```
</CodeGroup>
### 2. Confirm the state
`decay` is returned on every project read. To fetch only this field, use `?fields=decay`.
<CodeGroup>
```python Python
response = client.project.get(fields=["decay"])
print(response["decay"])
```
```javascript JavaScript
const response = await client.project.get({ fields: ["decay"] });
console.log(response.decay);
```
```bash cURL
curl "https://api.mem0.ai/api/v1/orgs/organizations/$ORG_ID/projects/$PROJECT_ID/?fields=decay" \
-H "Authorization: Token $MEM0_API_KEY"
```
```json Response
{ "decay": true }
```
</CodeGroup>
### 3. Turn it back off
The toggle is fully reversible. Setting it to `false` immediately restores the pre-decay ranking; nothing about your stored memories is modified or lost.
<CodeGroup>
```python Python
client.project.update(decay=False)
```
```javascript JavaScript
await client.project.update({ decay: false });
```
```bash cURL
curl -X PATCH https://api.mem0.ai/api/v1/orgs/organizations/$ORG_ID/projects/$PROJECT_ID/ \
-H "Authorization: Token $MEM0_API_KEY" \
-H "Content-Type: application/json" \
-d '{"decay": false}'
```
</CodeGroup>
<Note>
The toggle is idempotent. Re-applying the same value is a no-op, and access history accumulated while decay was on is preserved if you flip it back on later.
</Note>
## What changes when decay is on
- **Search ranking reorders.** A relevant memory you reinforced an hour ago will tend to outrank an equally-relevant memory that was last touched a month ago.
- **The candidate pool over-fetches** to give the scaling factor room to reorder. You still get exactly the `top_k` you requested, but the items returned can come from a deeper slice of the pre-decay ranking than before.
- **The public `score` field stays in `[0, 1]`.** Even when the internal product exceeds 1, the field returned to the client is clamped, so existing assertions and downstream UI logic continue to work.
## What stays the same
- **Public API shape** — every endpoint accepts the same parameters and returns the same fields. You don't touch your client code.
- **Threshold semantics on the request side** — your `threshold` is still applied during candidate selection.
- **Memory creation and storage** — every new memory still lands the same way. Decay is a search-time concern.
- **Per-memory data** — categories, metadata, timestamps, embeddings: untouched.
<Warning>
Because the scaling factor is applied *after* the threshold filter has already run, an item that passed the request `threshold` can come back with a public `score` slightly below it (a stale candidate dampened by `0.3×`). This is intentional — decay is a soft bias, not a filter. If you require a hard `score >= threshold` invariant on the response, filter client-side after the call.
</Warning>
## Lifecycle of a memory under decay
| Stage | Scaling factor | Effect |
|---|---|---|
| Just added | ≈ 1.5× | Strong boost — fresh facts surface easily. |
| Reinforced on a recent search | 1.2 – 1.5× | Sustains its boost for the next several searches. |
| Idle for a few days | 0.6 – 1.0× | Falls back into the neutral band. |
| Idle for weeks | 0.4 – 0.6× | Mild dampening — can still surface for strong matches. |
| Pre-decay legacy memory (no access history) | 0.3 – 1.0× | Falls back to `updated_at`: recently-updated entries land near 1.0×, long-stale entries approach the 0.3× floor. |
The reinforcement is bounded: each memory tracks at most the last 20 access timestamps, so the boost stays well-behaved no matter how many times a memory is retrieved.
## FAQ
**Will decay ever drop a result that would otherwise surface?**
No. The floor is `0.3×` — the scaling factor can dampen a score, never zero it. Threshold filtering happens *before* decay, so any candidate that cleared the threshold is in the pool decay reorders.
**Why is the public score sometimes below my requested threshold?**
The threshold is applied to the candidate pool pre-decay; the scaling factor then reshapes scores in the `0.3×–1.5×` band. A stale-but-relevant candidate can come back with a final score slightly under your threshold by design — the candidate stays visible but visibly dampened. Filter client-side if you need a hard floor on the response.
**Does decay change how I add memories?**
No. The `client.add(...)` path is unchanged. Decay is a search-time ranking adjustment.
**What if I had memories before turning decay on?**
They use a fallback: the memory's `updated_at` is treated as a single historical touch, so the same scaling applies based on how stale that update is — a recently-updated legacy memory enters near the neutral band (~1.0×), a long-stale one closer to the floor (~0.3×). Once retrieved they accumulate access history and behave like any other memory.
**Can I tune how aggressively decay scales scores?**
Not in this version. The current scaling is calibrated to be conservative — wide enough to meaningfully reorder candidates, narrow enough to never dominate the underlying relevance score. Per-project tuning is on the roadmap.
**Can I see the scaling factor per result?**
Internal scoring details are persisted on the search Event for support and debugging. They aren't exposed in the public response by design — the response surface stays a single `score` field.
**Does decay interact with reranking?**
Yes — they layer cleanly. The reranker produces a richer relevance score; decay then biases that score by reinforcement history before final truncation to `top_k`.
## What's next
This release is deliberately the simplest version of decay we could ship — every memory contributes to ranking through its access history alone, so the signal can be evaluated in isolation. On the roadmap:
- **Category-aware weighting.** A fact tagged `health` will be able to carry more weight than a passing observation tagged `misc`, so important categories don't get dampened the same way as noise.
- **Auto-tuning per project.** Project-scoped automatic adjustment of how aggressively decay scales scores, based on observed access patterns — replacing the fixed scaling band with one that fits your workload.
Both extensions are forward-compatible — no migration on your side will be needed when they ship.
@@ -0,0 +1,145 @@
---
title: Temporal Reasoning
description: "Time-aware memory retrieval for Mem0 Platform v3 so queries like 'last week', 'upcoming', and 'right now' return the right memories."
icon: "clock"
badge: "v3"
---
Some memories matter because of **when** they happened, not just because they sound similar. Temporal Reasoning lets Mem0 Platform v3 understand time-aware queries and return the most contextually appropriate results.
<Info>
**Use Temporal Reasoning when…**
- Users ask questions like "what happened last week?" or "what do I have coming up?"
- Your app stores both past events and future plans for the same person
- You want time-aware retrieval without building your own date-parsing layer
</Info>
<Warning>
Temporal Reasoning is a **Mem0 Platform v3** feature. It is not available on OSS memory stores or older Platform endpoints.
</Warning>
## Configure access
Confirm your `MEM0_API_KEY` is set and that you are using the v3 Platform client:
```python
from mem0 import MemoryClient
client = MemoryClient(api_key="your-api-key")
```
## How it works
When a memory describes an event, a future plan, or an ongoing state, Temporal Reasoning recognizes the time context so the right results surface at search time.
A query like `what did I do last week?` should return a completed past event — not an upcoming appointment and not a stable fact that hasn't changed. Temporal Reasoning handles that distinction automatically.
### Memory types Temporal Reasoning handles
| Type | What it represents | Example |
| --- | --- | --- |
| Dated occurrence | Something that happened at a known time | "I finished the Q1 review on March 10, 2025." |
| Future plan | A future commitment or scheduled item | "I have a dentist appointment on March 18, 2025." |
| Ongoing state | A fact that remains true over time | "I am the product lead at Acme Corp." |
| Relationship | A durable connection between people or entities | "Priya manages Jordan." |
| Preference | A stable preference or habit | "I prefer morning meetings." |
Results come back in the normal search response shape — Temporal Reasoning affects ranking, not the response format.
## Configure it
Temporal Reasoning is enabled by default for all v3 searches and writes. There is no per-request toggle.
Two parameters give you precise control when you need it:
- `timestamp` on `add()` — anchors an imported memory to the time it actually happened, rather than the time it was added to Mem0
- `reference_date` on `search()` — resolves relative phrases like `last week` against a fixed point in time
<CodeGroup>
```python Python
from datetime import datetime, timezone
from mem0 import MemoryClient
client = MemoryClient(api_key="your-api-key")
# Import a historical memory anchored to when it happened
client.add(
[{"role": "user", "content": "I finished the Q1 review on March 10, 2025."}],
user_id="jordan",
timestamp=int(datetime(2025, 3, 10, tzinfo=timezone.utc).timestamp()),
)
# Search with a relative query anchored to a known date
results = client.search(
"what did I do last week?",
filters={"user_id": "jordan"},
reference_date="2025-03-21T00:00:00Z",
)
```
```javascript JavaScript
import { MemoryClient } from "mem0ai";
const client = new MemoryClient({ apiKey: "your-api-key" });
// Import a historical memory anchored to when it happened
await client.add(
[{ role: "user", content: "I finished the Q1 review on March 10, 2025." }],
{
userId: "jordan",
timestamp: Math.floor(new Date("2025-03-10T00:00:00Z").getTime() / 1000),
}
);
// Search with a relative query anchored to a known date
const results = await client.search("what did I do last week?", {
filters: { user_id: "jordan" },
referenceDate: "2025-03-21T00:00:00Z",
});
```
</CodeGroup>
<Tip>
`reference_date` is especially useful in automated tests and demos because it makes relative phrases like `last week` resolve consistently every time.
</Tip>
## Supported query patterns
<AccordionGroup>
<Accordion title="Historical questions">
Examples: `last week`, `last month`, `in March 2025`, `on 2025-03-10`
</Accordion>
<Accordion title="Upcoming questions">
Examples: `upcoming`, `next week`, `tomorrow`, `what do I have coming up?`
</Accordion>
<Accordion title="Current-state questions">
Examples: `right now`, `currently`, `where do I work now?`
</Accordion>
<Accordion title="As-of questions">
Examples: `as of March 2025`, `where was I living as of 2024?`
</Accordion>
<Accordion title="Duration questions">
Examples: `how long have I lived here?`, `since when have I worked there?`
</Accordion>
</AccordionGroup>
## Verify the feature is working
- Run a temporal search with a time-aware query (e.g., "what did I do last week?") and confirm the memory that fits the time window ranks first.
- Use `reference_date` in test queries so relative phrases resolve consistently across runs.
- For backfilled data, pass `timestamp` on `add()` to confirm the memory reflects the right point in time.
## Best practices
- Use explicit dates in source conversations when events or plans matter temporally.
- Pass `timestamp` during historical imports so the ingestion time does not become the only time anchor.
- Scope searches with `filters` so time-aware ranking operates inside the right user boundary.
- Use `reference_date` in automated tests and reproducible demos.
<CardGroup cols={1}>
<Card title="Memory Timestamps" icon="calendar" href="/platform/features/timestamp">
Anchor imported memories to when they actually happened.
</Card>
</CardGroup>
<Snippet file="get-help.mdx" />
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@@ -46,6 +46,8 @@ The MCP server exposes these memory tools to your AI client:
| `delete_all_memories` | Bulk delete all memories in scope |
| `delete_entities` | Delete a user/agent/app/run entity and its memories |
| `list_entities` | Enumerate users/agents/apps/runs stored in Mem0 |
| `list_events` | List memory operation events with filters and pagination |
| `get_event_status` | Check the status of an async memory operation by `event_id` |
---
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@@ -12,7 +12,7 @@ Mem0 is the memory engine that keeps conversations contextual so users never rep
- **Personalized replies**: Memories persist across users and agents, cutting prompt bloat and repeat questions.
- **Hosted stack**: Mem0 runs the vector store, graph services, and rerankers—no provisioning, tuning, or maintenance.
- **Enterprise controls**: SOC 2, audit logs, and workspace governance ship by default for production readiness.
- **Enterprise controls**: Audit logs and workspace governance ship by default for production readiness.
<AccordionGroup>
<Accordion title="What you get with Mem0 Platform" icon="sparkles">
@@ -22,7 +22,7 @@ Mem0 is the memory engine that keeps conversations contextual so users never rep
| Fast setup | Add a few lines of code and you’re production-ready—no vector database or LLM configuration required. |
| Production scale | Automatic scaling, high availability, and managed infrastructure so you focus on product work. |
| Advanced features | Graph memory, webhooks, multimodal support, and custom categories are ready to enable. |
| Enterprise ready | SOC 2 Type II, GDPR compliance, and dedicated support keep security and governance covered. |
| Enterprise ready | Audit logs, workspace governance, and dedicated support keep security and governance covered. |
</Accordion>
</AccordionGroup>
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@@ -7,6 +7,10 @@ iconType: "solid"
Get started with Mem0 Platform's hosted API in under 5 minutes. This guide shows you how to authenticate and store your first memory.
<Note>
**Are you an AI agent?** See [Sign up as an agent](/platform/agent-signup) — mint a working API key in four commands, no email or dashboard required.
</Note>
## Prerequisites
- Mem0 Platform account (<a href="https://app.mem0.ai?utm_source=oss&utm_medium=platform-quickstart" rel="nofollow">Sign up here</a>)
+24 -2
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@@ -22,13 +22,35 @@ We follow the llms.txt standard:
## Agent Skills
Teach your coding assistant how to build with Mem0:
Mem0 ships two kinds of skills for AI coding assistants. Both work with Claude Code, Codex, Cursor, Windsurf, OpenCode, OpenClaw, and any assistant that supports the skills standard.
### Reference skills — always on
Teach your assistant Mem0's SDK surface so it writes correct code in everyday development:
```bash
npx skills add https://github.com/mem0ai/mem0 --skill mem0
npx skills add https://github.com/mem0ai/mem0 --skill mem0-cli
npx skills add https://github.com/mem0ai/mem0 --skill mem0-vercel-ai-sdk
```
Works with Claude Code, Cursor, Windsurf, and any assistant that supports skills. Once installed, your assistant understands Mem0's full API, framework integrations, and common patterns.
- `mem0` — Python and TypeScript SDKs (Platform + OSS), plus framework integrations (LangChain, CrewAI, OpenAI Agents, LangGraph, LlamaIndex, etc.)
- `mem0-cli` — terminal workflows for the `mem0` CLI (both Node and Python builds)
- `mem0-vercel-ai-sdk` — `@mem0/vercel-ai-provider` and `createMem0`
### Pipeline skills — run on demand
Let your assistant execute an end-to-end workflow in an existing repo. Invoked as slash commands:
```bash
npx skills add https://github.com/mem0ai/mem0 --skill mem0-integrate
npx skills add https://github.com/mem0ai/mem0 --skill mem0-test-integration
```
- `/mem0-integrate` — wire Mem0 into an existing repository using a goal-driven, test-first pipeline. Detects the stack, asks whether to use Platform or OSS, writes failing tests first, and keeps the integration additive and feature-flagged.
- `/mem0-test-integration` — verify what `/mem0-integrate` produced. Runs the repo's native test suite and a real end-to-end smoke flow against your API key, then produces a scorecard.
See the [skills index](https://github.com/mem0ai/mem0/tree/main/skills) for the full catalog.
## MCP Server Setup
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@@ -1,6 +1,6 @@
{
"name": "mem0",
"version": "0.1.1",
"version": "0.1.3",
"description": "Mem0 memory layer for AI applications. Add persistent memory, personalization, and semantic search to Claude workflows using the Mem0 Platform MCP server.",
"author": {
"name": "Mem0",
+45
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@@ -0,0 +1,45 @@
# Changelog
All notable changes to the Mem0 plugin will be documented in this file.
## 0.1.3
### Fixed
- **user_id resolution no longer derives from `MEM0_API_KEY`.** v0.1.2 changed the resolver to fall back to `"mem0-" + sha256(MEM0_API_KEY)[:12]` ahead of `$USER`, which silently moved every existing user to a new bucket on update. Memories written under the previous `$USER` value became unreachable from the plugin. Resolution is now back to `MEM0_USER_ID` → `$USER` → `"default"`.
- Dropped the "regardless of which machine you're on" line from the SessionStart bootstrap, since cross-machine consolidation now requires setting `MEM0_USER_ID` explicitly.
### Notes for users upgrading from 0.1.2
- The `~/.mem0/identity.json` cache file is no longer read or written. Safe to delete.
- If you wrote memories during the v0.1.2 window, they live under `mem0-<sha256(api_key)[:12]>`. To recover: temporarily `export MEM0_USER_ID=mem0-<hash>`, search/export, then unset.
- Want a single bucket across machines (the original goal of #5076)? Set `MEM0_USER_ID` explicitly in your shell profile. The plugin will not auto-derive one.
## 0.1.2
### Added
- Deterministic `user_id` resolver (`_identity.sh` / `_identity.py`) — **reverted in 0.1.3, see above.**
- SessionStart-compact handler (`capture_compact_summary.py`) that stores the post-compaction summary as a memory with `metadata.type=compact_summary`.
- Coding-taxonomy setup script (`setup_coding_categories.py`) — one-shot `project.update(custom_categories=[...])` for `architecture_decisions`, `anti_patterns`, `task_learnings`, `tooling_setup`, `bug_fixes`, `coding_conventions`, `user_preferences`.
- Opt-in hook logging via `MEM0_DEBUG=1` → `~/.mem0/hooks.log`.
- `mem0-mcp` skill replacing the Claude-Code-specific `mem0-codex` skill.
### Fixed
- `session_id` now written to memory metadata (`on_pre_compact.py`).
- SessionStart bootstrap exits silently when `MEM0_API_KEY` is unset.
- `block_memory_write.sh` regex tightened to `MEMORY.md` / `.claude/memory/*` — no longer blocks `docs/memory/*.md`.
- Removed duplicate PreCompact write path (kept agent-driven, dropped the parallel Python REST entry from `hooks.json` / `cursor-hooks.json`).
- Hook-side captures (`session_state`, `compact_summary`) now set `expiration_date = today + 90 days`.
## 0.1.1
- Cursor plugin fully functional (`#4547`).
- Codex plugin support and integration docs (`#4665`).
- Codex lifecycle hooks via opt-in installer (`#4917`).
- Removed invalid keys from Claude plugin config (`#4821`).
## 0.1.0
- Initial release: Mem0 plugin for Claude Code and Cursor (`#4518`).
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@@ -2,6 +2,18 @@
Add persistent memory to your AI workflows. Store, retrieve, and manage memories across sessions using the Mem0 Platform. Works with **Claude Code** (CLI), **Claude Cowork** (desktop app), **Cursor**, and **Codex**.
## Quick path for agents
If you're an AI agent setting up Mem0 autonomously (no human dashboard signup available), run:
```bash
mem0 init --agent --json
```
This mints an evaluation API key in <5 seconds — no email, no OTP, no browser. The key is written to your config and exported as `MEM0_API_KEY` for the current shell. Use it immediately against the Mem0 Platform or the MCP server. The human owner can later run `mem0 init --email <their-email>` to claim ownership: memories transfer, the same API key keeps working, and the agent isn't disrupted.
Humans setting up Mem0 by hand should continue with Step 1 below.
## Step 1: Set your API key
> **You must complete this step before installing the plugin.**
@@ -157,6 +169,32 @@ After installing, confirm the MCP server is connected:
- **Mem0 SDK Skill** — Guides the AI on how to integrate the Mem0 SDK (Python & TypeScript) into your applications.
- **Memory Protocol Skill** — Codex-specific skill that instructs the agent to retrieve relevant memories at task start, store learnings on completion, and capture session state before context loss. Complements the lifecycle hooks on Codex.
## Updating the plugin
When the plugin updates (new version pulled from the marketplace, or a fresh local install), the MCP server connection in your existing Claude Code / Cursor / Codex session is left holding a stale handle and stops responding. **Restart your client to reconnect:**
- **Claude Code:** run `/restart` in the prompt, or close and reopen the CLI.
- **Cursor:** quit and relaunch.
- **Codex:** restart the editor session.
Your `MEM0_API_KEY` doesn't need to be re-entered — the auth header is re-read from your environment on the new session. The plugin's MCP config uses `${MEM0_API_KEY}` interpolation at session start, not at install time, so as long as the env var is set persistently (in your shell profile or `~/.claude/settings.json` `env` block), reconnection is automatic on restart.
If reconnection still fails after a restart, check that `MEM0_API_KEY` is reachable in the new shell (`echo $MEM0_API_KEY`) and confirm you're using a key that starts with `m0-` (from https://app.mem0.ai/dashboard/api-keys, not a legacy token).
## Optional: tune categories for coding workflows
mem0 auto-tags every memory with one or more `categories` from a project-level list. The default list is consumer-oriented (`food`, `hobbies`, `music` …) — useful for chat assistants, less so for code. A one-shot script in this plugin replaces it with a coding-focused taxonomy:
```bash
# Dry-run first -- prints current vs proposed, no changes:
python mem0-plugin/scripts/setup_coding_categories.py
# Actually write:
python mem0-plugin/scripts/setup_coding_categories.py --apply
```
Requires the `mem0ai` Python SDK (`pip install mem0ai`) and `MEM0_API_KEY` set. New memories will then auto-tag against `architecture_decisions`, `anti_patterns`, `task_learnings`, `tooling_setup`, `bug_fixes`, `coding_conventions`, `user_preferences`. Re-run with a different list any time; `project.update(custom_categories=[...])` always replaces.
## MCP Tools
Once installed, the following tools are available:
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@@ -18,7 +18,7 @@
{
"type": "command",
"command": "${CODEX_PLUGIN_ROOT}/scripts/on_user_prompt.sh",
"statusMessage": "Searching mem0 memories...",
"statusMessage": "Checking memory relevance...",
"timeout": 5
}
]
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View File
@@ -15,10 +15,6 @@
"preCompact": [
{
"command": "${CURSOR_PLUGIN_ROOT}/scripts/on_pre_compact.sh"
},
{
"command": "python3 ${CURSOR_PLUGIN_ROOT}/scripts/on_pre_compact.py",
"timeout": 30
}
],
"stop": [
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View File
@@ -30,12 +30,6 @@
"type": "command",
"command": "${CLAUDE_PLUGIN_ROOT}/scripts/on_pre_compact.sh",
"statusMessage": "Preparing pre-compaction summary..."
},
{
"type": "command",
"command": "python3 ${CLAUDE_PLUGIN_ROOT}/scripts/on_pre_compact.py",
"statusMessage": "Saving session state to mem0...",
"timeout": 30
}
]
}
@@ -57,7 +51,7 @@
{
"type": "command",
"command": "${CLAUDE_PLUGIN_ROOT}/scripts/on_user_prompt.sh",
"statusMessage": "Searching mem0 memories...",
"statusMessage": "Checking memory relevance...",
"timeout": 5
}
]
+17
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@@ -0,0 +1,17 @@
"""Resolve mem0 user_id.
Resolution priority:
1. MEM0_USER_ID env var (explicit override)
2. $USER, else "default"
"""
from __future__ import annotations
import os
def resolve_user_id() -> str:
explicit = os.environ.get("MEM0_USER_ID", "").strip()
if explicit:
return explicit
return os.environ.get("USER") or "default"
+16
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@@ -0,0 +1,16 @@
# Source this file. Sets MEM0_RESOLVED_USER_ID.
#
# Resolution priority:
# 1. MEM0_USER_ID env var (explicit override)
# 2. $USER, else "default"
_mem0_resolve_identity() {
if [ -n "${MEM0_USER_ID:-}" ]; then
printf '%s' "$MEM0_USER_ID"
return
fi
printf '%s' "${USER:-default}"
}
MEM0_RESOLVED_USER_ID="$(_mem0_resolve_identity)"
export MEM0_RESOLVED_USER_ID
+5 -1
View File
@@ -13,6 +13,10 @@
set -euo pipefail
if [ -n "${MEM0_DEBUG:-}" ]; then
mkdir -p "$HOME/.mem0" && exec 2>>"$HOME/.mem0/hooks.log"
fi
INPUT=$(cat)
FILE_PATH=$(echo "$INPUT" | jq -r '.tool_input.file_path // .tool_input.path // ""' 2>/dev/null || echo "")
@@ -22,7 +26,7 @@ if [ -z "$FILE_PATH" ]; then
fi
case "$FILE_PATH" in
*/MEMORY.md|*/memory/*.md|*/.claude/*/memory/*)
*/MEMORY.md|*/.claude/memory/*)
echo "BLOCKED: Do not write to $FILE_PATH. Use the mem0 MCP \`add_memory\` tool instead to persist memories. This project uses mem0 for all memory storage." >&2
exit 2
;;
@@ -0,0 +1,172 @@
#!/usr/bin/env python3
"""Capture the post-compaction summary into mem0.
PreCompact hooks fire BEFORE the summary is generated, so they can't
store the actual compact-summary text. This script runs at
SessionStart with source=compact, reads the transcript, finds the
most recent entry flagged isCompactSummary=true, and stores it as a
memory tagged metadata.type=compact_summary.
Input: JSON on stdin with transcript_path, session_id, source
Output: stderr logs only (exit 0 always -- must not block)
Spawned in the background by on_session_start.sh; the user-facing
bootstrap text continues without waiting on the network.
"""
from __future__ import annotations
import json
import logging
import os
import sys
import urllib.error
import urllib.request
from datetime import date, timedelta
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
from _identity import resolve_user_id
log = logging.getLogger("mem0-compact-summary")
log.setLevel(logging.DEBUG)
_handler = logging.StreamHandler(sys.stderr)
_handler.setFormatter(logging.Formatter("[mem0-compact-summary] %(message)s"))
log.addHandler(_handler)
if os.environ.get("MEM0_DEBUG"):
_log_dir = os.path.expanduser("~/.mem0")
try:
os.makedirs(_log_dir, exist_ok=True)
_file_handler = logging.FileHandler(os.path.join(_log_dir, "hooks.log"))
_file_handler.setFormatter(logging.Formatter("[mem0-compact-summary] %(asctime)s %(message)s"))
log.addHandler(_file_handler)
except OSError:
pass
API_URL = "https://api.mem0.ai"
MAX_TAIL_LINES = 2000
MAX_SUMMARY_CHARS = 50000
# Compact summaries describe a single session's state -- stale after a quarter.
COMPACT_SUMMARY_EXPIRY_DAYS = 90
def tail_lines(filepath: str, n: int) -> list[str]:
try:
with open(filepath, "rb") as f:
f.seek(0, 2)
file_size = f.tell()
if file_size == 0:
return []
chunk_size = min(file_size, n * 4096)
f.seek(max(0, file_size - chunk_size))
data = f.read().decode("utf-8", errors="replace")
return data.splitlines()[-n:]
except OSError:
return []
def find_compact_summary(lines: list[str]) -> str:
"""Walk transcript backwards, return text content of the most recent
entry flagged isCompactSummary=true. Empty string if none found."""
for line in reversed(lines):
line = line.strip()
if not line:
continue
try:
entry = json.loads(line)
except json.JSONDecodeError:
continue
if not entry.get("isCompactSummary"):
continue
message = entry.get("message", {})
content = message.get("content", [])
if isinstance(content, str):
return content[:MAX_SUMMARY_CHARS]
if isinstance(content, list):
parts = []
for block in content:
if isinstance(block, str):
parts.append(block)
elif isinstance(block, dict) and block.get("type") == "text":
parts.append(block.get("text", ""))
return "\n".join(parts).strip()[:MAX_SUMMARY_CHARS]
return ""
def store_summary(api_key: str, summary: str, user_id: str, session_id: str) -> bool:
expires = (date.today() + timedelta(days=COMPACT_SUMMARY_EXPIRY_DAYS)).isoformat()
body = {
"messages": [{"role": "user", "content": summary}],
"user_id": user_id,
"metadata": {
"type": "compact_summary",
"source": "session-start-compact",
"session_id": session_id,
},
"infer": False,
"expiration_date": expires,
}
data = json.dumps(body).encode("utf-8")
req = urllib.request.Request(
f"{API_URL}/v1/memories/",
data=data,
headers={
"Content-Type": "application/json",
"Authorization": f"Token {api_key}",
},
method="POST",
)
try:
with urllib.request.urlopen(req, timeout=15) as resp:
if resp.status in (200, 201):
log.info("Compact summary stored")
return True
log.warning("API returned status %d", resp.status)
return False
except urllib.error.URLError as e:
log.warning("API call failed: %s", e)
return False
def main():
api_key = os.environ.get("MEM0_API_KEY", "")
if not api_key:
log.debug("MEM0_API_KEY not set, skipping capture")
return
try:
hook_input = json.loads(sys.stdin.read())
except (json.JSONDecodeError, OSError):
log.debug("No valid JSON on stdin")
return
transcript_path = hook_input.get("transcript_path", "")
if not transcript_path:
log.debug("No transcript_path provided")
return
session_id = hook_input.get("session_id", "")
user_id = resolve_user_id()
lines = tail_lines(transcript_path, MAX_TAIL_LINES)
if not lines:
log.debug("Transcript empty or unreadable: %s", transcript_path)
return
summary = find_compact_summary(lines)
if not summary:
log.debug("No isCompactSummary entry found")
return
log.info("Capturing compact summary (%d chars)", len(summary))
store_summary(api_key, summary, user_id, session_id)
if __name__ == "__main__":
try:
main()
except Exception as e:
log.error("Unexpected error: %s", e)
sys.exit(0)
+26 -4
View File
@@ -18,8 +18,12 @@ import json
import logging
import os
import sys
import urllib.request
import urllib.error
import urllib.request
from datetime import date, timedelta
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
from _identity import resolve_user_id
log = logging.getLogger("mem0-capture")
log.setLevel(logging.DEBUG)
@@ -27,11 +31,25 @@ _handler = logging.StreamHandler(sys.stderr)
_handler.setFormatter(logging.Formatter("[mem0-capture] %(message)s"))
log.addHandler(_handler)
if os.environ.get("MEM0_DEBUG"):
_log_dir = os.path.expanduser("~/.mem0")
try:
os.makedirs(_log_dir, exist_ok=True)
_file_handler = logging.FileHandler(os.path.join(_log_dir, "hooks.log"))
_file_handler.setFormatter(logging.Formatter("[mem0-capture] %(asctime)s %(message)s"))
log.addHandler(_file_handler)
except OSError:
pass
API_URL = "https://api.mem0.ai"
MAX_TAIL_LINES = 500
MAX_USER_MESSAGES = 30
MAX_BASH_COMMANDS = 20
MAX_ASSISTANT_TEXT = 10000
# session_state captures churn fast (active codebase, files in flight). Past
# ~3 months they're stale noise. Durable facts (decisions, conventions) are
# stored separately by the agent without an expiration_date.
SESSION_STATE_EXPIRY_DAYS = 90
def tail_lines(filepath: str, n: int) -> list[str]:
@@ -149,8 +167,9 @@ def build_content(state: dict, source: str) -> str:
return "\n".join(parts)
def store_memory(api_key: str, content: str, user_id: str, source: str) -> bool:
def store_memory(api_key: str, content: str, user_id: str, source: str, session_id: str = "") -> bool:
"""Store session state as a memory via the Mem0 REST API."""
expires = (date.today() + timedelta(days=SESSION_STATE_EXPIRY_DAYS)).isoformat()
body = {
"messages": [
{"role": "user", "content": content}
@@ -159,7 +178,9 @@ def store_memory(api_key: str, content: str, user_id: str, source: str) -> bool:
"metadata": {
"type": "session_state",
"source": source,
"session_id": session_id,
},
"expiration_date": expires,
}
data = json.dumps(body).encode("utf-8")
@@ -207,7 +228,8 @@ def main():
log.debug("No transcript_path provided")
return
user_id = os.environ.get("MEM0_USER_ID", os.environ.get("USER", "default"))
session_id = hook_input.get("session_id", "")
user_id = resolve_user_id()
lines = tail_lines(transcript_path, MAX_TAIL_LINES)
if not lines:
@@ -228,7 +250,7 @@ def main():
len(state["bash_commands"]),
)
store_memory(api_key, content, user_id, source)
store_memory(api_key, content, user_id, source, session_id)
if __name__ == "__main__":
+20 -6
View File
@@ -5,12 +5,16 @@
# the full context before it gets compressed.
#
# Output: Text instructions injected into Claude's context.
# Claude still has the full conversation and can write an accurate summary.
# A companion Python script (on_pre_compact.py) also runs to capture
# transcript state directly via the Mem0 REST API as a safety net.
# Claude still has the full conversation and can write an accurate summary,
# which it stores via add_memory(infer=False) so the platform preserves
# the structure verbatim instead of running a second extraction pass.
set -euo pipefail
if [ -n "${MEM0_DEBUG:-}" ]; then
mkdir -p "$HOME/.mem0" && exec 2>>"$HOME/.mem0/hooks.log"
fi
cat <<'EOF'
## CRITICAL: Pre-Compaction Session Summary
@@ -18,7 +22,9 @@ Context compaction is about to happen. You are about to lose most of your conver
### Step 1: Store session summary
Call `add_memory` with a thorough summary covering ALL of the following:
Call `add_memory` with `infer=False` and a thorough summary covering ALL of the following.
`infer=False` is critical here: you've already done the extraction work yourself using full context. Without it, the platform runs a second LLM pass that loses your structure and pulls fragmented facts. With it, your summary is preserved verbatim.
```
## Session Summary (Pre-Compaction)
@@ -44,11 +50,19 @@ Call `add_memory` with a thorough summary covering ALL of the following:
the post-compaction agent continue without asking redundant questions]
```
Include metadata: `{"type": "session_state", "source": "pre-compaction"}`
Tool call shape:
```
add_memory(
messages=[{"role":"user","content":"<the summary above>"}],
user_id="<the active user_id from the SessionStart bootstrap>",
metadata={"type":"session_state","source":"pre-compaction"},
infer=False,
)
```
### Step 2: Store any unstored learnings
If there are learnings from this session that you haven't stored yet, store them as separate memories:
If there are learnings from this session that you haven't stored yet, store them as separate memories with `infer=False` (same reasoning -- you've already extracted the fact, don't re-extract):
- Failed approaches -> metadata `{"type": "anti_pattern"}`
- Successful strategies -> metadata `{"type": "task_learning"}`
- Architecture decisions -> metadata `{"type": "decision"}`
+37 -4
View File
@@ -11,9 +11,34 @@
# even if jq is missing or stdin is malformed.
set -uo pipefail
if [ -n "${MEM0_DEBUG:-}" ]; then
mkdir -p "$HOME/.mem0" && exec 2>>"$HOME/.mem0/hooks.log"
fi
# Skip the bootstrap entirely if no API key is configured -- the agent
# would otherwise be told to call mem0 MCP tools that will all fail.
if [ -z "${MEM0_API_KEY:-}" ]; then
exit 0
fi
SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
# shellcheck source=_identity.sh
. "$SCRIPT_DIR/_identity.sh"
INPUT=$(cat)
SOURCE=$(echo "$INPUT" | jq -r '.source // "startup"' 2>/dev/null || echo "startup")
# Identity line is emitted before every bootstrap variant so the agent
# uses the same user_id the hooks resolved. Without this, the agent's
# search_memories/add_memory MCP calls may bind to a different bucket
# than what the hooks write to.
echo "## Mem0 Identity"
echo ""
echo "Active user_id: \`$MEM0_RESOLVED_USER_ID\`"
echo ""
echo "Always include \`{\"user_id\": \"$MEM0_RESOLVED_USER_ID\"}\` (wrapped in an \`AND\` clause) in every \`search_memories\` filter and as \`user_id\` on every \`add_memory\` call. This keeps the agent's MCP calls aligned with the bucket the hooks write to."
echo ""
if [ "$SOURCE" = "startup" ]; then
cat <<'EOF'
## Mem0 Session Bootstrap
@@ -40,14 +65,22 @@ Continue where you left off.
EOF
elif [ "$SOURCE" = "compact" ]; then
# Capture the just-generated compact summary in the background.
# PreCompact fires too early to see this entry; SessionStart-compact
# is the first place isCompactSummary=true is in the transcript.
echo "$INPUT" | python3 "$SCRIPT_DIR/capture_compact_summary.py" 2>/dev/null &
cat <<'EOF'
## Mem0 Post-Compaction Recovery
Context was just compacted. You may have lost important session context.
Context was just compacted. The Claude Code-generated compact summary
is being captured to mem0 in the background as `metadata.type=compact_summary`.
1. Call `search_memories` with queries related to what you were working on to reload relevant knowledge.
2. Check for any session state memories that were saved before compaction.
3. Continue working based on the recovered context.
1. Call `search_memories` to reload context, layering up to three angles:
- `metadata.type=session_state` -- the rich pre-compaction summary you wrote
- `metadata.type=compact_summary` -- the platform-generated condensed summary just now
- `metadata.type=decision` / `anti_pattern` -- specific facts you stored during the session
2. Continue working from the recovered context.
EOF
fi
+4
View File
@@ -12,6 +12,10 @@
set -euo pipefail
if [ -n "${MEM0_DEBUG:-}" ]; then
mkdir -p "$HOME/.mem0" && exec 2>>"$HOME/.mem0/hooks.log"
fi
SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
INPUT=$(cat)
+4
View File
@@ -17,6 +17,10 @@
set -uo pipefail
if [ -n "${MEM0_DEBUG:-}" ]; then
mkdir -p "$HOME/.mem0" && exec 2>>"$HOME/.mem0/hooks.log"
fi
INPUT=$(cat)
STOP_HOOK_ACTIVE=$(echo "$INPUT" | jq -r '.stop_hook_active // false' 2>/dev/null || echo "false")
+4
View File
@@ -9,6 +9,10 @@
set -euo pipefail
if [ -n "${MEM0_DEBUG:-}" ]; then
mkdir -p "$HOME/.mem0" && exec 2>>"$HOME/.mem0/hooks.log"
fi
INPUT=$(cat)
TASK_SUBJECT=$(echo "$INPUT" | jq -r '.task_subject // "unknown task"' 2>/dev/null || echo "unknown task")
+48 -37
View File
@@ -1,61 +1,72 @@
#!/usr/bin/env bash
# Hook: UserPromptSubmit
#
# Fires on every user message. Searches mem0 for relevant memories
# and injects them into Claude's context before processing.
# Fires on every user message. Instead of pre-searching mem0 with the
# raw prompt, this injects a decision rubric telling the agent when
# and how to search itself. The agent has more context than this
# script does -- let it decide.
#
# Input: JSON on stdin with prompt, session_id, cwd, transcript_path
# Output: Matching memories as context text (exit 0)
#
# Skips search for very short prompts (< 20 chars) and when
# MEM0_API_KEY is not set. Uses a 3s timeout to minimize latency.
# Input: JSON on stdin (prompt, session_id, cwd, transcript_path)
# Output: Decision rubric injected into Claude's context (exit 0)
# Intentionally omit -e so the script always exits 0 even if
# curl or jq fail — must never block the user's prompt.
# Intentionally omit -e so the script always exits 0 even if jq fails --
# must never block the user's prompt.
set -uo pipefail
if [ -n "${MEM0_DEBUG:-}" ]; then
mkdir -p "$HOME/.mem0" && exec 2>>"$HOME/.mem0/hooks.log"
fi
INPUT=$(cat)
PROMPT=$(echo "$INPUT" | jq -r '.prompt // ""' 2>/dev/null || echo "")
# Skip trivial prompts — not worth a network call
# Acknowledgements and short replies don't warrant memory context
if [ ${#PROMPT} -lt 20 ]; then
exit 0
fi
API_KEY="${MEM0_API_KEY:-}"
if [ -z "$API_KEY" ]; then
# No API key means the agent can't search anyway
if [ -z "${MEM0_API_KEY:-}" ]; then
exit 0
fi
USER_ID="${MEM0_USER_ID:-${USER:-default}}"
SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
# shellcheck source=_identity.sh
. "$SCRIPT_DIR/_identity.sh"
USER_ID="$MEM0_RESOLVED_USER_ID"
# Build request body safely via jq to avoid injection
BODY=$(jq -n --arg query "$PROMPT" --arg user_id "$USER_ID" \
'{query: $query, filters: {user_id: $user_id}, top_k: 5}')
cat <<EOF
## Memory check
# Search mem0 for memories relevant to this prompt
RESPONSE=$(curl -s --max-time 3 \
-X POST "https://api.mem0.ai/v2/memories/search/" \
-H "Authorization: Token $API_KEY" \
-H "Content-Type: application/json" \
-d "$BODY" \
2>/dev/null || echo "")
Before responding, decide whether persistent memory context from mem0 would
improve your answer. The agent -- not this hook -- owns this decision.
if [ -z "$RESPONSE" ]; then
exit 0
fi
**Search WHEN** the user:
- references past work, decisions, or things "we" built
- asks "how should we...", "best way to...", or any decision-style question
- hits an error, bug, or asks for debugging help
- requests work that touches their stack, tools, conventions, or preferences
- starts a non-trivial task in a known project
# Extract memories from response (API returns a flat array)
MEMORIES=$(echo "$RESPONSE" | jq -r '
if type == "array" then . else .results // [] end |
if length == 0 then empty else
"## Relevant memories from mem0\n\n" +
(map(select(.memory != null) | "- " + .memory) | join("\n"))
end
' 2>/dev/null || echo "")
**Skip WHEN:**
- the prompt is an acknowledgement or continuation
- the user is *stating* new info -- that's a write trigger (\`add_memory\`), not a search
- it's a pure syntax / factual question answerable from general knowledge
- you already searched this scope earlier in the turn
if [ -n "$MEMORIES" ]; then
echo "$MEMORIES"
fi
**If searching, do it well:**
- Run **2-4 parallel** \`search_memories\` calls with different angles, not one
query that echoes the user's prompt.
- Phrase queries as **nouns** ("auth module decisions"), not full sentences.
- Filter shape: the root must be a logical operator (\`AND\` / \`OR\` / \`NOT\`)
with an array, and metadata uses a **nested** object (not dotted keys).
Combine \`user_id\` with one \`metadata.type\` clause per call:
- \`{"AND": [{"user_id": "$USER_ID"}, {"metadata": {"type": "decision"}}]}\` -- design / architecture
- \`{"AND": [{"user_id": "$USER_ID"}, {"metadata": {"type": "anti_pattern"}}]}\` -- debugging, error handling
- \`{"AND": [{"user_id": "$USER_ID"}, {"metadata": {"type": "user_preference"}}]}\` -- tooling, stack, style
- \`{"AND": [{"user_id": "$USER_ID"}, {"metadata": {"type": "convention"}}]}\` -- established patterns
- Or scope with just \`{"AND": [{"user_id": "$USER_ID"}]}\` when no metadata filter fits.
- Empty results are normal -- proceed without context.
EOF
exit 0
@@ -0,0 +1,142 @@
#!/usr/bin/env python3
"""Replace mem0's default category taxonomy with one tuned for coding workflows.
mem0 auto-tags every memory with one or more `categories`. By default the list
is consumer-oriented (food, hobbies, music, ...), which is meaningless for code.
This script replaces the project's category list with a coding-focused one.
The change is project-level (per the platform docs, per-request overrides are
not supported on the managed API). Run once per project; future memories will
be tagged using the new list automatically.
Usage:
python setup_coding_categories.py # dry-run: show current vs proposed, no changes
python setup_coding_categories.py --apply # actually call project.update()
Requires the mem0ai Python SDK and MEM0_API_KEY to be set.
"""
from __future__ import annotations
import argparse
import json
import os
import sys
CODING_CATEGORIES = [
{
"architecture_decisions": (
"Design choices, system structure, technology selection, trade-offs evaluated, "
"and architectural patterns adopted in the project."
)
},
{
"anti_patterns": (
"Approaches that failed, debugging dead-ends, common mistakes to avoid, "
"and lessons learned from things that didn't work."
)
},
{
"task_learnings": (
"Strategies and approaches that succeeded for specific tasks, including tooling "
"tricks, workflow shortcuts, and effective problem-solving patterns."
)
},
{
"tooling_setup": (
"Development environment, build tools, dependencies, package managers, deploy "
"pipelines, and configuration steps for the project."
)
},
{
"bug_fixes": (
"Specific bug fixes with root cause analysis, the fix applied, and how the bug "
"was diagnosed -- useful for recognising similar issues later."
)
},
{
"coding_conventions": (
"Code style, naming patterns, file organisation, error-handling conventions, "
"and team agreements about how code is written in this project."
)
},
{
"user_preferences": (
"User's stated preferences for tools, libraries, languages, formatting, "
"and ways of working."
)
},
]
def _print_categories(label: str, cats):
print(f"=== {label} ===")
if cats:
print(json.dumps(cats, indent=2))
else:
print("(none / using mem0 defaults)")
print()
def main() -> int:
ap = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter)
ap.add_argument(
"--apply",
action="store_true",
help="Actually call project.update(). Without this flag, runs in dry-run mode.",
)
args = ap.parse_args()
if not os.environ.get("MEM0_API_KEY"):
print("ERROR: MEM0_API_KEY is not set. Export it and try again.", file=sys.stderr)
return 1
try:
from mem0 import MemoryClient
except ImportError:
print(
"ERROR: the mem0ai Python SDK is not installed.\n"
"Install with: pip install mem0ai\n"
"Then re-run this script.",
file=sys.stderr,
)
return 1
try:
client = MemoryClient()
except Exception as e:
print(
f"ERROR initialising MemoryClient: {e}\n"
"Most commonly this is an invalid MEM0_API_KEY -- check the key at "
"https://app.mem0.ai/dashboard/api-keys",
file=sys.stderr,
)
return 1
try:
current = client.project.get(fields=["custom_categories"])
current_cats = current.get("custom_categories") if isinstance(current, dict) else None
except Exception as e:
print(f"ERROR fetching current categories: {e}", file=sys.stderr)
return 1
_print_categories("Current project categories", current_cats)
_print_categories("Proposed coding categories", CODING_CATEGORIES)
if not args.apply:
print("Dry-run only -- no changes made. Re-run with --apply to write.")
return 0
print("Applying coding categories...")
try:
response = client.project.update(custom_categories=CODING_CATEGORIES)
except Exception as e:
print(f"ERROR applying update: {e}", file=sys.stderr)
return 1
print("Done.", response if response else "")
return 0
if __name__ == "__main__":
sys.exit(main())
-62
View File
@@ -1,62 +0,0 @@
---
name: mem0-codex
description: >
Mem0 persistent memory integration for Codex. Automatically retrieve relevant
memories at the start of each task, store key learnings when tasks complete,
and capture session state before context is lost. Use the mem0 MCP tools
(add_memory, search_memories, get_memories, etc.) for all memory operations.
---
# Mem0 Memory Protocol for Codex
You have access to persistent memory via the mem0 MCP tools. Follow this protocol to maintain context across sessions.
## On every new task
1. Call `search_memories` with a query related to the current task or project to load relevant context.
2. Review returned memories to understand what has been learned in prior sessions.
3. If appropriate, call `get_memories` to browse all stored memories for this user.
## After completing significant work
Extract key learnings and store them using the `add_memory` tool:
- **Decisions made** -> Include metadata `{"type": "decision"}`
- **Strategies that worked** -> Include metadata `{"type": "task_learning"}`
- **Failed approaches** -> Include metadata `{"type": "anti_pattern"}`
- **User preferences observed** -> Include metadata `{"type": "user_preference"}`
- **Environment/setup discoveries** -> Include metadata `{"type": "environmental"}`
- **Conventions established** -> Include metadata `{"type": "convention"}`
Memories can be as detailed as needed -- include full context, reasoning, code snippets, file paths, and examples. Longer, searchable memories are more valuable than vague one-liners.
## Before losing context
If context is about to be compacted or the session is ending, store a comprehensive session summary:
```
## Session Summary
### User's Goal
[What the user originally asked for]
### What Was Accomplished
[Numbered list of tasks completed]
### Key Decisions Made
[Architectural choices, trade-offs discussed]
### Files Created or Modified
[Important file paths with what changed]
### Current State
[What is in progress, pending items, next steps]
```
Include metadata: `{"type": "session_state"}`
## Memory hygiene
- Do NOT write to MEMORY.md or any file-based memory. Use mem0 MCP tools exclusively.
- Only store genuinely useful learnings. Skip trivial interactions.
- Use specific, searchable language in memory content.
+170
View File
@@ -0,0 +1,170 @@
---
name: mem0-mcp
description: >
Mem0 memory protocol for agents using the mem0 MCP tools (Claude Code, Cursor,
Codex, and any other MCP-aware runtime). Decide deliberately when memory context
would help, run targeted searches with metadata filters when it would, and store
key learnings as work completes. Use the mem0 MCP tools (add_memory,
search_memories, get_memories, etc.) for all memory operations.
---
# Mem0 MCP Memory Protocol
You have access to persistent memory via the mem0 MCP tools. Follow this protocol to maintain context across sessions.
## On every new task
Decide whether persistent memory context would improve your response, then act accordingly. Don't search by default — search deliberately.
### Decide: search or skip?
**Search WHEN** the user:
- references past work, decisions, or things "we" built
- asks "how should we...", "best way to...", or any decision-style question
- hits an error, bug, or asks for debugging help
- requests work that touches their stack, tools, conventions, or preferences
- starts a non-trivial task in a known project
**Skip WHEN:**
- the prompt is an acknowledgement or continuation ("ok", "thanks", "continue")
- the user is *stating* new info — that's a write trigger (`add_memory`), not a search
- it's a pure syntax / factual question answerable from general knowledge
- you already searched this scope earlier in the turn
Empty results are normal. Proceed without context — they don't mean the system is broken.
### How to search well
When you do search, run **2–4 parallel** `search_memories` calls at different angles instead of one query echoing the user's prompt.
**Query phrasing:**
- Use **nouns**, not sentences. `"auth module decisions"` beats `"what did we decide about auth"`.
- Strip conversational filler. *"remember when we picked Postgres?"* → search `"Postgres choice"`.
- Use entity names, not pronouns. Resolve "that thing" from recent context first.
- Don't search on meta-questions ("what was that?") — use recent context or `get_memories` ordered by `created_at`.
**Metadata filters** match the same `type` values written under "After completing significant work" below.
Two rules from the v2 filter spec:
1. The root **must** be a logical operator (`AND` / `OR` / `NOT`) with an array. A bare `{"user_id": "..."}` won't work.
2. Metadata uses a **nested** object, not a dotted key. `{"metadata": {"type": "decision"}}`, never `{"metadata.type": "decision"}`. Only top-level metadata keys are filterable.
Combine `user_id` with one metadata clause per call:
| `metadata.type` clause | Use for |
|--------|---------|
| `{"metadata": {"type": "decision"}}` | design / architecture / "how should we" questions |
| `{"metadata": {"type": "anti_pattern"}}` | debugging, error handling, things that failed before |
| `{"metadata": {"type": "user_preference"}}` | tooling, stack, style — always include for code work |
| `{"metadata": {"type": "convention"}}` | established patterns in this project |
Full filter (replace `<your_user_id>` with the active user_id from your runtime):
```python
filters={"AND": [{"user_id": "<your_user_id>"}, {"metadata": {"type": "decision"}}]}
```
### Worked example
User asks: *"Refactor the auth module to use JWT."*
Don't:
```python
search_memories(query="Refactor the auth module to use JWT")
# Hits whatever shares words. Misses prior decisions and preferences.
```
Do (parallel — substitute the active `user_id` for `<your_user_id>`):
```python
search_memories(query="auth module decisions",
filters={"AND": [{"user_id": "<your_user_id>"}, {"metadata": {"type": "decision"}}]})
search_memories(query="JWT",
filters={"AND": [{"user_id": "<your_user_id>"}]})
search_memories(query="auth refactor failures",
filters={"AND": [{"user_id": "<your_user_id>"}, {"metadata": {"type": "anti_pattern"}}]})
search_memories(query="auth",
filters={"AND": [{"user_id": "<your_user_id>"}, {"metadata": {"type": "user_preference"}}]})
```
## After completing significant work
Extract key learnings and store them using the `add_memory` tool:
- **Decisions made** -> Include metadata `{"type": "decision"}`
- **Strategies that worked** -> Include metadata `{"type": "task_learning"}`
- **Failed approaches** -> Include metadata `{"type": "anti_pattern"}`
- **User preferences observed** -> Include metadata `{"type": "user_preference"}`
- **Environment/setup discoveries** -> Include metadata `{"type": "environmental"}`
- **Conventions established** -> Include metadata `{"type": "convention"}`
> `metadata.type` (which you set explicitly) and `categories` (which the platform auto-tags after the project's custom-category list — see `scripts/setup_coding_categories.py`) are complementary. Always set `metadata.type` for explicit filtering; the platform fills in `categories` on its own. Don't try to set `categories` on `add_memory` calls — per-request overrides aren't supported on the managed API.
### Expiration: high-churn vs durable
Some memory types are state snapshots that go stale fast; others are durable facts that should outlive the session that created them. Mark the difference with `expiration_date` on writes.
| Type | Expiration | Why |
|---|---|---|
| `session_state`, `compact_summary` | `expiration_date` ≈ today + 90 days | Describe a single moment of project state. Useless after a quarter; clutter the recall surface. |
| `decision`, `anti_pattern`, `convention`, `user_preference`, `task_learning`, `environmental` | omit `expiration_date` | Durable facts. A decision made last year is still a decision; same for a convention or a user preference. |
`add_memory` accepts `expiration_date` as a string (`"YYYY-MM-DD"`). The two server-side hooks (`on_pre_compact.py`, `capture_compact_summary.py`) already set this for the types they write. When you write directly via the MCP tool, follow the same rule.
### Recency filter on recall
When the user is asking about *current* state ("where were we", "what's the active task", "the latest decision on X"), filter recall to recent memories so stale snapshots don't surface:
```python
# Last 90 days only
{"AND": [{"user_id": "<id>"}, {"metadata": {"type": "session_state"}}, {"created_at": {"gte": "<90 days ago, YYYY-MM-DD>"}}]}
```
Skip the recency filter when the user is asking about durable facts ("what conventions does this project use", "have we hit this bug before") — those are timeless and recency would hide them.
Memories can be as detailed as needed -- include full context, reasoning, code snippets, file paths, and examples. Longer, searchable memories are more valuable than vague one-liners.
### Use `infer=False` for already-structured content
When you've done the extraction work yourself — pre-compaction summaries, decisions, anti-patterns, conventions you've explicitly identified — pass `infer=False` so the platform stores your text verbatim instead of running a second extraction pass over it.
```python
add_memory(
messages=[{"role": "user", "content": "<your structured fact>"}],
user_id="<active user_id>",
metadata={"type": "decision"},
infer=False,
)
```
Stick to one mode per distinct piece of content — don't mix `infer=True` (default) and `infer=False` for the same fact, you'll get duplicates. Default (`infer=True`) is right for raw conversational signal you want extracted; `infer=False` is right for pre-extracted structure.
## Before losing context
If context is about to be compacted or the session is ending, store a comprehensive session summary:
```
## Session Summary
### User's Goal
[What the user originally asked for]
### What Was Accomplished
[Numbered list of tasks completed]
### Key Decisions Made
[Architectural choices, trade-offs discussed]
### Files Created or Modified
[Important file paths with what changed]
### Current State
[What is in progress, pending items, next steps]
```
Include metadata: `{"type": "session_state"}`
## Memory hygiene
- Do NOT write to MEMORY.md or any file-based memory. Use mem0 MCP tools exclusively.
- Only store genuinely useful learnings. Skip trivial interactions.
- Use specific, searchable language in memory content.
+2
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@@ -46,6 +46,8 @@ export MEM0_API_KEY="m0-your-api-key"
Get an API key at: https://app.mem0.ai/dashboard/api-keys?utm_source=oss&utm_medium=mem0-plugin-skill
> **Don't have a `MEM0_API_KEY`?** Run `mem0 init --agent --json` (after `pip install mem0-cli` or `npm install -g @mem0/cli`) to mint an evaluation key without email or dashboard. The human can claim later with `mem0 init --email <your-email>`.
## Step 2: Initialize the client
**Python:**
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "mem0ai",
"version": "3.0.2",
"version": "3.0.3",
"description": "The Memory Layer For Your AI Apps",
"main": "./dist/index.js",
"module": "./dist/index.mjs",
+165
View File
@@ -0,0 +1,165 @@
/**
* Best-effort read/write of ~/.mem0/config.json from the TS SDK.
*
* Used to stitch PostHog identities: SDKs and CLIs persist anonymous
* distinct_id values here, and the TS MemoryClient reads those on init to
* fire $identify and merge them into the email identity.
*
* Node-only. Browsers (no `process.versions.node`) no-op.
*/
export interface Mem0AnonIds {
oss?: string;
cli?: string;
aliasedPairs: string[];
}
interface NodeFs {
fs: typeof import("fs");
path: typeof import("path");
crypto: typeof import("crypto");
configPath: string;
}
async function getNodeFs(): Promise<NodeFs | null> {
if (typeof process === "undefined" || !process.versions?.node) return null;
try {
const [fs, path, os, crypto] = await Promise.all([
import("fs"),
import("path"),
import("os"),
import("crypto"),
]);
const fsMod = (fs as any).default ?? fs;
const pathMod = (path as any).default ?? path;
const osMod = (os as any).default ?? os;
const cryptoMod = (crypto as any).default ?? crypto;
const dir = process.env.MEM0_DIR || pathMod.join(osMod.homedir(), ".mem0");
return {
fs: fsMod,
path: pathMod,
crypto: cryptoMod,
configPath: pathMod.join(dir, "config.json"),
};
} catch {
return null;
}
}
function loadConfig(node: NodeFs): Record<string, any> | null {
try {
if (!node.fs.existsSync(node.configPath)) return null;
const parsed = JSON.parse(node.fs.readFileSync(node.configPath, "utf8"));
return parsed && typeof parsed === "object" ? parsed : null;
} catch {
return null;
}
}
function writeConfig(node: NodeFs, config: Record<string, any>): void {
node.fs.mkdirSync(node.path.dirname(node.configPath), { recursive: true });
node.fs.writeFileSync(node.configPath, JSON.stringify(config, null, 4));
}
function aliasPairMarker(node: NodeFs, anonId: string, email: string): string {
return node.crypto
.createHash("sha256")
.update(`${anonId}\0${email}`, "utf8")
.digest("hex");
}
function randomUserId(node: NodeFs): string {
if (typeof node.crypto.randomUUID === "function") {
return node.crypto.randomUUID();
}
return (
Math.random().toString(36).substring(2, 15) +
Math.random().toString(36).substring(2, 15)
);
}
export async function getOrCreateMem0UserId(): Promise<string | null> {
const node = await getNodeFs();
if (!node) return null;
try {
const config = loadConfig(node) ?? {};
if (typeof config.user_id === "string" && config.user_id) {
return config.user_id;
}
const userId = randomUserId(node);
config.user_id = userId;
writeConfig(node, config);
return userId;
} catch {
return null;
}
}
export async function readMem0AnonIds(): Promise<Mem0AnonIds | null> {
const node = await getNodeFs();
if (!node) return null;
const config = loadConfig(node);
if (!config) return null;
const telemetry =
config.telemetry && typeof config.telemetry === "object"
? config.telemetry
: {};
return {
oss: typeof config.user_id === "string" ? config.user_id : undefined,
cli:
typeof telemetry.anonymous_id === "string"
? telemetry.anonymous_id
: undefined,
aliasedPairs: Array.isArray(telemetry.aliased_pairs)
? telemetry.aliased_pairs.filter(
(item: unknown) => typeof item === "string",
)
: [],
};
}
export async function isMem0Aliased(
anonId: string,
email: string,
): Promise<boolean> {
if (!anonId || !email) return false;
const node = await getNodeFs();
if (!node) return false;
const config = loadConfig(node);
if (!config) return false;
const telemetry =
config.telemetry && typeof config.telemetry === "object"
? config.telemetry
: {};
const aliasedPairs = Array.isArray(telemetry.aliased_pairs)
? telemetry.aliased_pairs
: [];
return aliasedPairs.includes(aliasPairMarker(node, anonId, email));
}
export async function markMem0Aliased(
anonId: string,
email: string,
): Promise<void> {
const node = await getNodeFs();
if (!node) return;
try {
const config = loadConfig(node) ?? {};
const telemetry =
config.telemetry && typeof config.telemetry === "object"
? config.telemetry
: {};
const aliasedPairs = Array.isArray(telemetry.aliased_pairs)
? telemetry.aliased_pairs
: [];
const marker = aliasPairMarker(node, anonId, email);
if (!aliasedPairs.includes(marker)) {
aliasedPairs.push(marker);
}
telemetry.aliased_pairs = aliasedPairs;
config.telemetry = telemetry;
writeConfig(node, config);
} catch {
// Best-effort: read-only filesystems and unwritable paths just skip.
}
}
+38 -1
View File
@@ -20,7 +20,18 @@ import {
CreateMemoryExportPayload,
GetMemoryExportPayload,
} from "./mem0.types";
import { captureClientEvent, generateHash } from "./telemetry";
import {
captureClientEvent,
generateHash,
isTelemetryEnabled,
telemetry,
} from "./telemetry";
import {
getOrCreateMem0UserId,
isMem0Aliased,
markMem0Aliased,
readMem0AnonIds,
} from "./config";
import { camelToSnake, camelToSnakeKeys, snakeToCamelKeys } from "./utils";
import { createExceptionFromResponse, MemoryError } from "../common/exceptions";
@@ -118,6 +129,8 @@ export default class MemoryClient {
this.telemetryId = generateHash(this.apiKey);
}
await this._maybeAliasAnonToEmail();
captureClientEvent("init", this, {
client_type: "MemoryClient",
}).catch((error: any) => {
@@ -132,6 +145,30 @@ export default class MemoryClient {
}
}
private async _maybeAliasAnonToEmail(): Promise<void> {
if (!isTelemetryEnabled()) return;
try {
const email = this.telemetryId;
if (!email || !email.includes("@")) return;
const sharedAnonId = await getOrCreateMem0UserId();
const anonIds = await readMem0AnonIds();
if (!anonIds && !sharedAnonId) return;
const candidates = [anonIds?.oss || sharedAnonId, anonIds?.cli].filter(
(id): id is string => !!id && id !== email,
);
const seen = new Set<string>();
for (const anonId of candidates) {
if (seen.has(anonId) || (await isMem0Aliased(anonId, email))) continue;
seen.add(anonId);
if (await telemetry.captureIdentify(anonId, email)) {
await markMem0Aliased(anonId, email);
}
}
} catch (error: any) {
console.error("Failed to alias telemetry identity:", error);
}
}
private _captureEvent(methodName: string, args: any[]) {
captureClientEvent(methodName, this, {
success: true,
+9
View File
@@ -22,6 +22,7 @@ export interface SearchMemoryOptions {
topK?: number;
threshold?: number;
rerank?: boolean;
latestOnly?: boolean;
fields?: string[];
categories?: string[];
}
@@ -32,6 +33,7 @@ export interface GetAllMemoryOptions {
pageSize?: number;
startDate?: string;
endDate?: string;
latestOnly?: boolean;
categories?: string[];
}
@@ -50,6 +52,13 @@ export interface PromptUpdatePayload {
memoryDepth?: string | null;
usecaseSetting?: string | number;
multilingual?: boolean;
/**
* Toggle Memory Decay for this project. When `true`, search-time ranking
* boosts recently-used memories and gently dampens stale ones; when `false`,
* ranking is restored to the pre-decay behaviour. Off by default.
* See https://docs.mem0.ai/platform/features/memory-decay
*/
decay?: boolean;
[key: string]: any;
}
+52 -3
View File
@@ -32,8 +32,12 @@ class UnifiedTelemetry implements TelemetryClient {
this.host = host;
}
async captureEvent(distinctId: string, eventName: string, properties = {}) {
if (!MEM0_TELEMETRY) return;
async captureEvent(
distinctId: string,
eventName: string,
properties = {},
): Promise<boolean> {
if (!MEM0_TELEMETRY) return false;
const eventProperties = {
client_version: version,
@@ -61,9 +65,50 @@ class UnifiedTelemetry implements TelemetryClient {
if (!response.ok) {
console.error("Telemetry event capture failed:", await response.text());
return false;
}
return true;
} catch (error) {
console.error("Telemetry event capture failed:", error);
return false;
}
}
async captureIdentify(anonId: string, email: string): Promise<boolean> {
if (!MEM0_TELEMETRY) return false;
if (!anonId || !email || anonId === email) return false;
const payload = {
api_key: this.apiKey,
distinct_id: email,
event: "$identify",
properties: {
$anon_distinct_id: anonId,
client_source: "typescript",
$lib: "posthog-node",
},
};
try {
const response = await fetch(this.host, {
method: "POST",
headers: {
"Content-Type": "application/json",
},
body: JSON.stringify(payload),
});
if (!response.ok) {
console.error(
"Telemetry identify capture failed:",
await response.text(),
);
return false;
}
return true;
} catch (error) {
console.error("Telemetry identify capture failed:", error);
return false;
}
}
@@ -72,6 +117,10 @@ class UnifiedTelemetry implements TelemetryClient {
}
}
function isTelemetryEnabled(): boolean {
return MEM0_TELEMETRY;
}
const telemetry = new UnifiedTelemetry(POSTHOG_API_KEY, POSTHOG_HOST);
async function captureClientEvent(
@@ -101,4 +150,4 @@ async function captureClientEvent(
);
}
export { telemetry, captureClientEvent, generateHash };
export { telemetry, captureClientEvent, generateHash, isTelemetryEnabled };
+1 -1
View File
@@ -3,7 +3,7 @@ export interface TelemetryClient {
distinctId: string,
eventName: string,
properties?: Record<string, any>,
): Promise<void>;
): Promise<boolean>;
shutdown(): Promise<void>;
}
@@ -63,6 +63,24 @@ describe("MemoryClient - search()", () => {
expect(getFetchBody(call!).filters).toEqual({ user_id: "u1" });
});
test("serializes latestOnly as latest_only", async () => {
const extra = new Map<string, { status: number; body: unknown }>();
extra.set("/v3/memories/search/", {
status: 200,
body: { results: [] },
});
const mock = setupMockFetch(extra);
const client = new MemoryClient({ apiKey: TEST_API_KEY });
await client.search("test", {
filters: { user_id: "u1" },
latestOnly: true,
});
const call = findFetchCall(mock, "/v3/memories/search/", "POST");
expect(getFetchBody(call!).latest_only).toBe(true);
});
test("passes complex OR filters through to the API body", async () => {
const extra = new Map<string, { status: number; body: unknown }>();
extra.set("/v3/memories/search/", {
@@ -264,4 +282,22 @@ describe("MemoryClient - getAll() entity param rejection", () => {
await client.getAll({ filters: { user_id: "u1" } });
expect(findFetchCall(mock, "/v3/memories/", "POST")).toBeDefined();
});
test("serializes latestOnly as latest_only", async () => {
const extra = new Map<string, { status: number; body: unknown }>();
extra.set("/v3/memories/", {
status: 200,
body: { results: [] },
});
const mock = setupMockFetch(extra);
const client = new MemoryClient({ apiKey: TEST_API_KEY });
await client.getAll({
filters: { user_id: "u1" },
latestOnly: true,
});
const call = findFetchCall(mock, "/v3/memories/", "POST");
expect(getFetchBody(call!).latest_only).toBe(true);
});
});
@@ -0,0 +1,410 @@
/**
* Tests for PostHog identity stitching in the TS MemoryClient.
*
* Covers $identify firing, idempotency via pair markers, and the node/browser
* gate. Mocks fs and fetch; never touches the real ~/.mem0/config.json.
*/
import * as fs from "fs";
import * as os from "os";
import * as path from "path";
import { MemoryClient } from "../mem0";
import { telemetry } from "../telemetry";
import {
getOrCreateMem0UserId,
isMem0Aliased,
markMem0Aliased,
readMem0AnonIds,
} from "../config";
import { TEST_API_KEY } from "./helpers";
import { setupMockFetch, installConsoleSuppression } from "./setup";
installConsoleSuppression();
function setupMockFetchWithPostHog(): jest.Mock {
return setupMockFetch(
new Map([["us.i.posthog.com", { status: 200, body: "ok" }]]),
);
}
// ─── config.ts (node-only fs read/write) ──────────────────────
describe("config.ts — readMem0AnonIds / markMem0Aliased", () => {
let tmpHome: string;
const originalMem0Dir = process.env.MEM0_DIR;
beforeEach(() => {
tmpHome = fs.mkdtempSync(path.join(os.tmpdir(), "mem0-ts-test-"));
process.env.MEM0_DIR = tmpHome;
});
afterEach(() => {
if (fs.existsSync(tmpHome)) {
fs.rmSync(tmpHome, { recursive: true, force: true });
}
if (originalMem0Dir === undefined) {
delete process.env.MEM0_DIR;
} else {
process.env.MEM0_DIR = originalMem0Dir;
}
});
test("returns null when config file does not exist", async () => {
expect(await readMem0AnonIds()).toBeNull();
});
test("reads OSS user_id only", async () => {
fs.writeFileSync(
path.join(tmpHome, "config.json"),
JSON.stringify({ user_id: "oss-uuid" }),
);
const ids = await readMem0AnonIds();
expect(ids).toEqual({
oss: "oss-uuid",
cli: undefined,
aliasedPairs: [],
});
});
test("reads CLI anonymous_id and aliased_pairs", async () => {
fs.writeFileSync(
path.join(tmpHome, "config.json"),
JSON.stringify({
telemetry: { anonymous_id: "cli-anon", aliased_pairs: ["pair-marker"] },
}),
);
const ids = await readMem0AnonIds();
expect(ids).toEqual({
oss: undefined,
cli: "cli-anon",
aliasedPairs: ["pair-marker"],
});
});
test("getOrCreateMem0UserId creates and reuses shared SDK user_id", async () => {
const first = await getOrCreateMem0UserId();
const second = await getOrCreateMem0UserId();
expect(first).toBeTruthy();
expect(second).toBe(first);
const written = JSON.parse(
fs.readFileSync(path.join(tmpHome, "config.json"), "utf8"),
);
expect(written.user_id).toBe(first);
});
test("returns null on malformed JSON", async () => {
fs.writeFileSync(path.join(tmpHome, "config.json"), "{not json");
expect(await readMem0AnonIds()).toBeNull();
});
test("markMem0Aliased preserves other fields", async () => {
fs.writeFileSync(
path.join(tmpHome, "config.json"),
JSON.stringify({
user_id: "oss-uuid",
telemetry: { anonymous_id: "cli-anon" },
}),
);
await markMem0Aliased("oss-uuid", "user@example.com");
const written = JSON.parse(
fs.readFileSync(path.join(tmpHome, "config.json"), "utf8"),
);
expect(written.user_id).toBe("oss-uuid");
expect(written.telemetry.anonymous_id).toBe("cli-anon");
expect(written.telemetry.aliased_pairs).toHaveLength(1);
expect(await isMem0Aliased("oss-uuid", "user@example.com")).toBe(true);
});
test("markMem0Aliased creates telemetry section when missing", async () => {
fs.writeFileSync(
path.join(tmpHome, "config.json"),
JSON.stringify({ user_id: "oss-uuid" }),
);
await markMem0Aliased("oss-uuid", "user@example.com");
const written = JSON.parse(
fs.readFileSync(path.join(tmpHome, "config.json"), "utf8"),
);
expect(written.telemetry.aliased_pairs).toHaveLength(1);
});
test("markMem0Aliased tracks each pair independently", async () => {
fs.writeFileSync(
path.join(tmpHome, "config.json"),
JSON.stringify({ user_id: "oss-uuid" }),
);
await markMem0Aliased("oss-uuid", "user@example.com");
expect(await isMem0Aliased("oss-uuid", "user@example.com")).toBe(true);
expect(await isMem0Aliased("other-uuid", "user@example.com")).toBe(false);
expect(await isMem0Aliased("oss-uuid", "other@example.com")).toBe(false);
});
test("markMem0Aliased does not throw when target dir is unwritable", async () => {
// Point at a path that cannot be written to (a file-as-dir collision).
fs.writeFileSync(path.join(tmpHome, "blocker"), "x");
process.env.MEM0_DIR = path.join(tmpHome, "blocker"); // file used as dir
await expect(
markMem0Aliased("oss-uuid", "user@example.com"),
).resolves.toBeUndefined();
});
});
// ─── telemetry.captureIdentify ───────────────────────────────
describe("telemetry.captureIdentify", () => {
test("fires $identify with $anon_distinct_id", async () => {
const fetchMock = jest.fn(async () => ({
ok: true,
status: 200,
text: async () => "ok",
})) as unknown as typeof fetch;
global.fetch = fetchMock as any;
await telemetry.captureIdentify("anon-uuid", "user@example.com");
expect(fetchMock).toHaveBeenCalledTimes(1);
const [, init] = (fetchMock as jest.Mock).mock.calls[0];
const payload = JSON.parse(init.body);
expect(payload.event).toBe("$identify");
expect(payload.distinct_id).toBe("user@example.com");
expect(payload.properties.$anon_distinct_id).toBe("anon-uuid");
expect(payload.properties.$process_person_profile).toBeUndefined();
});
test("skips when anon equals email", async () => {
const fetchMock = jest.fn() as unknown as typeof fetch;
global.fetch = fetchMock as any;
await telemetry.captureIdentify("user@example.com", "user@example.com");
expect(fetchMock).not.toHaveBeenCalled();
});
test("skips when either input is empty", async () => {
const fetchMock = jest.fn() as unknown as typeof fetch;
global.fetch = fetchMock as any;
await telemetry.captureIdentify("", "user@example.com");
await telemetry.captureIdentify("anon", "");
expect(fetchMock).not.toHaveBeenCalled();
});
});
// ─── MemoryClient init aliasing ──────────────────────────────
describe("MemoryClient — _maybeAliasAnonToEmail", () => {
let tmpHome: string;
const originalMem0Dir = process.env.MEM0_DIR;
beforeEach(() => {
tmpHome = fs.mkdtempSync(path.join(os.tmpdir(), "mem0-ts-init-"));
process.env.MEM0_DIR = tmpHome;
});
afterEach(() => {
if (fs.existsSync(tmpHome)) {
fs.rmSync(tmpHome, { recursive: true, force: true });
}
if (originalMem0Dir === undefined) {
delete process.env.MEM0_DIR;
} else {
process.env.MEM0_DIR = originalMem0Dir;
}
});
// Construct a non-initialised client so we can call _maybeAliasAnonToEmail
// in isolation (the real constructor's _initializeClient also fires it).
function makeStubClient(telemetryId: string): MemoryClient {
const client = Object.create(MemoryClient.prototype) as MemoryClient;
(client as any).apiKey = TEST_API_KEY;
(client as any).host = "https://api.mem0.ai";
(client as any).telemetryId = telemetryId;
return client;
}
test("fires $identify on first init and persists pair marker", async () => {
fs.writeFileSync(
path.join(tmpHome, "config.json"),
JSON.stringify({ user_id: "oss-uuid" }),
);
const fetchMock = setupMockFetchWithPostHog();
const client = makeStubClient("test@example.com");
await (client as any)._maybeAliasAnonToEmail();
const identifyCalls = (fetchMock.mock.calls as any[]).filter(
([, init]: [string, RequestInit]) => {
if (!init?.body) return false;
return JSON.parse(init.body as string).event === "$identify";
},
);
expect(identifyCalls.length).toBe(1);
const body = JSON.parse(identifyCalls[0][1].body);
expect(body.distinct_id).toBe("test@example.com");
expect(body.properties.$anon_distinct_id).toBe("oss-uuid");
const written = JSON.parse(
fs.readFileSync(path.join(tmpHome, "config.json"), "utf8"),
);
expect(written.telemetry.aliased_pairs).toHaveLength(1);
});
test("platform-first init creates shared anon ID and identifies it", async () => {
const fetchMock = setupMockFetchWithPostHog();
const client = makeStubClient("test@example.com");
await (client as any)._maybeAliasAnonToEmail();
const written = JSON.parse(
fs.readFileSync(path.join(tmpHome, "config.json"), "utf8"),
);
expect(written.user_id).toBeTruthy();
expect(written.telemetry.aliased_pairs).toHaveLength(1);
const identifyCalls = (fetchMock.mock.calls as any[]).filter(
([, init]: [string, RequestInit]) => {
if (!init?.body) return false;
return JSON.parse(init.body as string).event === "$identify";
},
);
expect(identifyCalls.length).toBe(1);
const body = JSON.parse(identifyCalls[0][1].body);
expect(body.distinct_id).toBe("test@example.com");
expect(body.properties.$anon_distinct_id).toBe(written.user_id);
});
test("second init does not refire $identify", async () => {
fs.writeFileSync(
path.join(tmpHome, "config.json"),
JSON.stringify({
user_id: "oss-uuid",
telemetry: {},
}),
);
await markMem0Aliased("oss-uuid", "test@example.com");
const fetchMock = setupMockFetchWithPostHog();
const client = makeStubClient("test@example.com");
await (client as any)._maybeAliasAnonToEmail();
const identifyCalls = (fetchMock.mock.calls as any[]).filter(
([, init]: [string, RequestInit]) => {
if (!init?.body) return false;
return JSON.parse(init.body as string).event === "$identify";
},
);
expect(identifyCalls.length).toBe(0);
});
test("fires $identify for both OSS and CLI anon ids", async () => {
fs.writeFileSync(
path.join(tmpHome, "config.json"),
JSON.stringify({
user_id: "oss-uuid",
telemetry: { anonymous_id: "cli-anon" },
}),
);
const fetchMock = setupMockFetchWithPostHog();
const client = makeStubClient("test@example.com");
await (client as any)._maybeAliasAnonToEmail();
const identifyCalls = (fetchMock.mock.calls as any[]).filter(
([, init]: [string, RequestInit]) => {
if (!init?.body) return false;
return JSON.parse(init.body as string).event === "$identify";
},
);
expect(identifyCalls.length).toBe(2);
const anonIds = identifyCalls.map(
(c: [string, RequestInit]) =>
JSON.parse(c[1].body as string).properties.$anon_distinct_id,
);
expect(anonIds).toContain("oss-uuid");
expect(anonIds).toContain("cli-anon");
const written = JSON.parse(
fs.readFileSync(path.join(tmpHome, "config.json"), "utf8"),
);
expect(written.telemetry.aliased_pairs).toHaveLength(2);
});
test("noop when telemetryId is not an email", async () => {
fs.writeFileSync(
path.join(tmpHome, "config.json"),
JSON.stringify({ user_id: "oss-uuid" }),
);
const fetchMock = setupMockFetch();
const client = makeStubClient("not-an-email");
await (client as any)._maybeAliasAnonToEmail();
const identifyCalls = (fetchMock.mock.calls as any[]).filter(
([, init]: [string, RequestInit]) => {
if (!init?.body) return false;
return JSON.parse(init.body as string).event === "$identify";
},
);
expect(identifyCalls.length).toBe(0);
});
test("does not throw when config read fails", async () => {
fs.writeFileSync(path.join(tmpHome, "config.json"), "{not json");
setupMockFetch();
const client = makeStubClient("test@example.com");
await expect(
(client as any)._maybeAliasAnonToEmail(),
).resolves.toBeUndefined();
});
test("noop when telemetry disabled — no fs read, no fs write, no events", async () => {
fs.writeFileSync(
path.join(tmpHome, "config.json"),
JSON.stringify({ user_id: "oss-uuid" }),
);
const fetchMock = setupMockFetch();
jest.resetModules();
const original = process.env.MEM0_TELEMETRY;
process.env.MEM0_TELEMETRY = "false";
try {
const { MemoryClient: ColdClient } = await import("../mem0");
const client = Object.create(ColdClient.prototype);
client.apiKey = TEST_API_KEY;
client.host = "https://api.mem0.ai";
client.telemetryId = "test@example.com";
await client._maybeAliasAnonToEmail();
} finally {
if (original === undefined) delete process.env.MEM0_TELEMETRY;
else process.env.MEM0_TELEMETRY = original;
jest.resetModules();
}
const identifyCalls = (fetchMock.mock.calls as any[]).filter(
([, init]: [string, RequestInit]) => {
if (!init?.body) return false;
return JSON.parse(init.body as string).event === "$identify";
},
);
expect(identifyCalls.length).toBe(0);
const written = JSON.parse(
fs.readFileSync(path.join(tmpHome, "config.json"), "utf8"),
);
expect(written.telemetry?.aliased_pairs).toBeUndefined();
});
});
// ─── Browser env path (no process.versions.node) ─────────────
describe("config.ts in browser-like environment", () => {
test("readMem0AnonIds returns null when not Node", async () => {
const originalProcess = global.process;
// @ts-expect-error force-undefining global to simulate a browser
delete global.process;
try {
jest.resetModules();
const { readMem0AnonIds: browserRead } = await import("../config");
expect(await browserRead()).toBeNull();
} finally {
global.process = originalProcess;
jest.resetModules();
}
});
});
+7 -1
View File
@@ -53,6 +53,7 @@ import {
ScoredResult,
} from "../utils/scoring";
import { getDefaultVectorStoreDbPath } from "../utils/sqlite";
import { getOrCreateMem0UserId } from "../../../client/config";
// Entity params that must be passed via filters - check both snake_case and camelCase
const ENTITY_PARAMS = [
@@ -466,7 +467,12 @@ export class Memory {
this.telemetryId === "anonymous" ||
this.telemetryId === "anonymous-supabase"
) {
this.telemetryId = await this.vectorStore.getUserId();
this.telemetryId =
(await getOrCreateMem0UserId()) ||
(await this.vectorStore.getUserId());
try {
await this.vectorStore.setUserId(this.telemetryId);
} catch {}
}
return this.telemetryId;
} catch (error) {
+63 -34
View File
@@ -1,9 +1,33 @@
import type { Client as ClientType } from "pg";
import pkg from "pg";
const { Client } = pkg;
const { Client, escapeIdentifier } = pkg;
import { VectorStore } from "./base";
import { SearchFilters, VectorStoreConfig, VectorStoreResult } from "../types";
const SAFE_IDENTIFIER_RE = /^[a-zA-Z_][a-zA-Z0-9_]{0,127}$/;
function validateIdentifier(
name: string,
label: string = "identifier",
): string {
if (!SAFE_IDENTIFIER_RE.test(name)) {
throw new Error(
`Invalid ${label} '${name}': only letters, digits, and underscores are allowed, ` +
`must start with a letter or underscore, and be at most 128 characters.`,
);
}
return name;
}
function escapeFilterKey(key: string): string {
if (!SAFE_IDENTIFIER_RE.test(key)) {
throw new Error(
`Invalid filter key '${key}': only letters, digits, and underscores are allowed.`,
);
}
return key;
}
interface PGVectorConfig extends VectorStoreConfig {
dbname?: string;
user: string;
@@ -25,10 +49,13 @@ export class PGVector implements VectorStore {
private _initPromise?: Promise<void>;
constructor(config: PGVectorConfig) {
this.collectionName = config.collectionName || "memories";
this.collectionName = validateIdentifier(
config.collectionName || "memories",
"collectionName",
);
this.useDiskann = config.diskann || false;
this.useHnsw = config.hnsw || false;
this.dbName = config.dbname || "vector_store";
this.dbName = validateIdentifier(config.dbname || "vector_store", "dbname");
this.config = config;
this.client = new Client({
@@ -41,6 +68,10 @@ export class PGVector implements VectorStore {
this.initialize().catch(console.error);
}
private col(): string {
return escapeIdentifier(this.collectionName);
}
async initialize(): Promise<void> {
if (!this._initPromise) {
this._initPromise = this._doInitialize();
@@ -102,31 +133,28 @@ export class PGVector implements VectorStore {
}
private async createDatabase(dbName: string): Promise<void> {
// Create database (cannot be parameterized)
await this.client.query(`CREATE DATABASE ${dbName}`);
await this.client.query(`CREATE DATABASE ${escapeIdentifier(dbName)}`);
}
private async createCol(embeddingModelDims: number): Promise<void> {
// Create the table
const dims = Math.floor(embeddingModelDims);
await this.client.query(`
CREATE TABLE IF NOT EXISTS ${this.collectionName} (
CREATE TABLE IF NOT EXISTS ${this.col()} (
id UUID PRIMARY KEY,
vector vector(${embeddingModelDims}),
vector vector(${dims}),
payload JSONB
);
`);
// Create indexes based on configuration
if (this.useDiskann && embeddingModelDims < 2000) {
try {
// Check if vectorscale extension is available
const result = await this.client.query(
"SELECT * FROM pg_extension WHERE extname = 'vectorscale'",
);
if (result.rows.length > 0) {
await this.client.query(`
CREATE INDEX IF NOT EXISTS ${this.collectionName}_diskann_idx
ON ${this.collectionName}
CREATE INDEX IF NOT EXISTS ${escapeIdentifier(this.collectionName + "_diskann_idx")}
ON ${this.col()}
USING diskann (vector);
`);
}
@@ -136,8 +164,8 @@ export class PGVector implements VectorStore {
} else if (this.useHnsw) {
try {
await this.client.query(`
CREATE INDEX IF NOT EXISTS ${this.collectionName}_hnsw_idx
ON ${this.collectionName}
CREATE INDEX IF NOT EXISTS ${escapeIdentifier(this.collectionName + "_hnsw_idx")}
ON ${this.col()}
USING hnsw (vector vector_cosine_ops);
`);
} catch (error) {
@@ -153,16 +181,15 @@ export class PGVector implements VectorStore {
): Promise<void> {
const values = vectors.map((vector, i) => ({
id: ids[i],
vector: `[${vector.join(",")}]`, // Format vector as string with square brackets
vector: `[${vector.join(",")}]`,
payload: payloads[i],
}));
const query = `
INSERT INTO ${this.collectionName} (id, vector, payload)
INSERT INTO ${this.col()} (id, vector, payload)
VALUES ($1, $2::vector, $3::jsonb)
`;
// Execute inserts in parallel using Promise.all
await Promise.all(
values.map((value) =>
this.client.query(query, [value.id, value.vector, value.payload]),
@@ -182,7 +209,8 @@ export class PGVector implements VectorStore {
if (filters) {
for (const [key, value] of Object.entries(filters)) {
filterConditions.push(`payload->>'${key}' = $${filterIndex}`);
const safeKey = escapeFilterKey(key);
filterConditions.push(`payload->>'${safeKey}' = $${filterIndex}`);
filterValues.push(value);
filterIndex++;
}
@@ -195,7 +223,7 @@ export class PGVector implements VectorStore {
const searchQuery = `
SELECT id, ts_rank_cd(to_tsvector('simple', payload->>'textLemmatized'), plainto_tsquery('simple', $1)) AS score, payload
FROM ${this.collectionName}
FROM ${this.col()}
WHERE to_tsvector('simple', payload->>'textLemmatized') @@ plainto_tsquery('simple', $1)
${filterClause}
ORDER BY score DESC
@@ -221,13 +249,14 @@ export class PGVector implements VectorStore {
filters?: SearchFilters,
): Promise<VectorStoreResult[]> {
const filterConditions: string[] = [];
const queryVector = `[${query.join(",")}]`; // Format query vector as string with square brackets
const queryVector = `[${query.join(",")}]`;
const filterValues: any[] = [queryVector, topK];
let filterIndex = 3;
if (filters) {
for (const [key, value] of Object.entries(filters)) {
filterConditions.push(`payload->>'${key}' = $${filterIndex}`);
const safeKey = escapeFilterKey(key);
filterConditions.push(`payload->>'${safeKey}' = $${filterIndex}`);
filterValues.push(value);
filterIndex++;
}
@@ -240,7 +269,7 @@ export class PGVector implements VectorStore {
const searchQuery = `
SELECT id, vector <=> $1::vector AS distance, payload
FROM ${this.collectionName}
FROM ${this.col()}
${filterClause}
ORDER BY distance
LIMIT $2
@@ -251,13 +280,13 @@ export class PGVector implements VectorStore {
return result.rows.map((row) => ({
id: row.id,
payload: row.payload,
score: row.distance,
score: Math.max(0, Math.min(1, 1 - Number(row.distance))),
}));
}
async get(vectorId: string): Promise<VectorStoreResult | null> {
const result = await this.client.query(
`SELECT id, payload FROM ${this.collectionName} WHERE id = $1`,
`SELECT id, payload FROM ${this.col()} WHERE id = $1`,
[vectorId],
);
@@ -274,10 +303,10 @@ export class PGVector implements VectorStore {
vector: number[],
payload: Record<string, any>,
): Promise<void> {
const vectorStr = `[${vector.join(",")}]`; // Format vector as string with square brackets
const vectorStr = `[${vector.join(",")}]`;
await this.client.query(
`
UPDATE ${this.collectionName}
UPDATE ${this.col()}
SET vector = $1::vector, payload = $2::jsonb
WHERE id = $3
`,
@@ -286,14 +315,13 @@ export class PGVector implements VectorStore {
}
async delete(vectorId: string): Promise<void> {
await this.client.query(
`DELETE FROM ${this.collectionName} WHERE id = $1`,
[vectorId],
);
await this.client.query(`DELETE FROM ${this.col()} WHERE id = $1`, [
vectorId,
]);
}
async deleteCol(): Promise<void> {
await this.client.query(`DROP TABLE IF EXISTS ${this.collectionName}`);
await this.client.query(`DROP TABLE IF EXISTS ${this.col()}`);
}
private async listCols(): Promise<string[]> {
@@ -315,7 +343,8 @@ export class PGVector implements VectorStore {
if (filters) {
for (const [key, value] of Object.entries(filters)) {
filterConditions.push(`payload->>'${key}' = $${paramIndex}`);
const safeKey = escapeFilterKey(key);
filterConditions.push(`payload->>'${safeKey}' = $${paramIndex}`);
filterValues.push(value);
paramIndex++;
}
@@ -328,14 +357,14 @@ export class PGVector implements VectorStore {
const listQuery = `
SELECT id, payload
FROM ${this.collectionName}
FROM ${this.col()}
${filterClause}
LIMIT $${paramIndex}
`;
const countQuery = `
SELECT COUNT(*)
FROM ${this.collectionName}
FROM ${this.col()}
${filterClause}
`;
+126
View File
@@ -0,0 +1,126 @@
/// <reference types="jest" />
const searchRows = [
{
id: "a",
payload: { data: "exactly x-axis" },
distance: "0",
},
{
id: "b",
payload: { data: "close to x-axis" },
distance: "0.006116251198662548",
},
{
id: "c",
payload: { data: "y-axis" },
distance: "1",
},
{
id: "d",
payload: { data: "opposite x-axis" },
distance: "2",
},
];
function mockPgQuery(sql: string) {
if (sql.includes("SELECT 1 FROM pg_database")) {
return { rows: [{ "?column?": 1 }] };
}
if (sql.includes("FROM information_schema.tables")) {
return { rows: [{ table_name: "memories" }] };
}
if (sql.includes("vector <=> $1::vector AS distance")) {
return { rows: searchRows };
}
return { rows: [] };
}
jest.mock("pg", () => {
const clients: any[] = [];
const Client = jest.fn().mockImplementation((config: any) => {
const client = {
config,
connect: jest.fn().mockResolvedValue(undefined),
end: jest.fn().mockResolvedValue(undefined),
query: jest
.fn()
.mockImplementation(async (sql: string) => mockPgQuery(sql)),
};
clients.push(client);
return client;
});
const escapeIdentifier = (str: string) => `"${str.replace(/"/g, '""')}"`;
return {
__esModule: true,
default: { Client, escapeIdentifier },
Client,
escapeIdentifier,
__mock: { Client, clients },
};
});
import { PGVector } from "../src/vector_stores/pgvector";
describe("PGVector - search()", () => {
beforeEach(() => {
const pg = require("pg");
pg.__mock.Client.mockClear();
pg.__mock.clients.length = 0;
});
test("returns similarity score (1 - distance) clamped to [0, 1]", async () => {
const store = new PGVector({
collectionName: "memories",
user: "postgres",
password: "postgres",
host: "localhost",
port: 5432,
embeddingModelDims: 3,
dimension: 3,
} as any);
await store.initialize();
const results = await store.search([1, 0, 0], 4);
expect(results).toEqual([
{
id: "a",
payload: { data: "exactly x-axis" },
score: 1,
},
{
id: "b",
payload: { data: "close to x-axis" },
score: 0.9938837488013375,
},
{
id: "c",
payload: { data: "y-axis" },
score: 0,
},
{
id: "d",
payload: { data: "opposite x-axis" },
score: 0,
},
]);
const pg = require("pg");
expect(pg.__mock.Client).toHaveBeenCalledTimes(2);
const activeClient = pg.__mock.clients[1];
expect(activeClient.query).toHaveBeenCalledWith(
expect.stringContaining("vector <=> $1::vector AS distance"),
["[1,0,0]", 4],
);
});
});
+30 -2
View File
@@ -19,8 +19,8 @@ from mem0.client.types import (
from mem0.client.utils import api_error_handler
# Exception classes are referenced in docstrings only
from mem0.memory.setup import get_user_id, setup_config
from mem0.memory.telemetry import capture_client_event
from mem0.memory.setup import get_user_id, is_aliased, mark_aliased, read_anon_ids, setup_config
from mem0.memory.telemetry import capture_client_event, client_telemetry
logger = logging.getLogger(__name__)
@@ -33,6 +33,32 @@ setup_config()
ENTITY_PARAMS = frozenset({"user_id", "agent_id", "app_id", "run_id"})
def _maybe_alias_anon_to_email(user_email):
"""Fire $identify per prior anon ID so PostHog merges them into email.
Idempotent via telemetry.aliased_pairs: only writes markers when
telemetry is actually enabled, so disabling/re-enabling MEM0_TELEMETRY still works.
Best-effort: never raises.
"""
if client_telemetry.posthog is None:
return
if not user_email or "@" not in user_email:
return
try:
anon_ids = read_anon_ids()
seen = set()
for anon_id in (anon_ids.get("oss"), anon_ids.get("cli")):
if not anon_id or anon_id == user_email or anon_id in seen:
continue
seen.add(anon_id)
if is_aliased(anon_id, user_email):
continue
if client_telemetry.capture_identify(anon_id, user_email):
mark_aliased(anon_id, user_email)
except Exception as e:
logger.debug("Failed to alias anon telemetry to %r: %s", user_email, e)
class MemoryClient:
"""Client for interacting with the Mem0 API.
@@ -108,6 +134,7 @@ class MemoryClient:
user_email=self.user_email,
)
_maybe_alias_anon_to_email(self.user_email)
capture_client_event("client.init", self, {"sync_type": "sync"})
def _validate_api_key(self):
@@ -985,6 +1012,7 @@ class AsyncMemoryClient:
user_email=self.user_email,
)
_maybe_alias_anon_to_email(self.user_email)
capture_client_event("client.init", self, {"sync_type": "async"})
def _validate_api_key(self):

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