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Mgeeeek a2516269cc Surface mem0_notice for unclaimed Agent Mode keys + docs 
CLI now consumes the unified mem0_notice surface that the platform side
emits for unclaimed Agent Mode keys. The notice is a directive to the
LLM agent reading the output, with a verbatim sentence to relay to the
human owner. Two presentation paths:

- Human/text output: yellow stderr banner after the primary output,
  once per command. Skipped in agent mode (the JSON envelope carries
  it instead, so no duplication).
- JSON/agent output (--json/--agent): folded into the envelope as
  "mem0_notice" so an agent parsing the output sees it without
  inspecting HTTP headers.

CLI changes (Python + Node, kept in lockstep):
- state.{ts,py}: captureNotice / takeNotice helpers — last-write-wins
  stash so multi-request commands fire the notice exactly once.
- backend/platform.{ts,py}: _request extracts notice from response
  bodies (top-level dict or list[0]) with header fallback, strips
  from downstream payload, captures for end-of-command surfacing.
- output.{ts,py}: JSON envelope formatters fold in any pending notice.
- index.ts / app.py: entrypoint surfaces notice on exit when not in
  agent mode.
- commands/agent-mode.{ts,py}: init success path prints the platform's
  notice verbatim (fallback to dim claim-command line if a stale
  backend doesn't return it).

Init-flag handling fix: the Python argv preprocessor was stripping
--agent from sys.argv unconditionally as the global JSON-output alias.
That swallowed `mem0 init --agent` (where --agent is a subcommand flag
for unattended bootstrap). Now preserved when "init" is in argv.

Parity tests: cli/python/tests/test_agent_mode.py and
cli/node/tests/agent-mode.test.ts — 7 tests each, kept in sync.

cli-spec.json updated: init now lists --agent and --source.

Docs:
- README.md: Agent Mode promo at top of Quickstart.
- docs/llms.txt: fast-path block for AI agents reading the docs.
- skills/mem0/SKILL.md, skills/mem0-cli/SKILL.md,
  skills/mem0-integrate/SKILL.md, mem0-plugin/skills/mem0/SKILL.md:
  autonomous-setup section + fallback hints.
- mem0-plugin/README.md, openclaw/README.md: "Quick path for agents"
  blocks above the human Quick Start.
2026-05-14 02:11:39 +05:30
..
references
fix: update skills and docs (#4868)
2026-04-18 11:42:37 +05:30
LICENSE
feat(skills): introduce Mem0 skill graph with dedicated CLI and Vercel AI SDK skills (#4725)
2026-04-06 20:41:29 +05:30
README.md
Self-hosted dashboard and admin auth (#4837)
2026-04-23 19:06:36 +05:30
SKILL.md
Surface mem0_notice for unclaimed Agent Mode keys + docs
2026-05-14 02:11:39 +05:30

README.md

Mem0 CLI Skill for Claude

Manage memories from the terminal using the Mem0 CLI. This skill teaches Claude how to use every mem0 command, flag, and output mode -- for both the Node.js and Python implementations.

What This Skill Does

When installed, Claude can:

  • Run mem0 commands correctly in your terminal (add, search, list, get, update, delete, import, config, init, status, entity, event)
  • Construct complex invocations with the right flags, scoping, filters, and output formats
  • Pipe and script mem0 commands in shell workflows, CI/CD pipelines, and agent loops
  • Debug issues like missing API keys, entity scoping conflicts, and async processing delays

Installation

CLI (Claude Code, OpenCode, OpenClaw, or any tool that supports skills)

npx skills add https://github.com/mem0ai/mem0 --skill mem0-cli

Claude.ai

  1. Download this skills/mem0-cli folder as a ZIP
  2. Go to Settings > Capabilities > Skills
  3. Click Upload skill and select the ZIP

Claude API (Skills API)

curl -X POST https://api.anthropic.com/v1/skills \
  -H "x-api-key: $ANTHROPIC_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"name": "mem0-cli", "source": "https://github.com/mem0ai/mem0/tree/main/skills/mem0-cli"}'

Prerequisites

  • A Mem0 Platform API key (Get one here)

  • Node.js 18+ or Python 3.10+

  • Install the CLI:

    # Node.js
npm install -g @mem0/cli

# Python
pip install mem0-cli

  • Set the environment variable:

    export MEM0_API_KEY="m0-your-api-key"

    Or run mem0 init for the interactive setup wizard.

Quick Start

After installing, just ask Claude:

  • "Add a memory for user alice that she prefers dark mode"
  • "Search alice's memories for dietary preferences"
  • "List all memories and output as JSON"
  • "Delete all memories for user bob"
  • "Set up mem0 CLI in my CI pipeline"
  • "Pipe the output of my script into mem0 add"

What's Inside

skills/mem0-cli/
├── SKILL.md                          # Skill definition and instructions
├── README.md                         # This file
├── LICENSE                           # Apache-2.0
└── references/                       # Documentation (loaded on demand)
    ├── command-reference.md           # Every command, flag, option, and example
    ├── configuration.md               # Config file, env vars, precedence, init wizard
    └── workflows.md                   # Piping, scripting, CI/CD, agent mode recipes

Links

Skill Graph

This skill is part of the Mem0 skill graph -- three interconnected skills for different interfaces to the Mem0 platform:

Skill Purpose Link
mem0 Python/TypeScript SDK, REST API, framework integrations local / GitHub
mem0-cli (this skill) Terminal commands for memory operations local / GitHub
mem0-vercel-ai-sdk Vercel AI SDK provider with automatic memory local / GitHub

License

Apache-2.0

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