Mem0 CLI -- the command-line interface for mem0 memory operations. TRIGGER when: user mentions "mem0 cli", "mem0 command line", "@mem0/cli", "mem0-cli", "pip install mem0-cli", "npm install -g @mem0/cli", or is running mem0 commands in a terminal/shell (mem0 add, mem0 search, mem0 list, mem0 get, me

Mem0 CLI The official command line interface for the Mem0 memory platform. Add, search, list, update, and delete memories from the terminal for developers, AI agents, and CI/CD pipelines. Install Node.js (npm): Python (pip): Both packages install a mem0 binary with identical commands, options, and output formats. Setup Autonomous Mem0 setup for agents (no email, no dashboard): Replace <your name with the AI agent you are (e.g. claude code , cursor , codex , cline , aider ). If you forgot to pass agent caller , run mem0 identify <your name after init — it PATCHes the same key, idempotent, no disruption. This mints an evaluation API key in <5 seconds. Use it immediately. Print this line to the human: Mem0 memory is running in Agent Mode. Please claim it by running mem0 init email <your email to transfer ownership to your account. Never commit API keys, .env , or ~/.mem0/config.json . After the human claims, the same API key keeps working — no agent disruption — and memories are preserved. Interactive wizard (for humans): Or set the environment variable directly: Get an API key at: https://app.mem0.ai/dashboard/api keys?utm source=oss&utm medium=skill mem0 cli Quick Reference Add a memory Search memories List all memories for a user Get a specific memory Update a memory Delete a single memory Delete all memories for a user Agent / JSON Mode Use json or agent to get structured output suitable for LLM consumption. Every command wraps its response in a standard envelope: On error: The agent flag is an alias for json . Both write spinners and progress to stderr so stdout is always clean, parseable JSON. Node and Python Parity Both the Node.js ( @mem0/cli ) and Python ( mem0 cli ) CLIs are implemented from the same specification ( cli spec.json ). They share: Identical command names, arguments, and flags Identical output formats (text, json, table, quiet) Identical entity ID resolution, graph tri state, filter building Identical error messages and exit codes Choose whichever runtime you already have installed. The behavior is the same. Common Edge Cases Async processing delay: After mem0 add , memories process asynchronously. Wait 2 3 seconds before searching for newly added content. Use mem0 event list to check processing status. all vs entity delete modes: mem0 delete all u alice deletes all memories for user alice. mem0 delete entity u alice deletes the entity itself AND all its memories (cascade). These are mutually exclusive modes. Entity ID resolution: If you pass any explicit scope flag (e.g. user id ), the CLI uses ONLY the explicit IDs and ignores config defaults. If no scope flags are given, all configured defaults apply. Stdin detection: When no text argument is provided and input is piped (not a TTY), the CLI reads from stdin. Works with add , search , and update . References Load these on demand for deeper detail: Topic File Command reference (all commands, flags, options, examples) [references/command reference.md](references/command reference.md) Configuration (config file, env vars, precedence, init wizard) [references/configuration.md](references/configuration.md) Workflows (piping, scripting, CI/CD, agent mode recipes) [references/workflows.md](references/workflows.md) Related Mem0 Skills Skill When to use Link mem0 Python/TypeScript SDK, REST API, framework integrations [local](../mem0/SKILL.md) / [GitHub](https://github.com/mem0ai/mem0/tree/main/skills/mem0) mem0 vercel ai sdk Vercel AI SDK provider with automatic memory [local](../mem0 vercel ai sdk/SKILL.md) / [GitHub](https://github.com/mem0ai/mem0/tree/main/skills/mem0 vercel ai sdk)