Name: mem0-cli
Author: mem0ai

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 the same commands, options, and output formats (see [Node and Python Differences]( node and python differences) for the exceptions). 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. Place the flag before the subcommand ( mem0 json search "q" ), which works in both CLIs. Data commands (add, search, list, get, update, delete, import, config, entity, event, status) wrap their response in a standard envelope: On error: The agent flag is an alias for json (except on mem0 init , where agent is the Agent Mode bootstrap flag). Both write spinners and progress to stderr so stdout is clean, parseable JSON (the one exception is Node import , see below). Optional keys: duration ms , scope , count appear only where relevant, and mem0 notice appears when the platform flags an unclaimed Agent Mode account. Node and Python Differences Both the Node.js ( @mem0/cli ) and Python ( mem0 cli ) CLIs share the command set, flags, entity ID resolution, filter building, and the JSON envelope. Choose whichever runtime you already have installed. Known differences: json / agent placement: Python accepts the flag anywhere on the command line. Node reads it only as a global option, so put it before the subcommand ( mem0 json list ). mem0 init json and mem0 help json work after the subcommand in both. For the Agent Mode bootstrap, Node starts it only from init agent or init json (a root level mem0 json init or mem0 agent init does not start it, and without an agent runtime env var it fails with the non TTY error), while Python also accepts those root level forms. mem0 init agent json works in both. limit : mem0 search limit is a Python only alias for top k . Agent mode delete all data: Python returns {"deleted": true} (plus scope for project ); Node returns the raw API result. import JSON output: Python prints the envelope with scope . Node omits scope and writes the Importing memories... n/n progress line to stdout before the JSON, so only Python's output pipes cleanly to jq . Message text: The empty search error ( Search query cannot be empty. in Python, No query provided... in Node) and the delete dry run footers differ slightly. 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. dry run in json / agent mode: mem0 json delete all dry run still requires force , then prints nothing and deletes nothing (exit 0). Node also prints nothing for single and entity dry runs. Use text mode to see the preview. dry run does not protect all project : mem0 delete all project dry run ignores the flag and deletes every memory in the project. Never use dry run to preview a project wide delete. 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 stdin is a pipe or a redirected file (a plain non TTY is not enough), the CLI reads from stdin. Works with add , search , and update . In json / agent mode add never reads stdin (Python also skips it for search and update ), so pass the text as an argument there. 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)