mem0-cli

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):

npm install -g @mem0/cli

Python (pip):

pip install mem0-cli

Both packages install a mem0 binary with the same commands, options, and output formats (see Node and Python Differences for the exceptions).

Setup

Autonomous Mem0 setup for agents (no email, no dashboard):

mem0 init --agent --agent-caller <your-name> --json

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):

mem0 init

Or set the environment variable directly:

export MEM0_API_KEY="m0-xxx"

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

mem0 add "I prefer dark mode" --user-id alice

Search memories

mem0 search "preferences" --user-id alice

List all memories for a user

mem0 list --user-id alice

Get a specific memory

mem0 get <memory-id>

Update a memory

mem0 update <memory-id> "new text"

Delete a single memory

mem0 delete <memory-id>

Delete all memories for a user

mem0 delete --all --user-id alice --force

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:

{
  "status": "success",
  "command": "search",
  "duration_ms": 245,
  "scope": { "user_id": "alice" },
  "count": 3,
  "data": [
    { "id": "mem-abc", "memory": "User prefers dark mode", "score": 0.92 }
  ]
}

On error:

{
  "status": "error",
  "command": "search",
  "error": "Invalid or expired API key.",
  "data": null
}

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
Configuration (config file, env vars, precedence, init wizard)	references/configuration.md
Workflows (piping, scripting, CI/CD, agent mode recipes)	references/workflows.md

Related Mem0 Skills

Skill	When to use	Link
mem0	Python/TypeScript SDK, REST API, framework integrations	local / GitHub
mem0-vercel-ai-sdk	Vercel AI SDK provider with automatic memory	local / GitHub