Files
mem0/cli
Mgeeeek 4f40437d65 feat(cli): auto-sync active api_key to plugin env touchpoints
When saveConfig writes a fresh api_key (e.g. agent-mode bootstrap, OTP
signup), propagate the value into other ecosystem locations that hold
the same key:

  - ~/.claude/settings.json::env::MEM0_API_KEY (Claude Code env injection)
  - ~/.zshrc / ~/.bashrc / ~/.bash_profile `export MEM0_API_KEY="..."`

Without this, agent-mode bootstrap mints a new shadow into config.json
but the Claude plugin's MCP server keeps using the OLD env-var key —
silent surprise.

Hard guarantees:

  1. **Update-only**, never create. If a target file doesn't already
     contain a MEM0_API_KEY entry, we leave it alone. The user's
     existing setup decides which surfaces are managed; we don't
     unilaterally start writing to new files.
  2. **Preserve surrounding content.** JSON files keep all other keys.
     Shell rc files keep all other lines, comments, and the trailing
     newline (regex uses [ \t]* not \s*, which would eat the final \n
     when MEM0_API_KEY is the last line of .zshrc).
  3. **Atomic writes.** tmpfile + rename, so a crash mid-write leaves
     the original intact.
  4. **Idempotent.** If the target already has this value, no-op.
  5. **Best-effort.** Any IOError in the sync is swallowed; the
     canonical config.json write is never blocked by plugin-state.

Implemented identically in Python (plugin_sync.py) and Node
(plugin-sync.ts). Hooked into save_config() / saveConfig() so every
api_key change propagates without any caller plumbing.

Verified on a sandbox copy of real ~/.claude/settings.json and
~/.zshrc: only the MEM0_API_KEY values changed; all 36 other lines
in settings.json and 50+ lines in .zshrc preserved byte-for-byte
including the trailing newline.

Out of scope (deliberate non-changes):
  - ~/.codex/config.toml — no mem0 server entry to update
  - ~/.cursor/mcp.json — no mem0 server entry to update
  - <plugin-install-dir>/.api_key — plugin-managed, different schema
2026-05-14 16:19:21 +05:30
..

mem0 CLI

The official command-line interface for mem0 — the memory layer for AI agents. Works with the Mem0 Platform API. Available in Python and Node.js.

For AI agents: pass --agent (or --json) on any command for structured JSON output purpose-built for tool loops — sanitized fields, no colors or spinners, errors as JSON. See Agent mode below.

Installation

npm install -g @mem0/cli
pip install mem0-cli

Both packages install a mem0 binary with identical behavior.

Quick start

# Interactive setup wizard
mem0 init

# Or login via email (get a new API key)
mem0 init --email alice@company.com

# Or authenticate with an existing API key
mem0 init --api-key m0-xxx

# Add a memory
mem0 add "I prefer dark mode and use vim keybindings" --user-id alice

# Search memories
mem0 search "What are Alice's preferences?" --user-id alice

# List all memories for a user
mem0 list --user-id alice

# Update a memory
mem0 update <memory-id> "I switched to light mode"

# Delete a memory
mem0 delete <memory-id>

Commands

Command Description
mem0 init Setup wizard — login via email or configure API key manually
mem0 add Add a memory from text, JSON messages, a file, or stdin
mem0 search Search memories using natural language
mem0 list List memories with optional filters and pagination
mem0 get Retrieve a specific memory by ID
mem0 update Update the text or metadata of a memory
mem0 delete Delete a memory, all memories for a scope, or an entity
mem0 import Bulk import memories from a JSON file
mem0 config View or modify CLI configuration
mem0 entity List or delete entities (users, agents, apps, runs)
mem0 event Inspect background processing events (bulk deletes, large add jobs)
mem0 status Verify API connection and display current project
mem0 version Print the CLI version

Run mem0 <command> --help for detailed usage on any command.

Agent mode

Pass --agent (or its alias --json) as a global flag on any command to get output designed for AI agent tool loops:

mem0 --agent search "user preferences" --user-id alice
mem0 --agent add "User prefers dark mode" --user-id alice
mem0 --agent list --user-id alice

Every command returns the same envelope shape:

{
  "status": "success",
  "command": "search",
  "duration_ms": 134,
  "scope": { "user_id": "alice" },
  "count": 2,
  "data": [
    { "id": "abc-123", "memory": "User prefers dark mode", "score": 0.97, "created_at": "2026-01-15", "categories": ["preferences"] }
  ]
}

What agent mode does differently from --output json:

  • Sanitized data: only the fields an agent needs (id, memory, score, etc.) — no internal API noise
  • No human output: spinners, colors, and banners are suppressed entirely
  • Errors as JSON: errors go to stdout as {"status": "error", "command": "...", "error": "..."} with a non-zero exit code

Use mem0 help --json to get the full command tree as JSON — useful for agents that need to self-discover available commands.

Output formats

Control how results are displayed with --output:

Format Description
text Human-readable with colors and formatting (default)
json Structured JSON for piping to jq (raw API response)
table Tabular format (default for list)
quiet Minimal — just IDs or status codes
agent Structured JSON envelope with sanitized fields (set by --agent/--json)

Environment variables

Variable Description
MEM0_API_KEY API key (overrides config file)
MEM0_BASE_URL API base URL
MEM0_USER_ID Default user ID
MEM0_AGENT_ID Default agent ID
MEM0_APP_ID Default app ID
MEM0_RUN_ID Default run ID
MEM0_ENABLE_GRAPH Enable graph memory (true / false)

Implementations

Language Directory Package Docs
TypeScript node/ @mem0/cli README
Python python/ mem0-cli README

Documentation

Full documentation is available at docs.mem0.ai/platform/cli.

License

Apache-2.0