Files
Saket Aryan bc5526f13d feat(integrations): declare which surface each client is, and its version
Nothing on the wire said which Mem0 surface made a call. Both SDKs sent only an
auth header, so the platform saw python-httpx and axios and attributed every
plugin, wrapper and direct API user to one undifferentiated bucket. Version was
unknowable, which is what gates every deprecation decision.

Three headers, and the rules on them are the point:

- X-Mem0-Source and X-Application are SET-ONCE. Whichever layer is outermost
  sets them; nothing below overwrites. A plugin wrapping the SDK keeps its own
  identity instead of being renamed by the transport underneath it.
- X-Mem0-Client is APPEND-ONLY. A plugin calling the Python SDK produces
  `mem0-plugin/0.3.1, mem0-python/2.0.19`, so neither layer can erase the other.

Deliberately not User-Agent: proxies rewrite it, and we have already met a WAF
that 403s on it.

The plugin core also hoists `source` out of metadata to the top level, which is
where the backend actually reads it. It sat in metadata, which get_event_source
never consults, so all six plugins arrived indistinguishable from a raw SDK call
no matter what they set. The harness tag stays in metadata as hook provenance.

pi-agent had PI_AGENT as a PostHog property only and never sent it on the wire.
vercel-ai-sdk sent nothing at all from its raw fetch calls.

Values must exist in the platform's EventSource enum or they bucket to OTHERS,
so integrations/AGENTS.md now states the contract and the "adding an
integration" checklist requires landing the platform value in the same week.

Pairs with mem0ai/platform#3602, which recognizes these values.

TypeScript changes are not typechecked locally — deps are not installed for
those packages. CI covers them.

Claude-Session: https://claude.ai/code/session_01C7tEmH86HAr7GoAAKCEHZb
2026-09-15 00:19:00 +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

Run mem0 <command> --help for detailed usage on any command, or mem0 --version to print the CLI version.

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