@mem0/openclaw-mem0

Long-term memory for OpenClaw agents, powered by Mem0.

Your agent forgets everything between sessions. This plugin fixes that — it watches conversations, extracts what matters, and brings it back when relevant. Automatically.

Quick Start

openclaw plugins install @mem0/openclaw-mem0

Platform (Mem0 Cloud)

Get an API key from app.mem0.ai:

openclaw mem0 init --api-key <your-key> --user-id <your-user-id>

Or configure manually in openclaw.json:

"openclaw-mem0": {
  "enabled": true,
  "config": {
    "apiKey": "${MEM0_API_KEY}",
    "userId": "alice"
  }
}

Open-Source (Self-hosted)

No Mem0 key needed. Requires OPENAI_API_KEY for default embeddings and LLM. Vectors are stored locally in SQLite at ~/.mem0/vector_store.db — no external database required.

Defaults: text-embedding-3-small for embeddings, gpt-5.4 for fact extraction.

"openclaw-mem0": {
  "enabled": true,
  "config": {
    "mode": "open-source",
    "userId": "alice"
  }
}

Customize the embedder, vector store, or LLM via the oss block:

"config": {
  "mode": "open-source",
  "userId": "alice",
  "oss": {
    "embedder": { "provider": "openai", "config": { "model": "text-embedding-3-small" } },
    "vectorStore": { "provider": "qdrant", "config": { "host": "localhost", "port": 6333 } },
    "llm": { "provider": "openai", "config": { "model": "gpt-5.4" } }
  }
}

All oss fields are optional. See the Mem0 OSS docs for supported providers.

How It Works

<p align="center"> <img src="https://raw.githubusercontent.com/mem0ai/mem0/main/docs/images/openclaw-architecture.png"; alt="Architecture" width="800" /> </p>

Auto-Recall — Before the agent responds, the plugin searches Mem0 for relevant memories and injects them into context.

Auto-Capture — After the agent responds, the conversation is filtered through a noise-removal pipeline and sent to Mem0. New facts get stored, stale ones updated, duplicates merged.

Both run silently. No prompting, no manual calls required.

Memory Scopes

• Session (short-term) — Scoped to the current conversation via run_id. Recalled alongside long-term memories.
• User (long-term) — Persistent across all sessions. Default for memory_add.

Multi-Agent Isolation

Each agent gets its own memory namespace automatically via session key routing (agent:<name>:<uuid> maps to userId:agent:<name>). Single-agent setups are unaffected.

Agent Tools

Eight tools are registered for agent use:

CLI

All commands: openclaw mem0 <command>.

# Memory operations
openclaw mem0 add "User prefers TypeScript over JavaScript"
openclaw mem0 search "what languages does the user know"
openclaw mem0 search "preferences" --scope long-term
openclaw mem0 get <memory_id>
openclaw mem0 list --user-id alice --top-k 20
openclaw mem0 update <memory_id> "Updated preference text"
openclaw mem0 delete <memory_id>
openclaw mem0 delete --all --user-id alice --confirm
openclaw mem0 import memories.json

# Management
openclaw mem0 init
openclaw mem0 init --api-key <key> --user-id alice
openclaw mem0 status
openclaw mem0 config show
openclaw mem0 config get api_key
openclaw mem0 config set user_id alice

# Events (platform only)
openclaw mem0 event list
openclaw mem0 event status <event_id>

# Memory consolidation
openclaw mem0 dream
openclaw mem0 dream --dry-run

Configuration Reference

General

Platform Mode

Open-Source Mode

All fields optional. Defaults: text-embedding-3-small embeddings, local SQLite vector store (~/.mem0/vector_store.db), gpt-5.4 LLM.

License

Apache 2.0