OpenClaw - Mem0

Add long-term memory to OpenClaw agents with the @mem0/openclaw-mem0 plugin. Your agent forgets everything between sessions — this plugin fixes that by automatically watching conversations, extracting what matters, and bringing it back when relevant.

Overview

The plugin provides:

1. Auto-Recall — Before the agent responds, memories matching the current message are injected into context
2. Auto-Capture — After the agent responds, the exchange is sent to Mem0 which decides what’s worth keeping
3. Agent Tools — Five tools for explicit memory operations during conversations

Both auto-recall and auto-capture run silently with no manual configuration required.

Installation

openclaw plugins install @mem0/openclaw-mem0

Setup and Configuration

Platform Mode (Mem0 Cloud)

Add to your openclaw.json:

// plugins.entries
"openclaw-mem0": {
  "enabled": true,
  "config": {
    "apiKey": "${MEM0_API_KEY}",
    "userId": "your-user-id"
  }
}

Open-Source Mode (Self-hosted)

No Mem0 key needed. Requires OPENAI_API_KEY for default embeddings/LLM.

"openclaw-mem0": {
  "enabled": true,
  "config": {
    "mode": "open-source",
    "userId": "your-user-id"
  }
}

Sensible defaults work out of the box. To customize the embedder, vector store, or LLM:

"config": {
  "mode": "open-source",
  "userId": "your-user-id",
  "oss": {
    "embedder": { "provider": "openai", "config": { "model": "text-embedding-3-small" } },
    "vectorStore": { "provider": "qdrant", "config": { "host": "localhost", "port": 6333 } },
    "llm": { "provider": "openai", "config": { "model": "gpt-4o" } }
  }
}

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

Short-term vs Long-term Memory

Memories are organized into two scopes:

• Session (short-term) — Auto-capture stores memories scoped to the current session via Mem0’s run_id / runId parameter. These are contextual to the ongoing conversation.
• User (long-term) — The agent can explicitly store long-term memories using the memory_store tool (with longTerm: true, the default). These persist across all sessions for the user.

During auto-recall, the plugin searches both scopes and presents them separately — long-term memories first, then session memories — so the agent has full context.

The agent gets five tools it can call during conversations:

The memory_search and memory_list tools accept a scope parameter ("session", "long-term", or "all") to control which memories are queried. The memory_store tool accepts a longTerm boolean (default: true) to choose where to store.

CLI Commands

# Search all memories (long-term + session)
openclaw mem0 search "what languages does the user know"

# Search only long-term memories
openclaw mem0 search "what languages does the user know" --scope long-term

# Search only session/short-term memories
openclaw mem0 search "what languages does the user know" --scope session

# View stats
openclaw mem0 stats

Configuration Options

General Options

Platform Mode Options

Open-Source Mode Options

Everything inside oss is optional — defaults use OpenAI embeddings (text-embedding-3-small), in-memory vector store, and OpenAI LLM.

Key Features

1. Zero Configuration — Auto-recall and auto-capture work out of the box with no prompting required
2. Dual Memory Scopes — Session-scoped short-term and user-scoped long-term memories
3. Flexible Backend — Use Mem0 Cloud for managed service or self-host with open-source mode
4. Rich Tool Suite — Five agent tools for explicit memory operations when needed

Conclusion

The @mem0/openclaw-mem0 plugin gives OpenClaw agents persistent memory with minimal setup. Whether using Mem0 Cloud or self-hosting, your agents can now remember user preferences, facts, and context across sessions automatically.