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.

"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-4o" } }
  }
}

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

How It Works

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

Scope	Description
Session (short-term)	Memories scoped to the current conversation via `run_id`. Automatically recalled alongside long-term memories.
User (long-term)	Persistent memories that span all sessions. Stored via `memory_add` with `longTerm: true` (the default).

During auto-recall, both scopes are searched and presented separately — long-term first, then session — so the agent has full context.

Multi-Agent Isolation

In multi-agent setups, each agent gets its own memory namespace automatically. Session keys matching agent:<name>:<uuid> route memories to userId:agent:<name>. Single-agent deployments are unaffected.

All memory tools accept an optional agentId parameter for cross-agent queries:

memory_search({ query: "user's tech stack", agentId: "researcher" })

Agent Tools

Seven tools are available to the agent during conversations:

Tool	Description
`memory_search`	Search memories by natural language query. Supports `scope` (`session`, `long-term`, `all`) and `agentId` filtering.
`memory_add`	Save a fact to memory. Supports `category`, `importance`, `longTerm`, and `agentId`.
`memory_get`	Retrieve a specific memory by ID.
`memory_list`	List stored memories with optional `userId`, `agentId`, and `limit` filters.
`memory_update`	Update an existing memory's text in place. Preserves edit history.
`memory_delete`	Delete by ID, search query, or bulk (`all: true`). Requires `confirm: true` for bulk.
`memory_history`	View the edit history of a specific memory.

CLI

All commands follow the pattern openclaw mem0 <command>.

Memory Operations

# Add a memory
openclaw mem0 add "User prefers TypeScript over JavaScript"

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

# Get, list, update, delete
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

# View edit history
openclaw mem0 history <memory_id>

Management

# Authenticate and configure
openclaw mem0 init
openclaw mem0 init --api-key <key> --user-id alice

# Check connectivity
openclaw mem0 status

# Manage configuration
openclaw mem0 config show
openclaw mem0 config get api_key
openclaw mem0 config set user_id alice

# Memory consolidation (review, merge, prune)
openclaw mem0 dream
openclaw mem0 dream --dry-run

Configuration Reference

General

Key	Type	Default	Description
`mode`	`"platform"` \| `"open-source"`	`"platform"`	Backend mode
`userId`	`string`	`"default"`	Unique identifier for the user. You define this — it's not found in any dashboard. All memories are scoped to this value.
`autoRecall`	`boolean`	`true`	Inject relevant memories before each turn
`autoCapture`	`boolean`	`true`	Extract and store facts after each turn
`topK`	`number`	`5`	Max memories returned per recall
`searchThreshold`	`number`	`0.5`	Minimum similarity score (0-1)

Platform Mode

Key	Type	Default	Description
`apiKey`	`string`	—	Required. Mem0 API key (supports `${MEM0_API_KEY}`)
`orgId`	`string`	—	Organization ID
`projectId`	`string`	—	Project ID
`enableGraph`	`boolean`	`false`	Enable entity graph for relationship tracking
`customInstructions`	`string`	(built-in)	Custom extraction rules for what to store and how to format
`customCategories`	`object`	(12 defaults)	Category name to description map for memory tagging

Open-Source Mode

All fields below are optional. Defaults use OpenAI embeddings, in-memory vector store, and OpenAI LLM.

Key	Type	Default	Description
`customPrompt`	`string`	(built-in)	Extraction prompt for memory processing
`oss.embedder.provider`	`string`	`"openai"`	Embedding provider
`oss.embedder.config`	`object`	—	Provider config (`apiKey`, `model`, `baseURL`)
`oss.vectorStore.provider`	`string`	`"memory"`	Vector store provider
`oss.vectorStore.config`	`object`	—	Provider config (`host`, `port`, `collectionName`)
`oss.llm.provider`	`string`	`"openai"`	LLM provider
`oss.llm.config`	`object`	—	Provider config (`apiKey`, `model`, `baseURL`)
`oss.historyDbPath`	`string`	—	SQLite path for memory edit history
`oss.disableHistory`	`boolean`	`false`	Skip history DB initialization

Supported providers: openai, anthropic, ollama, lmstudio, qdrant, chroma, and more. See the Mem0 OSS docs for the full list.

License

Apache 2.0