Openmemory

A FastMCP server that exposes mem0 long-term memory to MCP clients (e.g. an AI coding agent) over SSE.

It is a thin, stateless MCP layer over an existing mem0 REST server (http://mem0:8000) — it does not run its own vector store. This keeps a single source of truth for memory (the mem0 pgvector store) instead of introducing a second, disconnected memory silo.

Tools

Tool	Purpose
search_memory(query, user_id?, limit?)	Recall memories relevant to a query. Call at the start of a task.
add_memory(text, user_id?, role?)	Store a fact/preference/exchange. Use automatically when you learn something durable, or on explicit request.
list_memories(user_id?)	List stored memories for a bucket.
delete_memory(memory_id)	Forget a single memory by id.

Memory is isolated per user_id ("bucket"). When a caller omits user_id, MEM0_DEFAULT_USER_ID is used, giving the agent a single shared memory.

Configuration

Environment variables (prefix MEM0_):

Variable	Default	Description
MEM0_MEM0_URL	http://mem0:8000	Base URL of the mem0 REST server
MEM0_API_KEY	(none)	Admin API key, sent as X-API-Key
MEM0_DEFAULT_USER_ID	coder-agent	Bucket used when no user_id is passed
MEM0_SEARCH_LIMIT	5	Default number of memories per search
MEM0_TIMEOUT	10	HTTP timeout (s) for reads (search/list)
MEM0_WRITE_TIMEOUT	60	HTTP timeout (s) for writes (add runs a server-side LLM extraction)
MEM0_SERVER_HOST	0.0.0.0	Bind host for the SSE server
MEM0_SERVER_PORT	8000	Bind port for the SSE server

Run

pip install -e .
openmemory-mcp-sse   # SSE at http://0.0.0.0:8000/sse
# or
openmemory-mcp       # stdio mode

Container

Built by the release-containers workflow (release-please) to ghcr.io/dedsxc/openmemory-mcp:<version> for linux/amd64,linux/arm64.