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MCP server for Recollect

Project description

recollect-mcp

MCP server exposing cognitive memory via the Recollect SDK. 5 tools, 3 resources, server-managed sessions.

Install

pip install recollect-mcp

Usage

# stdio (default)
recollect-mcp

# streamable-http
recollect-mcp --transport streamable-http

Environment Variables

Variable Required Default Description
MEMORY_USER_ID Yes -- Scopes all operations to this user. Server refuses to start without it.
DATABASE_URL Yes postgresql://localhost:5432/memory_sdk PostgreSQL connection string.
ANTHROPIC_API_KEY For default provider -- Anthropic API key for LLM extraction.
OPENAI_API_KEY For OpenAI provider -- OpenAI API key.
ANTHROPIC_MODEL No claude-haiku-4-5-20251001 Override Anthropic extraction model.
OPENAI_MODEL No gpt-5-mini Override OpenAI extraction model.
OLLAMA_MODEL No qwen3.5 Override Ollama extraction model.
OLLAMA_BASE_URL No http://localhost:11434/v1 Ollama API endpoint.
MEMORY_CONFIG No -- Path to custom TOML config file.
SERVER_HOST No localhost Server bind host (streamable-http transport).
SERVER_PORT No 8000 Server bind port (streamable-http transport).

Client configuration

Add to .mcp.json (Claude Code) or claude_desktop_config.json (Claude Desktop):

{
  "mcpServers": {
    "memory": {
      "command": "uvx",
      "args": ["recollect-mcp"],
      "env": {
        "MEMORY_USER_ID": "your-user-id",
        "DATABASE_URL": "postgresql://user@localhost:5432/dbname",
        "ANTHROPIC_API_KEY": "sk-ant-..."
      }
    }
  }
}

Providers

The server uses Anthropic by default for LLM extraction. To use a different provider, set environment variables in the env block of your MCP client config.

Anthropic (default)

"env": {
  "MEMORY_USER_ID": "your-user-id",
  "DATABASE_URL": "postgresql://user@localhost:5432/dbname",
  "ANTHROPIC_API_KEY": "sk-ant-..."
}

OpenAI

"env": {
  "MEMORY_USER_ID": "your-user-id",
  "DATABASE_URL": "postgresql://user@localhost:5432/dbname",
  "OPENAI_API_KEY": "sk-...",
  "OPENAI_MODEL": "gpt-5-mini"
}

Ollama (local)

"env": {
  "MEMORY_USER_ID": "your-user-id",
  "DATABASE_URL": "postgresql://user@localhost:5432/dbname",
  "OLLAMA_MODEL": "qwen3.5",
  "OLLAMA_BASE_URL": "http://localhost:11434/v1"
}

Reasoning models (Qwen3, DeepSeek-R1) use thinking tokens that count against the extraction budget. If remember returns extraction errors, increase max_tokens via a custom config file:

# memory.toml
[extraction]
max_tokens = 8192

Custom configuration

Mount a memory.toml in the server's working directory, or set MEMORY_CONFIG:

"env": {
  "MEMORY_USER_ID": "your-user-id",
  "DATABASE_URL": "postgresql://user@localhost:5432/dbname",
  "ANTHROPIC_API_KEY": "sk-ant-...",
  "MEMORY_CONFIG": "/path/to/memory.toml"
}

Tools

Tool Parameters Description
remember content: str Store an experience. LLM extracts entities, concepts, significance, and persona facts.
recall query: str Retrieve relevant memories. Returns persona facts as context followed by matching traces.
pin content: str Promote a statement to a permanent persona fact (allergies, preferences, relationships).
unpin fact_id: str Remove a persona fact.
forget trace_id: str Delete a memory trace.

Resources

URI Description
memory://primer Relational graph of persona facts. Read at conversation start for user context.
memory://facts All active persona facts with confidence scores and timestamps.
memory://health Server and database health status.

Requirements

  • Python 3.12+
  • PostgreSQL 17 with pgvector

License

MIT

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