recollect-mcp 0.14.0

MCP server for Recollect

recollect-mcp

MCP server for persistent memory. 6 tools, 3 resources, server-managed sessions. See the project README for architecture details.

Install

pip install recollect-mcp    # or: uv add recollect-mcp

Usage

# stdio (default)
recollect-mcp

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

# with logging
recollect-mcp --log-file logs/mcp.jsonl --verbose

Tools

Tool	Parameters	Description
remember	content: str	Store an experience. LLM extracts entities, concepts, significance, and persona facts.
recall	query: str, token_budget: int = 2000	Retrieve relevant memories. Returns persona facts as context followed by matching traces.
reflect	--	Load persona context for the current session. Call before responding to any user message.
pin	trace_id: str	Promote a memory's extracted relations to permanent persona facts.
unpin	fact_id: str	Archive a persona fact. It stops surfacing in recall and reflect; the row is retained.
forget	trace_id: str, force: bool = false	Forget a memory trace: it stops surfacing in recall and never auto-revives. Derived facts archive; safety-critical (health/dietary/constraint) and pinned facts are retained unless force=true. Nothing is hard-deleted.

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.

Clients that support MCP resources get session priming automatically via primer. For clients that don't, reflect loads the same context as a tool call. If neither is invoked, the first recall of the session still surfaces safety-critical persona facts (pinned, health, dietary) as a fallback -- the full relational context comes from primer or reflect.

Client configuration

Add to .mcp.json (Claude Code) or claude_desktop_config.json (Claude Desktop). Keep API keys out of the JSON: put them in an env file and pass it with --env-file. Use an absolute path -- the client spawns the server from its own working directory.

{
  "mcpServers": {
    "memory": {
      "command": "uvx",
      "args": [
        "--env-file",
        "/Users/you/.config/recollect/recollect.env",
        "recollect-mcp"
      ],
      "env": {
        "MEMORY_USER_ID": "your-user-id",
        "DATABASE_URL": "postgresql://user@localhost:5432/dbname",
        "PYDANTIC_AI_MODEL": "anthropic:claude-haiku-4-5-20251001"
      }
    }
  }
}

# /Users/you/.config/recollect/recollect.env -- secrets only, chmod 600
ANTHROPIC_API_KEY=sk-ant-...

Variables in the env block take precedence over the env file, so define each in one place only.

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.
PYDANTIC_AI_MODEL	No	--	pydantic-ai model string in provider:model format (e.g., ollama:ministral-3, anthropic:claude-haiku-4-5-20251001).
ANTHROPIC_API_KEY	For Anthropic models	--	Anthropic API key. Read by pydantic-ai's Anthropic backend.
OPENAI_API_KEY	For OpenAI models	--	OpenAI API key. Read by pydantic-ai's OpenAI backend.
OLLAMA_BASE_URL	No	http://localhost:11434/v1	Ollama API endpoint.
MEMORY_EXTRACTION_MAX_TOKENS	No	8192	Max tokens for LLM extraction. Reasoning models consume thinking tokens before output; 8192 covers most cases.
MEMORY_CONFIG	No	--	Path to custom TOML config file.
MEMORY_EXTRACTION_TEMPLATE_PATH	No	--	Path to override extraction prompt (markdown with header schema).
HF_HUB_OFFLINE	No	--	Set to 1 to skip HuggingFace HTTP checks on startup. Use after the embedding model has been cached locally.
SERVER_HOST	No	localhost	Server bind host (streamable-http transport).
SERVER_PORT	No	8000	Server bind port (streamable-http transport).
MEMORY_RECALL_TOKENS_ENABLED	No	true	Enable recall token disambiguation.
MEMORY_RECALL_TOKENS_TOP_K	No	5	Max related traces for token assessment.
MEMORY_RECALL_TOKENS_THRESHOLD	No	0.42	Min cosine similarity for related trace lookup at write time.
MEMORY_RECALL_TOKENS_STRENGTH_THRESHOLD	No	0.1	Min token strength to activate.
MEMORY_RECALL_TOKENS_REINFORCE_BOOST	No	0.1	Strength increment on activation.
MEMORY_RECALL_TOKENS_DECAY_FACTOR	No	0.9	Inactive token decay per consolidation.
MEMORY_RECALL_TOKENS_HOP_DECAY	No	0.85	Signal attenuation per token hop during propagation.
MEMORY_RECALL_TOKENS_PROPAGATION_BLEND	No	0.5	Weight of propagated signal in the additive blend.
MEMORY_RECALL_TOKENS_MAX_ROUNDS	No	3	Max re-seeding iterations at query time.
MEMORY_RECALL_TOKENS_STABILITY_THRESHOLD	No	0.95	Top-K overlap fraction to stop re-seeding early.
MEMORY_RECALL_TOKENS_TOP_SEEDS	No	3	Token-discovered traces used as seeds per re-seeding round.
MEMORY_RECALL_TOKENS_SYSTEM_PROMPT	No	--	Override situational-assessment system prompt (inline string).
MEMORY_RECALL_TOKENS_USER_PROMPT	No	--	Override situational-assessment user prompt (inline string).

Provider

PYDANTIC_AI_MODEL prefix	Required credential
anthropic:...	ANTHROPIC_API_KEY
openai:...	OPENAI_API_KEY
openrouter:...	OPENROUTER_API_KEY (e.g. openrouter:google/gemini-3-flash-preview)
ollama:...	OLLAMA_BASE_URL (defaults to http://localhost:11434/v1)

Reasoning models (Qwen3, DeepSeek-R1) consume thinking tokens from the extraction budget. If remember returns extraction errors, increase MEMORY_EXTRACTION_MAX_TOKENS or set MEMORY_CONFIG to a custom TOML file with [extraction] max_tokens = 8192.

Requirements

• Python 3.12+
• PostgreSQL 17 with pgvector

License

MIT