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

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