Labsco
MCP SERVER

Self-hosted memory that stores thoughts as a weighted entity graph, with a background cycle that deduplicates, synthesises and archives.

Agent Memory
Summary
It publishes a benchmark number, which most memory servers do not.

37.2% on LongMemEval is a figure you can argue with, and that is the point — the alternative is a memory system that makes no measurable claim at all. The design behind it is the graph: connections above 0.80 similarity get typed by an LLM, so "contradicts" and "supersedes" are stored relations rather than something re-derived at query time, and co-occurrence edges strengthen links that keep being retrieved together. Running it means running Postgres with pgvector and paying OpenRouter for embeddings.

What it is

A memory server you host yourself. Thoughts arrive from Telegram, RSS and paper pipelines, or straight from an AI client, and land in an entity graph rather than a flat document store — embedded, deduplicated, auto-linked and entity-resolved on the way in.

What you get
  • `capture_thought` saves a new thought with automatic embedding; `search_thoughts` does semantic search with optional one-hop graph expansion
  • `list_thoughts` browses by type, topic, person, theme, quality and time; `thought_stats` returns counts and breakdowns
  • `get_connections` traverses typed links — extends, contradicts, is-evidence-for, supersedes — classified by an LLM above 0.80 similarity
  • `list_entities` browses the people, tools, projects and organizations extracted from your notes
  • `weekly_review` summarises themes, open loops and next steps; `analyze` reports hubs, density, sources, co-occurrence and themes
  • Maintenance is exposed rather than hidden: `dedup_review` with a similarity histogram, `refresh_salience`, `review_stale`, `serendipity_digest` for forgotten high-quality notes, and `pipeline` for ingest health
  • `update_thought` re-embeds and re-extracts metadata; `delete_thought` cascades connections; `migration_guide` covers importing from other platforms
Requirements

Either Supabase or Docker Compose, plus PostgreSQL with pgvector and an OpenRouter API key for embeddings and metadata extraction. Clients connect over streamable HTTP to the deployment's `/open-brain-mcp/mcp` path with your key in an `x-brain-key` header — for Claude Code, `claude mcp add --transport http --header "x-brain-key: ..."`. A Telegram bot is optional and is the intended capture path on the go.

Setup effort

One command plus a key — claude mcp add --transport http --header "x-brain-key: YOUR_MCP_KEY" open-brain https://YOUR_REF.supabase.co/functions/v1/open-brain-mcp/mcp, then supply credentials