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Open Brain

Agent-readable second brain. One PostgreSQL database, one MCP server, every AI you use.

Open Brain stores your thoughts as vector embeddings so any AI tool (Claude Code, Cursor, Windsurf, ChatGPT Desktop, VS Code Copilot) can search your memory by meaning, not just keywords. Local-first. You own the data. ~$0/month to run.

The Problem

Every AI coding tool has amnesia. Close the chat, lose the context. Switch from Cursor to Claude Code? Start from scratch. That decision you made last Tuesday? Gone.

Open Brain fixes this. One shared memory layer that every agent reads and writes to, automatically, silently, without you lifting a finger.

How It Works

Your thought
    |
    v
[remember / capture_context]
    |
    +---> Ollama / OpenAI  -->  vector embedding (768-1536 dims)
    +---> heuristic / LLM  -->  metadata (type, people, topics, action_items)
    +---> project scoping   -->  optional project tag for filtering
              |
              v
    PostgreSQL + pgvector
    (+ annotations, ratings, access tracking)
              |
              v
    MCP Server (stdio / HTTP)  <--  server.py  (12 tools)
              |
    +---------+-----------+
    v         v           v
 Claude    Cursor    Windsurf   ...any MCP client

Key Features

  • Cross-agent memory: Capture in Claude Code, recall in Cursor. One brain, every tool.
  • Semantic search: Find memories by meaning, not keywords. "That database decision" finds it even if you never typed those words.
  • Hybrid search: Combines vector similarity with full-text ranking for exact names, project codes, and dates.
  • Uptime-based decay: Stale memories fade naturally -- but only during active server time. Vacations, power outages, and overnight gaps cost you nothing.
  • Time-scoped search: Ask "what did I decide last week?" with since_days=7. Filter by creation date.
  • Auto-capture: Agents store decisions, bugs, and context as you work. You never have to say "remember this."
  • Auto-recall: Agents search the brain before starting tasks. Prior context surfaces automatically.
  • One-command wiring: python server.py wire auto-discovers and configures every AI tool on your system.
  • Smart batching: Embeddings and metadata extraction are batched to avoid GPU model thrashing.
  • Quality signals: Rate memories up/down. Access tracking surfaces the most useful memories.
  • Smart merge: When storing, the LLM decides whether to ADD, MERGE, REPLACE, or SKIP related memories in the similarity gray zone. Contradictions are detected and resolved automatically.
  • Background consolidation: Optional background thread periodically merges and deduplicates related memories using the LLM (OPEN_BRAIN_CONSOLIDATION_INTERVAL).
  • Working memory: Ephemeral scratchpad for in-session context. Three tools (scratch_set, scratch_get, scratch_list). Cleared on restart, never pollutes long-term memory.
  • Bi-temporal modelling: Two time axes per memory -- valid_time (when it happened) and transaction_time (when we learned it). Query with as_of to see what was known at any point in time.
  • Pinned guardrails: Pin workflow rules to a project so agents always see them.
  • Project scoping: Tag memories by project. Search within a project without noise from others.
  • 100% local: PostgreSQL + pgvector + Ollama. No cloud. No API keys required. Your data stays yours.

Supported Clients

Client Transport Status
Claude Code (CLI / VS Code) stdio Fully supported
Windsurf stdio Fully supported
Cursor stdio Fully supported
VS Code Copilot stdio Fully supported
Claude Desktop stdio Fully supported
ChatGPT Desktop SSE proxy Supported via mcp.server.sse
Continue stdio Fully supported
Any MCP client stdio / HTTP Fully supported