brain-mcp

brain-mcp

An MCP server that provides persistent semantic memory backed by PostgreSQL and pgvector for storing and searching thoughts via vector embeddings. It enables dimensional organization, conflict detection, and historical tracking of facts, decisions, and observations.

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README

brain-mcp

An MCP (Model Context Protocol) server that provides persistent semantic memory backed by PostgreSQL + pgvector. Store "thoughts" with vector embeddings and organize them via a flexible dimensional model.

Two Servers

This repo provides two MCP servers with a shared codebase:

  • brain-mcp (dist/index.js) — General-purpose knowledge store with ADR support. Use this for non-code contexts.
  • brain-code-mcp (dist/code.js) — Superset of brain-mcp with code-aware tools. Use this for software projects.

You only need to configure one — brain-code-mcp includes all brain-mcp tools.

Features

  • Semantic search — find thoughts by meaning using cosine similarity over vector embeddings
  • Dimensional organization — tag thoughts with typed dimensions (person, project, topic, tag, file, symbol, etc.)
  • Thought temporality — thoughts have types (fact, decision, observation, question) and can be superseded while preserving history
  • Multi-brain support — isolated knowledge spaces via the BRAIN_NAME environment variable
  • Conflict detection — automatically surfaces similar existing thoughts when capturing new ones
  • Architecture Decision Records — structured ADR capture with auto-numbering, alternatives, and consequences
  • Code-linked knowledge — link thoughts to repositories, files, and symbols (brain-code-mcp)
  • Knowledge freshness — detect stale knowledge when referenced code changes (brain-code-mcp)

Tools

Core tools (both servers)

Tool Description
capture_thought Store a thought with type, dimensions, metadata, and embedding. Surfaces conflicts with similar active thoughts.
search Semantic vector search with optional filters (dimension, thought type, etc.)
list_recent Chronological listing with optional filters
explore_dimension All thoughts linked to a given dimension
list_dimensions All dimensions with thought counts
list_brains List all brains with optional thought counts. Respects BRAIN_ACCESSIBLE.
supersede_thought Replace an existing thought, preserving history. Auto-preserves ADR metadata.
capture_adr Record an Architecture Decision Record with context, alternatives, and consequences
list_adrs List and filter ADRs by status or dimension

Code tools (brain-code-mcp only)

Tool Description
capture_code_context Capture knowledge linked to specific files, symbols, or repositories
search_code Semantic search filtered to code-linked knowledge
check_freshness Check if code-linked knowledge is stale by comparing git state
refresh_stale_knowledge Find stale thoughts with git diffs for review

Core prompts (both servers)

Prompt Description
brain_overview Comprehensive orientation: thought counts, dimensions, recent thoughts, ADR summary, open questions
deep_dive Deep dive into a dimension with all linked thoughts, co-occurring dimensions, and ADRs
decision_review Review active decisions and ADRs, flagging overdue revisit dates
capture_session Set up a knowledge capture session with existing taxonomy and related knowledge

Code prompts (brain-code-mcp only)

Prompt Description
codebase_knowledge All knowledge about a repo grouped by file/symbol, with optional freshness checks
file_context All knowledge about a specific file with freshness and semantically related unlinked knowledge

Setup

Prerequisites

  • Node.js
  • PostgreSQL with pgvector extension
  • An OpenRouter API key (for generating embeddings)

Quick start (Claude Code)

Set OPENROUTER_API_KEY in your shell environment (e.g. in ~/.bashrc or ~/.zshrc):

export OPENROUTER_API_KEY="your-key-here"

Then add to your project's .mcp.json:

{
  "mcpServers": {
    "brain": {
      "command": "npx",
      "args": ["-y", "github:markschaake/brain-mcp"],
      "env": {
        "DATABASE_URL": "postgresql://user:pass@host:5432/brain",
        "BRAIN_NAME": "personal"
      }
    }
  }
}

For brain-code-mcp (includes code-aware tools):

{
  "mcpServers": {
    "brain": {
      "command": "npx",
      "args": ["-y", "-p", "github:markschaake/brain-mcp", "brain-code-mcp"],
      "env": {
        "DATABASE_URL": "postgresql://user:pass@host:5432/brain",
        "BRAIN_NAME": "my-project"
      }
    }
  }
}

Note: Do not put OPENROUTER_API_KEY in .mcp.json — it is often checked into version control. The server reads it from the environment automatically.

The database schema is automatically created on first run.

Database options

Option 1: Use the included docker-compose (easiest for local development)

git clone https://github.com/markschaake/brain-mcp.git
cd brain-mcp
docker compose up -d   # starts PostgreSQL+pgvector on port 5488

With docker-compose, the default DATABASE_URL (postgresql://brain:brain@localhost:5488/brain) works without any configuration.

Option 2: Bring your own PostgreSQL

Any PostgreSQL instance with the pgvector extension installed will work. Set DATABASE_URL in your MCP config. The schema is auto-applied on first server startup.

Local development

pnpm install
pnpm run build
pnpm run dev    # watch mode (tsc --watch)
pnpm run lint   # run ESLint

# Run directly
OPENROUTER_API_KEY=your-key node dist/index.js      # brain-mcp
OPENROUTER_API_KEY=your-key node dist/code.js        # brain-code-mcp

Environment variables

Variable Description Default
DATABASE_URL PostgreSQL connection string postgresql://brain:brain@localhost:5488/brain
OPENROUTER_API_KEY Required for embedding generation
EMBEDDING_MODEL Override the embedding model openai/text-embedding-3-small
BRAIN_NAME Which brain (knowledge space) to use personal
BRAIN_ACCESSIBLE Comma-separated whitelist of brain names this instance can access. Empty = all brains accessible. (empty)

Multi-brain usage

All tools and prompts accept an optional brain parameter to target a specific brain by name at runtime, without restarting the server. Omit it to use the default brain (BRAIN_NAME).

Read-only tools (search, list_recent, explore_dimension, list_dimensions, list_adrs, search_code, check_freshness, refresh_stale_knowledge) also accept brain: "*" to query across all accessible brains.

Write tools (capture_thought, supersede_thought, capture_adr, capture_code_context) reject "*" — you must specify a brain name for writes.

Use BRAIN_ACCESSIBLE to restrict which brains a server instance can access:

{
  "mcpServers": {
    "brain": {
      "command": "npx",
      "args": ["-y", "github:markschaake/brain-mcp"],
      "env": {
        "DATABASE_URL": "postgresql://user:pass@host:5432/brain",
        "BRAIN_NAME": "personal",
        "BRAIN_ACCESSIBLE": "personal,work,shared"
      }
    }
  }
}

When BRAIN_ACCESSIBLE is empty (default), all brains are accessible.

Architecture

Source files

File Purpose
src/index.ts brain-mcp entry point
src/code.ts brain-code-mcp entry point (superset)
src/tools.ts Shared tool registration (core + ADR tools)
src/db.ts PostgreSQL connection pool and helpers
src/migrate.ts Auto-migration runner (applies migrations/*.sql on startup)
src/embeddings.ts Embedding generation via OpenRouter
src/git.ts Git operations for freshness detection
src/prompts.ts MCP prompt registration (core prompts for both servers)

Database schema

Migrations are in migrations/ and are auto-applied on server startup.

  • brains — isolated knowledge spaces
  • thoughts — content + vector(1536) embedding + metadata (jsonb) + thought type + status
  • dimensions — typed categories with metadata, unique per (brain, name, type)
  • thought_dimensions — many-to-many links with optional context

Embeddings are indexed with HNSW for fast cosine similarity search.

Code-linked dimension types

brain-code-mcp uses these dimension types to link knowledge to code:

Type Name convention Metadata
repo Repository name {} (extensible)
file Repo-relative path {repo, line_start, line_end, git_sha}
symbol Symbol name {repo, file, kind}

ADR metadata

ADRs are stored as decision thoughts with structured metadata:

{
  "adr": true,
  "adr_number": 7,
  "adr_title": "Use pgvector for semantic search",
  "adr_status": "accepted",  // proposed | accepted | deprecated | superseded
  "adr_context": "Why this decision was needed...",
  "adr_alternatives": [{ "name": "Pinecone", "pros": [...], "cons": [...] }],
  "adr_consequences": ["Must run PostgreSQL with pgvector"],
  "adr_decided_date": "2026-03-01"
}

License

ISC

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