mcp-memories

An MCP server that captures code build sessions and publishes them to a shared team knowledge base, making past work discoverable via semantic search.

What it does:

• Auto-captures every agent session via IDE hooks (Cursor, Claude Code)

• When you call complete_session, it summarizes with Grove AI and embeds with Voyage voyage-code-4

• Team members search with natural language — vector search + Voyage reranking returns the most relevant past builds

Setup

1. Install and build

npm install
npm run build

2. Configure environment

cp .env.example .env
# Fill in MONGODB_URI, MDB_GROVE_API_KEY, GROVE_BASE_URL, VOYAGE_API_KEY, MEMORIES_AUTHOR

3. Register the MCP server

Add to your IDE's MCP config (e.g. ~/.cursor/mcp.json or Claude Desktop config.json):

{
  "mcpServers": {
    "mcp-memories": {
      "command": "node",
      "args": ["/path/to/mcp-memories/dist/index.js"],
      "env": {
        "MONGODB_URI": "mongodb+srv://...",
        "MEMORIES_DB": "mcp_memories",
        "MDB_GROVE_API_KEY": "...",
        "GROVE_BASE_URL": "...",
        "GROVE_MODEL": "claude-3-7-sonnet",
        "VOYAGE_API_KEY": "...",
        "MEMORIES_AUTHOR": "your.name"
      }
    }
  }
}

4. Set up auto-capture hooks

Cursor — hooks.json is already in .cursor/hooks.json. It fires the capture script on every stop event automatically.

Claude Code — merge the snippet in hooks/claude/settings-snippet.json into your ~/.claude/settings.json, updating the path to point to this repo.

Related MCP server: Concept Tracker

Tools

Typical workflow

# During a session — automatic (hook fires) or manual:
capture_activity(session_id="abc123", conversation_context="Built JWT auth middleware...")

# When done:
complete_session(session_id="abc123", final_notes="Ended up using RS256 instead of HS256 because...")

# Later, someone else starting similar work:
search_memories(query="JWT authentication middleware Node.js")

MongoDB Atlas setup

The server creates its own indexes on startup, including the Atlas Vector Search index (memories_vector_index, 1024 dimensions, cosine similarity, voyage-code-4). You need an Atlas cluster with Vector Search enabled.