Memory MCP Server

Memory MCP Server

A long-term memory storage system for LLMs that helps them remember context across multiple sessions using semantic search with embeddings to provide relevant historical information from past interactions and development decisions.

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Memory MCP Server

A long-term memory storage system for LLMs using the Model Context Protocol (MCP) standard. This system helps LLMs remember the context of work done over the entire history of a project, even across multiple sessions. It uses semantic search with embeddings to provide relevant context from past interactions and development decisions.

Features

  • Project-based memory organization
  • Semantic search using Ollama embeddings (nomic-embed-text model, 768 dimensions)
  • Multiple memory types:
    • Conversations: Dialog context and important discussions
    • Code: Implementation details and changes
    • Decisions: Key architectural and design choices
    • References: Links to external resources and documentation
  • Rich metadata storage including:
    • Implementation status
    • Key decisions
    • Files created/modified
    • Code changes
    • Dependencies added
  • Tagging system for memory organization
  • Relationship tracking between memories

Prerequisites

  • Node.js (v18 or later)
  • Ollama running locally (for embeddings)
    • Must have the nomic-embed-text model installed
  • SQLite3

Installation

  1. Clone the repository
  2. Install dependencies:
    npm install
    
  3. Build the project:
    npm run build
    
  4. Create a .env file with required configuration:
    OLLAMA_HOST=http://localhost:11434
    DB_PATH=memory.db
    

Usage

  1. Start the server in development mode:

    npm run dev
    

    This will:

    • Compile TypeScript
    • Copy schema files
    • Start the server with auto-reload
  2. The server connects via stdio for Cursor compatibility

Database Schema

The system uses SQLite with the following tables:

Core Tables

  • projects: Project information and metadata
  • memories: Memory entries storing various types of development context
  • embeddings: Vector embeddings (768d) for semantic search capabilities

Organization Tables

  • tags: Memory organization tags
  • memory_tags: Many-to-many relationships between memories and tags
  • memory_relationships: Directed relationships between memory entries

MCP Tools

The following tools are available through the MCP protocol:

Memory Management

  • store-dev-memory: Create new development memories with:
    • Content
    • Type (conversation/code/decision/reference)
    • Tags
    • Code changes
    • Files created/modified
    • Key decisions
    • Implementation status
  • list-dev-memories: List existing memories with optional tag filtering
  • get-dev-memory: Retrieve specific memory by ID
  • search: Semantic search across memories using embeddings

Development

For development:

npm run dev

This will:

  1. Kill any existing server instances
  2. Rebuild the TypeScript code
  3. Copy the schema.sql to the dist directory
  4. Start the server in development mode

Dependencies

Key dependencies:

  • @modelcontextprotocol/sdk@^1.7.0: MCP protocol implementation
  • better-sqlite3@^9.4.3: SQLite database interface
  • node-fetch@^3.3.2: HTTP client for Ollama API
  • zod@^3.22.4: Runtime type checking and validation

Project Structure

memory-mcp-server/
├── src/
│   ├── db/
│   │   ├── init.ts     # Database initialization
│   │   └── service.ts  # Database service layer
│   ├── dev-memory.ts   # Development memory helpers
│   ├── index.ts        # Main server implementation
│   └── schema.sql      # Database schema
├── dist/               # Compiled JavaScript
├── package.json        # Project configuration
└── tsconfig.json       # TypeScript configuration

Contributing

Contributions are welcome! Please ensure you:

  1. Write clear commit messages
  2. Add appropriate documentation
  3. Follow the existing code style
  4. Add/update tests as needed

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