MCP Memory Service MCP Server

MCP Memory Service - TypeScript

A modern TypeScript implementation of a cloud-based vector memory service for AI assistants via the Model Context Protocol (MCP). This service provides persistent storage with semantic search capabilities for Claude.ai and other AI assistants.

Current Version: 1.7.2 | Status: Production-ready | Test Coverage: 95.2%

Features

• 🧠 3-Tier Memory System: SYSTEM, LEARNED, and MEMORY layers for hierarchical knowledge organization
• 👥 Multi-Tenant Support: Secure user isolation with Clerk OAuth authentication
• 🔍 Vector Search: Semantic similarity search using OpenAI embeddings
• 🔄 Automatic Embeddings: Auto-generates and updates embeddings on data changes
• 🏢 Entity Management: Track people, organizations, projects, and relationships
• 📚 Interaction History: Store and retrieve conversation history with context
• 📱 Contacts Sync: True bidirectional sync with macOS Contacts using LLM-based deduplication
• 🔄 Google Sync: Google Contacts and Calendar integration with incremental sync (v1.7.0+)
• 📅 Calendar Tracking: Week-based Google Calendar event sync with attendee linking
• 🌐 Web Interface: Modern Next.js web UI for visual memory management (staging on port 3002)
• 🔌 MCP Protocol: JSON-RPC 2.0 over stdio (local) and HTTP (remote)
• 🌐 REST API: HTTP interface for web applications
• 🔐 OAuth Integration: Clerk authentication for remote access with 95.2% test coverage
• ☁️ Cloud-Ready: Built for modern cloud deployment with Turso database
• 🔐 Security Patches: Critical user isolation vulnerabilities fixed in v1.7.1
• 📝 Smart Logging: LOG_LEVEL-aware logging with state tracking (v1.7.1+)

Architecture

src/
├── types/          # TypeScript type definitions
├── models/         # Data models and schemas
├── database/       # Database connection and operations
├── core/           # Core memory logic and vector search
├── mcp/           # MCP server implementation
├── api/           # REST API server
├── cli/           # CLI tool
├── utils/         # Utility functions
└── index.ts       # Main entry point

web/
├── app/           # Next.js app directory
├── components/    # React components
├── lib/           # Utilities and integrations
└── public/        # Static assets

Quick Start

Prerequisites

• Node.js 18+
• Turso database (or LibSQL compatible)
• OpenAI API key (for embeddings)

Installation

# Clone and install dependencies
npm install

# Copy environment configuration
cp .env.local .env

# Build the project
npm run build

# Start development server
npm run dev

Environment Variables

Required variables in .env:

# Database Configuration
TURSO_URL=libsql://your-database.turso.io
TURSO_AUTH_TOKEN=your-auth-token

# OpenAI Configuration (for vector embeddings)
OPENAI_API_KEY=your-openai-api-key

# Optional Configuration
LOG_LEVEL=info              # Options: debug, info (default), warn, error (v1.7.1+)
MCP_DEBUG=0                 # Set to 1 for detailed MCP protocol debugging
DEFAULT_USER_EMAIL=user@example.com

# Automatic Embedding Updates (v1.1.0+)
ENABLE_EMBEDDING_MONITOR=true  # Enable background monitoring
EMBEDDING_MONITOR_INTERVAL=60000  # Check every 60 seconds

# Web Interface (v1.3.0+)
NEXT_PUBLIC_CLERK_PUBLISHABLE_KEY=your-clerk-publishable-key
CLERK_SECRET_KEY=your-clerk-secret-key

# Google Integration (v1.7.0+)
GOOGLE_CLIENT_ID=your-google-client-id
GOOGLE_CLIENT_SECRET=your-google-client-secret
GOOGLE_REDIRECT_URI=http://localhost:3002/api/auth/google/callback  # Use port 3002 for staging

Usage

MCP Server (for Claude Desktop)

Recommended: Using CLI Tool

# Install globally
npm install -g mcp-memory-ts

# Initialize configuration
mcp-memory init

# Install to Claude Desktop
mcp-memory install

# Check status
mcp-memory status

This creates a config in ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "mcp-memory-ts": {
      "command": "mcp-memory",
      "args": ["server"],
      "env": {
        "TURSO_URL": "your-database-url",
        "TURSO_AUTH_TOKEN": "your-auth-token",
        "OPENAI_API_KEY": "your-openai-key",
        "DEFAULT_USER_EMAIL": "user@example.com"
      }
    }
  }
}

Manual Setup

For development or manual configuration:

# Start MCP server
npm run mcp-server

# Or with debug logging
MCP_DEBUG=1 npm run mcp-server

# Or using CLI command
mcp-memory server --debug

Remote MCP Server (HTTP with OAuth)

For web applications and remote access with Clerk authentication:

# Start remote MCP server
npm run mcp-server-remote

The remote MCP server will be available at http://localhost:3003 with:

• Authentication: Clerk OAuth session tokens
• Multi-Tenant: Complete user isolation by email
• Protocol: JSON-RPC 2.0 over HTTP
• Security: Rate limiting, CORS, session management
• **