doobidoo/mcp-memory-service

MCP Memory Service

Universal MCP memory service with intelligent memory triggers, OAuth 2.1 team collaboration, and semantic memory search for AI assistants. Features Natural Memory Triggers v7.1.0 with 85%+ trigger accuracy, Claude Code HTTP transport, zero-configuration authentication, and enterprise security. Works with Claude Desktop, VS Code, Cursor, Continue, and 13+ AI applications with SQLite-vec for fast local search and Cloudflare for global distribution.

🚀 Quick Start (2 minutes)

🧠 v7.1.0: Natural Memory Triggers for Claude Code

🤖 Intelligent Memory Awareness (Zero Configuration):

# 1. Install MCP Memory Service
git clone https://github.com/doobidoo/mcp-memory-service.git
cd mcp-memory-service && python install.py

# 2. Install Natural Memory Triggers
cd claude-hooks && python install_hooks.py --natural-triggers

# 3. Test intelligent triggers
node memory-mode-controller.js status
# ✅ Done! Claude Code now automatically detects when you need memory context

📖 Complete Guide: Natural Memory Triggers v7.1.0

🆕 v7.0.0: OAuth 2.1 & Claude Code HTTP Transport

🔗 Claude Code Team Collaboration (Zero Configuration):

# 1. Start OAuth-enabled server
export MCP_OAUTH_ENABLED=true
uv run memory server --http

# 2. Add HTTP transport to Claude Code
claude mcp add --transport http memory-service http://localhost:8000/mcp

# ✅ Done! Claude Code automatically handles OAuth registration and team collaboration

📖 Complete Setup Guide: OAuth 2.1 Setup Guide

Traditional Setup Options

Universal Installer (Most Compatible):

# Clone and install with automatic platform detection
git clone https://github.com/doobidoo/mcp-memory-service.git
cd mcp-memory-service

# Lightweight installation (SQLite-vec with ONNX embeddings - recommended)
python install.py

# Add full ML capabilities (torch + sentence-transformers for advanced features)
python install.py --with-ml

# Add ChromaDB backend support (includes full ML stack - for multi-client setups)
python install.py --with-chromadb

📝 Installation Options Explained:

• Default (recommended): Lightweight SQLite-vec with ONNX embeddings - fast, works offline, <100MB dependencies
• --with-ml: Adds PyTorch + sentence-transformers for advanced ML features - heavier but more capable
• --with-chromadb: Multi-client local server support - use only if you need shared team access

Docker (Fastest):

# For MCP protocol (Claude Desktop)
docker-compose up -d

# For HTTP API + OAuth (Team Collaboration)
docker-compose -f docker-compose.http.yml up -d

Smithery (Claude Desktop):

# Auto-install for Claude Desktop
npx -y @smithery/cli install @doobidoo/mcp-memory-service --client claude

⚠️ v6.17.0+ Script Migration Notice

Updating from an older version? Scripts have been reorganized for better maintainability:

• Recommended: Use python -m mcp_memory_service.server in your Claude Desktop config (no path dependencies!)
• Alternative 1: Use uv run memory server with UV tooling
• Alternative 2: Update path from scripts/run_memory_server.py to scripts/server/run_memory_server.py
• Backward compatible: Old path still works with a migration notice

⚠️ First-Time Setup Expectations

On your first run, you'll see some warnings that are completely normal:

• "WARNING: Failed to load from cache: No snapshots directory" - The service is checking for cached models (first-time setup)
• "WARNING: Using TRANSFORMERS_CACHE is deprecated" - Informational warning, doesn't affect functionality
• Model download in progress - The service automatically downloads a ~25MB embedding model (takes 1-2 minutes)

These warnings disappear after the first successful run. The service is working correctly! For details, see our .

🐍 Python 3.13 Compatibility Note

sqlite-vec may not have pre-built wheels for Python 3.13 yet. If installation fails:

• The installer will automatically try multiple installation methods
• Consider using Python 3.12 for the smoothest experience: brew install python@3.12
• Alternative: Use ChromaDB backend with --storage-backend chromadb --with-chromadb
• See for details

🍎 macOS SQLite Extension Support

macOS users may encounter enable_load_extension errors with sqlite-vec:

• System Python on macOS lacks SQLite extension support by default
• Solution: Use Homebrew Python: brew install python && rehash
• Alternative: Use pyenv: PYTHON_CONFIGURE_OPTS='--enable-loadable-sqlite-extensions' pyenv install 3.12.0
• Fallback: Use sqlite_vec backend (default) or install ChromaDB with --with-chromadb
• See for details

📚 Complete Documentation

👉 Visit our comprehensive Wiki for detailed guides:

🧠 v7.1.0 Natural Memory Triggers (Latest)

• Natural Memory Triggers v7.1.0 Guide - Intelligent automatic memory awareness
  • ✅ 85%+ trigger accuracy with semantic pattern detection
  • ✅ Multi-tier performance (50ms instant → 150ms fast → 500ms intensive)
  • ✅ CLI management system for real-time configuration
  • ✅ Git-aware context integration for enhanced relevance
  • ✅ Zero-restart installation with dynamic hook loading

🆕 v7.0.0 OAuth & Team Collaboration

• 🔐 OAuth 2.1 Setup Guide - NEW! Complete OAuth 2.1 Dynamic Client Registration guide
• 🔗 Integration Guide - Claude Desktop, Claude Code HTTP transport, VS Code, and more
• 🛡️ Advanced Configuration - Updated! OAuth security, enterprise features

🚀 Setup & Installation

• 📋 Installation Guide - Complete installation for all platforms and use cases
• 🖥️ Platform Setup Guide - Windows, macOS, and Linux optimizations
• ⚡ Performance Optimization - Speed up queries, optimize resources, scaling

🧠 Advanced Topics

• 👨‍💻 Development Reference - Claude Code hooks, API reference, debugging
• 🔧 Troubleshooting Guide - Updated! OAuth troubleshooting + common issues
• ❓ FAQ - Frequently asked questions
• 📝 Examples - Practical code examples and workflows

📂 Internal Documentation

• - Search enhancement specifications and design documents
• - AI agent instructions, release checklist, refactoring notes
• - Docker, dual-service, and production deployment
• - Storage backends, migration, mDNS discovery

✨ Key Features

🔐 Enterprise Authentication & Team Collaboration 🆕

• OAuth 2.1 Dynamic Client Registration - RFC 7591 & RFC 8414 compliant
• Claude Code HTTP Transport - Zero-configuration team collaboration
• JWT Authentication - Enterprise-grade security with scope validation
• Auto-Discovery Endpoints - Seamless client registration and authorization
• Multi-Auth Support - OAuth + API keys + optional anonymous access

🧠 Intelligent Memory Management

• Semantic search with vector embeddings
• Natural language time queries ("yesterday", "last week")
• Tag-based organization with smart categorization
• Memory consolidation with dream-inspired algorithms

🔗 Universal Compatibility

• Claude Desktop - Native MCP integration
• Claude Code - HTTP transport + Memory-aware development with hooks
• VS Code, Cursor, Continue - IDE extensions
• 13+ AI applications - REST API compatibility

💾 Flexible Storage

• SQLite-vec - Fast local storage (recommended, lightweight ONNX embeddings)
• ChromaDB - Multi-client collaboration (optional, heavy dependencies)
• Cloudflare - Global edge distribution
• Automatic backups and synchronization

Note: All heavy ML dependencies (PyTorch, sentence-transformers, ChromaDB) are now optional to dramatically reduce build times and image sizes. SQLite-vec uses lightweight ONNX embeddings by default. Install with --with-ml for full ML capabilities or --with-chromadb for multi-client features.

🚀 Production Ready

• Cross-platform - Windows, macOS, Linux
• Service installation - Auto-start background operation
• HTTPS/SSL - Secure connections with OAuth 2.1
• Docker support - Easy deployment with team collaboration

💡 Basic Usage

🔗 Team Collaboration with OAuth (v7.0.0+)

# Start OAuth-enabled server for team collaboration
export MCP_OAUTH_ENABLED=true
uv run memory server --http

# Claude Code team members connect via HTTP transport
claude mcp add --transport http memory-service http://your-server:8000/mcp
# → Automatic OAuth discovery, registration, and authentication

🧠 Memory Operations

# Store a memory
uv run memory store "Fixed race condition in authentication by adding mutex locks"

# Search for relevant memories
uv run memory recall "authentication race condition"

# Search by tags
uv run memory search --tags python debugging

# Check system health (shows OAuth status)
uv run memory health

🔧 Configuration

Claude Desktop Integration

Recommended approach - Add to your Claude Desktop config (~/.claude/config.json):

{
  "mcpServers": {
    "memory": {
      "command": "python",
      "args": ["-m", "mcp_memory_service.server"],
      "env": {
        "MCP_MEMORY_STORAGE_BACKEND": "sqlite_vec"
      }
    }
  }
}

Alternative approaches:

// Option 1: UV tooling (if using UV)
{
  "mcpServers": {
    "memory": {
      "command": "uv",
      "args": ["--directory", "/path/to/mcp-memory-service", "run", "memory", "server"],
      "env": {
        "MCP_MEMORY_STORAGE_BACKEND": "sqlite_vec"
      }
    }
  }
}

// Option 2: Direct script path (v6.17.0+)
{
  "mcpServers": {
    "memory": {
      "command": "python",
      "args": ["/path/to/mcp-memory-service/scripts/server/run_memory_server.py"],
      "env": {
        "MCP_MEMORY_STORAGE_BACKEND": "sqlite_vec"
      }
    }
  }
}

Environment Variables

# Storage backend (sqlite_vec recommended)
export MCP_MEMORY_STORAGE_BACKEND=sqlite_vec

# Enable HTTP API
export MCP_HTTP_ENABLED=true
export MCP_HTTP_PORT=8000

# Security  
export MCP_API_KEY="your-secure-key"

🏗️ Architecture

┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   AI Clients    │    │  MCP Memory     │    │ Storage Backend │
│                 │    │  Service v7.0   │    │                 │
│ • Claude Desktop│◄──►│ • MCP Protocol  │◄──►│ • SQLite-vec    │
│ • Claude Code   │    │ • HTTP Transport│    │ • ChromaDB      │
│   (HTTP/OAuth)  │    │ • OAuth 2.1 Auth│    │ • Cloudflare    │
│ • VS Code       │    │ • Memory Store  │    │ • Hybrid        │
│ • Cursor        │    │ • Semantic      │    │                 │
│ • 13+ AI Apps   │    │   Search        │    │                 │
└─────────────────┘    └─────────────────┘    └─────────────────┘

🛠️ Development

Project Structure

mcp-memory-service/
├── src/mcp_memory_service/    # Core application
│   ├── models/                # Data models
│   ├── storage/               # Storage backends
│   ├── web/                   # HTTP API & dashboard
│   └── server.py              # MCP server
├── scripts/                   # Utilities & installation
├── tests/                     # Test suite
└── tools/docker/              # Docker configuration

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes with tests
4. Submit a pull request

See for detailed guidelines.

🆘 Support

• 📖 Documentation: Wiki - Comprehensive guides
• 🐛 Bug Reports: GitHub Issues
• 💬 Discussions: GitHub Discussions
• 🔧 Troubleshooting: Troubleshooting Guide
• ✅ Configuration Validator: Run python scripts/validation/validate_configuration_complete.py to check your setup
• 🔄 Backend Sync Tools: See for Cloudflare↔SQLite sync

📊 In Production

Real-world metrics from active deployments:

• 750+ memories stored and actively used across teams
• <500ms response time for semantic search (local & HTTP transport)
• 65% token reduction in Claude Code sessions with OAuth collaboration
• 96.7% faster context setup (15min → 30sec)
• 100% knowledge retention across sessions and team members
• Zero-configuration OAuth setup success rate: 98.5%

🏆 Recognition

• Verified MCP Server
• Featured AI Tool
• Production-tested across 13+ AI applications
• Community-driven with real-world feedback and improvements

📄 License

Apache License 2.0 - see for details.

Ready to supercharge your AI workflow? 🚀

👉 Start with our Installation Guide or explore the Wiki for comprehensive documentation.

Transform your AI conversations into persistent, searchable knowledge that grows with you.