README.md•20.8 kB
# MCP Memory Service
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[](https://github.com/doobidoo/mcp-memory-service#-in-production)
[](https://claude.ai)
[](https://cursor.sh)
[](https://modelcontextprotocol.io/)
[](https://github.com/doobidoo/mcp-memory-service/wiki)
**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.
<img width="240" alt="MCP Memory Service" src="https://github.com/user-attachments/assets/eab1f341-ca54-445c-905e-273cd9e89555" />
## 🚀 Quick Start (2 minutes)
### 🆕 **v8.7.0: Cosine Similarity & Maintenance Tools**
**🎯 Fixed Search Accuracy + 1800x Faster Database Maintenance**:
```bash
# Automatic migration on startup - nothing to do!
# Search similarity scores now 70-79% (was 0%)
# New maintenance scripts for power users:
cd mcp-memory-service
# Regenerate all embeddings (~5min for 2600 memories)
python scripts/maintenance/regenerate_embeddings.py
# Fast duplicate cleanup (1800x faster than API!)
bash scripts/maintenance/fast_cleanup_duplicates.sh # <5s for 100+ duplicates
# Find duplicates with timestamp normalization
python scripts/maintenance/find_all_duplicates.py # <2s for 2000 memories
```
**✨ What's New in v8.7.0:**
- 🎯 **Fixed 0% similarity scores** - Migrated to cosine distance metric (70-79% accuracy now)
- 🔧 **Maintenance scripts** - 1800x performance improvement (5s vs 2.5 hours for 100 duplicates)
- 📈 **Search accuracy boost** - Exact match 79.2% (was 61%)
- 🔄 **Automatic migration** - Seamless upgrade on first startup
- 📚 **Comprehensive docs** - Performance benchmarks, best practices, troubleshooting
**📖 Complete Guide**: [Maintenance Scripts README](scripts/maintenance/README.md)
---
### 🆕 **v8.6.0: Document Ingestion System**
**📄 Transform Documents into Searchable Memory** (Production Ready):
```bash
# 1. Install/Update MCP Memory Service
git clone https://github.com/doobidoo/mcp-memory-service.git
cd mcp-memory-service && python install.py
# 2. Start the server with web interface
uv run memory server --http
# 3. Access interactive dashboard
open http://127.0.0.1:8888/
# ✅ Upload PDFs, TXT, MD, JSON - Browse chunks - Search content!
```
**✨ What's New in v8.6.0:**
- 📚 **Complete document management UI** with drag-and-drop upload
- 🔍 **Interactive document viewer** with chunk-by-chunk browsing
- 🏷️ **Smart tagging** with length validation (prevents bloat)
- 🔒 **Security hardened** (path traversal & XSS protection)
- 📄 **Multiple formats**: PDF, TXT, MD, JSON with optional [semtools](https://github.com/run-llama/semtools) for enhanced parsing
**📖 Complete Guide**: [Document Ingestion Guide](https://github.com/doobidoo/mcp-memory-service/wiki)
---
### 🆕 **v8.4.0: Memory Hooks Recency Optimization**
**📊 Intelligent Recent Memory Prioritization** (80% Better Context):
```bash
# Automatically prioritizes recent development work over old memories
# Memory hooks now surface memories <7 days old with 80% higher accuracy
# 1. Install Natural Memory Triggers (includes recency optimization)
cd claude-hooks && python install_hooks.py --natural-triggers
# 2. Verify recency scoring
node test-recency-scoring.js
# ✅ Done! Recent memories automatically prioritized in Claude Code
```
**📖 Complete Guide**: [Memory Hooks Configuration](https://github.com/doobidoo/mcp-memory-service/tree/main/claude-hooks/CONFIGURATION.md)
---
### 🧠 **Natural Memory Triggers v7.1.0+**
**🤖 Intelligent Memory Awareness** (Zero Configuration):
- ✅ **85%+ trigger accuracy** with semantic pattern detection
- ✅ **Recent memory prioritization** (v8.4.0+) - 80% better context
- ✅ **Multi-tier performance** (50ms instant → 150ms fast → 500ms intensive)
- ✅ **CLI management system** for real-time configuration
**📖 Complete Guide**: [Natural Memory Triggers](https://github.com/doobidoo/mcp-memory-service/wiki/Natural-Memory-Triggers-v7.1.0)
---
### 🆕 **v7.0.0: OAuth 2.1 & Claude Code HTTP Transport**
**🔗 Claude Code Team Collaboration** (Zero Configuration):
```bash
# 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](https://github.com/doobidoo/mcp-memory-service/wiki/OAuth-2.1-Setup-Guide)
---
### Traditional Setup Options
**Universal Installer (Most Compatible):**
```bash
# 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
# Install with hybrid backend (SQLite-vec + Cloudflare sync)
python install.py --storage-backend hybrid
```
**📝 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
- **`--storage-backend hybrid`**: Hybrid backend with SQLite-vec + Cloudflare sync - best for multi-device access
**Docker (Fastest):**
```bash
# 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):**
```bash
# 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 [First-Time Setup Guide](docs/first-time-setup.md).
### 🐍 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 Cloudflare backend with `--storage-backend cloudflare`
- See [Troubleshooting Guide](docs/troubleshooting/general.md#python-313-sqlite-vec-issues) 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 Cloudflare or Hybrid backend: `--storage-backend cloudflare` or `--storage-backend hybrid`
- See [Troubleshooting Guide](docs/troubleshooting/general.md#macos-sqlite-extension-issues) for details
## 📚 Complete Documentation
**👉 Visit our comprehensive [Wiki](https://github.com/doobidoo/mcp-memory-service/wiki) for detailed guides:**
### 🧠 v7.1.0 Natural Memory Triggers (Latest)
- **[Natural Memory Triggers v7.1.0 Guide](https://github.com/doobidoo/mcp-memory-service/wiki/Natural-Memory-Triggers-v7.1.0)** - 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](https://github.com/doobidoo/mcp-memory-service/wiki/OAuth-2.1-Setup-Guide)** - **NEW!** Complete OAuth 2.1 Dynamic Client Registration guide
- **[🔗 Integration Guide](https://github.com/doobidoo/mcp-memory-service/wiki/03-Integration-Guide)** - Claude Desktop, **Claude Code HTTP transport**, VS Code, and more
- **[🛡️ Advanced Configuration](https://github.com/doobidoo/mcp-memory-service/wiki/04-Advanced-Configuration)** - **Updated!** OAuth security, enterprise features
### 🚀 Setup & Installation
- **[📋 Installation Guide](https://github.com/doobidoo/mcp-memory-service/wiki/01-Installation-Guide)** - Complete installation for all platforms and use cases
- **[🖥️ Platform Setup Guide](https://github.com/doobidoo/mcp-memory-service/wiki/02-Platform-Setup-Guide)** - Windows, macOS, and Linux optimizations
- **[⚡ Performance Optimization](https://github.com/doobidoo/mcp-memory-service/wiki/05-Performance-Optimization)** - Speed up queries, optimize resources, scaling
### 🧠 Advanced Topics
- **[👨💻 Development Reference](https://github.com/doobidoo/mcp-memory-service/wiki/06-Development-Reference)** - Claude Code hooks, API reference, debugging
- **[🔧 Troubleshooting Guide](https://github.com/doobidoo/mcp-memory-service/wiki/07-TROUBLESHOOTING)** - **Updated!** OAuth troubleshooting + common issues
- **[❓ FAQ](https://github.com/doobidoo/mcp-memory-service/wiki/08-FAQ)** - Frequently asked questions
- **[📝 Examples](https://github.com/doobidoo/mcp-memory-service/wiki/09-Examples)** - Practical code examples and workflows
### 📂 Internal Documentation
- **[🏗️ Architecture Specs](docs/architecture/)** - Search enhancement specifications and design documents
- **[👩💻 Development Docs](docs/development/)** - AI agent instructions, release checklist, refactoring notes
- **[🚀 Deployment Guides](docs/deployment/)** - Docker, dual-service, and production deployment
- **[📚 Additional Guides](docs/guides/)** - Storage backends, migration, mDNS discovery
## ✨ Key Features
### 📄 **Document Ingestion System** 🆕 v8.6.0
- **Interactive Web UI** - Drag-and-drop document upload with real-time progress
- **Multiple Formats** - PDF, TXT, MD, JSON with intelligent chunking
- **Document Viewer** - Browse chunks, view metadata, search content
- **Smart Tagging** - Automatic tagging with length validation (max 100 chars)
- **Optional semtools** - Enhanced PDF/DOCX/PPTX parsing with LlamaParse
- **Security Hardened** - Path traversal protection, XSS prevention, input validation
- **7 New Endpoints** - Complete REST API for document management
### 🔐 **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
- **Document-aware search** - Query across uploaded documents and manual memories
### 🔗 **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, 5ms reads)
- **Cloudflare** - Global edge distribution with D1 + Vectorize
- **Hybrid** - Best of both worlds: SQLite-vec speed + Cloudflare sync (recommended for teams)
- **Automatic backups** and synchronization
> **Note**: All heavy ML dependencies (PyTorch, sentence-transformers) 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.
### 🚀 **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
- **Interactive Dashboard** - Web UI at http://127.0.0.1:8888/ for complete management
## 💡 Basic Usage
### 📄 **Document Ingestion** (v8.6.0+)
```bash
# Start server with web interface
uv run memory server --http
# Access interactive dashboard
open http://127.0.0.1:8888/
# Upload documents via CLI
curl -X POST http://127.0.0.1:8888/api/documents/upload \
-F "file=@document.pdf" \
-F "tags=documentation,reference"
# Search document content
curl -X POST http://127.0.0.1:8888/api/search \
-H "Content-Type: application/json" \
-d '{"query": "authentication flow", "limit": 10}'
```
### 🔗 **Team Collaboration with OAuth** (v7.0.0+)
```bash
# 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**
```bash
# 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`):
```json
{
"mcpServers": {
"memory": {
"command": "python",
"args": ["-m", "mcp_memory_service.server"],
"env": {
"MCP_MEMORY_STORAGE_BACKEND": "sqlite_vec"
}
}
}
}
```
**Alternative approaches:**
```json
// 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
```bash
# 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 v8.6 │ │ │
│ • Claude Desktop│◄──►│ • MCP Protocol │◄──►│ • SQLite-vec │
│ • Claude Code │ │ • HTTP Transport│ │ • Cloudflare │
│ (HTTP/OAuth) │ │ • OAuth 2.1 Auth│ │ • Hybrid │
│ • VS Code │ │ • Memory Store │ │ (SQLite+CF) │
│ • Cursor │ │ • Semantic │ │ │
│ • 13+ AI Apps │ │ Search │ │ │
│ • Web Dashboard │ │ • Doc Ingestion │ │ │
│ (Port 8888) │ │ (PDF/TXT/MD) │ │ │
└─────────────────┘ └─────────────────┘ └─────────────────┘
```
## 🛠️ 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 [CONTRIBUTING.md](CONTRIBUTING.md) for detailed guidelines.
## 🆘 Support
- **📖 Documentation**: [Wiki](https://github.com/doobidoo/mcp-memory-service/wiki) - Comprehensive guides
- **🐛 Bug Reports**: [GitHub Issues](https://github.com/doobidoo/mcp-memory-service/issues)
- **💬 Discussions**: [GitHub Discussions](https://github.com/doobidoo/mcp-memory-service/discussions)
- **🔧 Troubleshooting**: [Troubleshooting Guide](https://github.com/doobidoo/mcp-memory-service/wiki/07-TROUBLESHOOTING)
- **✅ Configuration Validator**: Run `python scripts/validation/validate_configuration_complete.py` to check your setup
- **🔄 Backend Sync Tools**: See [scripts/README.md](scripts/README.md#backend-synchronization) 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
- [](https://smithery.ai/server/@doobidoo/mcp-memory-service) **Verified MCP Server**
- [](https://glama.ai/mcp/servers/bzvl3lz34o) **Featured AI Tool**
- **Production-tested** across 13+ AI applications
- **Community-driven** with real-world feedback and improvements
## 📄 License
Apache License 2.0 - see [LICENSE](LICENSE) for details.
---
**Ready to supercharge your AI workflow?** 🚀
👉 **[Start with our Installation Guide](https://github.com/doobidoo/mcp-memory-service/wiki/01-Installation-Guide)** or explore the **[Wiki](https://github.com/doobidoo/mcp-memory-service/wiki)** for comprehensive documentation.
*Transform your AI conversations into persistent, searchable knowledge that grows with you.*