Local Mem0 MCP Server

Local Mem0 MCP Server

A fully self-hosted Model Context Protocol (MCP) server that integrates Mem0 for persistent memory capabilities. Enables AI assistants like Claude to store and retrieve contextual information across conversations.

✨ Features

• 🧠 Persistent Memory: Store and retrieve memories across conversations
• 🔒 Fully Self-Hosted: No external APIs or cloud dependencies
• 🐳 Containerized: Complete Docker deployment with one command
• 🚀 Easy Installation: Single script setup for Windows, Mac, and Linux
• 🤖 Local AI Models: Uses Ollama with phi3:mini and nomic-embed-text
• 📊 Vector Storage: PostgreSQL with pgvector for efficient memory search
• 🔌 MCP Compatible: Works with Claude Desktop and other MCP-capable AI tools

🚀 Quick Start

Prerequisites

• Docker Desktop installed and running
• Claude Desktop (for testing)

Installation

Windows:

git clone https://github.com/Synapse-OS/local-mem0-mcp.git
cd local-mem0-mcp
install.bat

Mac/Linux:

git clone https://github.com/Synapse-OS/local-mem0-mcp.git
cd local-mem0-mcp
chmod +x install.sh
./install.sh

The installation will:

1. Build the MCP server container
2. Start PostgreSQL and Ollama services
3. Download AI models (~2.5GB total)
4. Configure Claude Desktop integration
5. Test the installation

Testing

After installation and configuration:

1. Restart Claude Desktop completely (close and reopen)
2. Verify MCP server: Type /mcp - should list mem0-local as available
3. Test memory storage: "Remember that I'm testing the MCP memory system today"
4. Test memory retrieval: "What do you remember about me?"
5. Verify persistence: Restart Claude Desktop and ask again - memories should persist

Troubleshooting MCP Connection:

• If /mcp shows no servers, check the configuration file path and JSON syntax
• Ensure Docker containers are running: docker ps
• Check MCP server logs: docker logs mem0-mcp-server

🏗️ Architecture

┌─────────────────┐    ┌──────────────────┐    ┌─────────────────┐
│   Claude        │    │   MCP Server     │    │   PostgreSQL    │
│   Desktop       │◄──►│   (FastMCP)      │◄──►│   + pgvector    │
└─────────────────┘    └──────────────────┘    └─────────────────┘
                                │
                                ▼
                       ┌──────────────────┐
                       │     Ollama       │
                       │   phi3:mini +    │
                       │ nomic-embed-text │
                       └──────────────────┘

🔧 Configuration

Claude Desktop MCP Configuration

After installation, configure Claude Desktop to use the MCP server:

Windows: Edit %APPDATA%\Claude\claude_desktop_config.json:

Mac: Edit ~/Library/Application Support/Claude/claude_desktop_config.json:

Linux: Edit ~/.config/Claude/claude_desktop_config.json:

Add this configuration:

{
  "mcpServers": {
    "mem0-local": {
      "command": "docker",
      "args": [
        "exec", "-i", "mem0-mcp-server",
        "python", "/app/src/server.py"
      ]
    }
  }
}

System Configuration

The system is configured for local operation by default:

• MCP Server: Runs in Docker container with STDIO transport
• Database: PostgreSQL with pgvector on port 5432
• AI Models: Local Ollama instance on port 11434
• Memory Storage: User-isolated memories with vector embeddings

📋 Available Memory Operations

• add_memory: Store new memories
• search_memories: Find relevant memories by query
• get_all_memories: Retrieve all memories for a user
• update_memory: Modify existing memories
• delete_memory: Remove specific memories
• delete_all_memories: Clear all memories for a user
• get_memory_stats: Get memory statistics

🔍 Troubleshooting

Check services:

docker ps

View logs:

docker-compose -f docker-compose.local.yml logs

Restart services:

docker-compose -f docker-compose.local.yml restart

Clean restart:

docker-compose -f docker-compose.local.yml down -v
# Run install script again

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• Mem0 - Memory management framework
• FastMCP - MCP server implementation
• Ollama - Local AI model inference
• pgvector - Vector similarity search