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:

Mac/Linux:

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

🔧 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:

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:

View logs:

Restart services:

Clean restart:

🤝 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