Mem0 MCP Server

A Model Context Protocol (MCP) server for integrating AI assistants with Mem0.ai's persistent memory system.

Overview

This server provides MCP-compatible tools that let any compatible AI assistant access and manage persistent memories stored in Mem0. It acts as a bridge between AI models and the Mem0 memory system, enabling assistants to:

• Store and retrieve memories
• Search memories with semantic similarity
• Manage different memory types (episodic, semantic, procedural)
• Utilize short-term memory for conversation context
• Apply selective memory patterns
• Create knowledge graphs from memories

Project Structure

The project has been refactored from a monolithic design to a modular structure:

mem0_mcp_server/
├── core/                   # Core functionality
│   ├── client.py           # Mem0 client initialization 
│   ├── logging.py          # Logging configuration
│   └── server.py           # MCP server setup
├── operations/             # Basic memory operations
│   └── basic.py            # Add, search, get, delete, update
├── memory_types/           # Specialized memory implementations
│   ├── short_term.py       # Conversation, working, attention
│   └── specialized.py      # Episodic, semantic, procedural
└── advanced/               # Advanced features
    ├── features.py         # Categories, instructions, graph, feedback
    └── selective.py        # Pattern-based memory filtering

app.py                      # Main entry point

Getting Started

Setting up in Cursor or Claude Desktop

1. Install the package:

pip install mcp-mem0-server

2. Add the following configuration to your MCP configuration file:

For Cursor, add this to ~/.cursor/mcp.json:

"mem0-memory-general": {
  "command": "mcp-mem0-server",
  "args": [],
  "env": {
    "MEM0_API_KEY": "your-mem0-api-key-here"
  }
}

For Claude Desktop, add a similar configuration in your settings.

3. Restart Cursor or Claude Desktop to apply the changes.

Memory Types

The server supports different memory types organized by duration and function:

Short-Term Memories

• Conversation Memory: Recall of recent message exchanges
• Working Memory: Temporary information being actively used
• Attention Memory: Information currently in focus

Long-Term Memories

• Episodic Memory: Specific events and experiences
• Semantic Memory: Facts, concepts, and knowledge
• Procedural Memory: Skills and how-to information

Advanced Features

• Custom Categories: Define and manage your own memory categories
• Memory Instructions: Set guidelines for how memories should be processed
• Graph Relations: Access knowledge graph relationships between entities
• Selective Memory: Filter text with include/exclude patterns before storing
• Feedback Mechanism: Provide feedback on memory quality

Usage

All memories in the system use "default_user" as the default user_id.

For detailed usage examples, see the USAGE_GUIDE.md.

Documentation

• Getting Started
• API Reference
• Memory Types
• Advanced Features
• Configuration

License

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

Acknowledgments

• Mem0.ai for their excellent memory API
• FastMCP for the MCP server implementation
• All contributors to this project