mem0-mcp

A simplified MCP (Model Context Protocol) server for persistent memory management using mem0.ai. This server enables AI assistants to remember information across conversations.

Features

• Persistent Memory: Store and retrieve information across conversations
• Semantic Search: Find relevant memories using natural language
• Simple API: Just 3 core tools for memory management

Quick Start

Prerequisites

• Python 3.8+
• mem0.ai API key (get one at mem0.ai)

Installation

1. Clone the repository:

git clone https://github.com/yourusername/mem0-mcp.git
cd mem0-mcp

2. Install dependencies:

pip install -r requirements.txt

3. Set up environment variables:

cp .env.example .env
# Edit .env and add your MEM0_API_KEY

Running the Server

python main.py

Custom Configuration

python main.py --host 0.0.0.0 --port 8080 --debug

Configuration

Environment Variables

Variable	Description	Default
MEM0_API_KEY	Your mem0.ai API key	Required
PORT	Server port	8080
DEFAULT_USER_ID	Default user ID for memories	cursor_mcp

Command Line Options

python main.py [OPTIONS]

Options:
  --host HOST           Host to bind to (default: 0.0.0.0)
  --port PORT           Port to bind to (default: 8080)
  --name NAME           Server name (default: mem0-mcp)
  --debug               Enable debug mode
  --no-instructions     Disable custom instructions

Available Tools

1. add_memory - Add new information to memory
2. search_memories - Search memories using natural language
3. get_all_memories - Retrieve all stored memories

Integration

Claude Desktop / Cursor

Add to your MCP settings:

{
  "mcpServers": {
    "mem0-mcp": {
      "command": "python",
      "args": ["/path/to/mem0-mcp/main.py"]
    }
  }
}

Project Structure

mem0-mcp/
├── src/
│   ├── core/
│   │   ├── __init__.py
│   │   ├── config.py
│   │   └── mem0_client.py
│   ├── tools/
│   │   ├── __init__.py
│   │   └── memory_tools.py
│   └── server/
│       ├── __init__.py
│       ├── main.py
│       └── server_factory.py
├── main.py
├── .env.example
├── requirements.txt
├── pyproject.toml
└── README.md

Deployment

Render

To deploy on Render, you need to update the Start Command in your service settings:

1. Go to your Render dashboard
2. Select your mem0-mcp service
3. Go to Settings → Build & Deploy
4. Change "Start Command" to: python main.py
5. Save changes and manually deploy

Alternatively, you can use the render.yaml configuration provided in this repository.

License

MIT License - see LICENSE file for details

Acknowledgments

• mem0.ai for the memory API
• Anthropic MCP for the protocol specification