memU MCP Server

A Model Context Protocol (MCP) server that provides access to memU AI memory framework capabilities.

Overview

This MCP server wraps the memU AI memory framework, enabling AI applications to use advanced memory management features through the standardized MCP protocol.

Related MCP server: Mem0 MCP Server

Features

• Memory Storage: Store and organize conversation memories

• Smart Retrieval: Retrieve relevant memories using semantic search

• Memory Management: Update, delete, and organize memory data

• Statistics: Get insights into memory usage and performance

• Multi-user Support: Handle multiple users and AI agents

Quick Start

Prerequisites

• Python 3.8+

• memU API key (get one at https://app.memu.so/api-key/)

Local Development

# Clone the repository
git clone <repository-url>
cd memu-mcp-server

# Install dependencies
pip install -r requirements.txt

# Set up environment variables
export MEMU_API_KEY="your-memu-api-key"

# Run the server
python -m memu_mcp_server.main

Render Deployment

# Deploy to Render (using Blueprint)
1. Connect your GitHub repository to Render
2. Render will automatically detect render.yaml
3. Set MEMU_API_KEY as a secret in Render dashboard
4. Deploy!

# Or use the Render CLI
render deploy

Usage Examples

# Local development
python -m memu_mcp_server.main --log-level DEBUG

# Render mode (for testing locally)
python -m memu_mcp_server.main --render-mode

# With custom configuration
python -m memu_mcp_server.main --config config/server.json

# API server (for health checks)
python -m memu_mcp_server.api --host 0.0.0.0 --port 8080

Configuration

• Local Development: See config/example.json for configuration options

• Render Deployment: See Render Deployment Guide

• Environment Variables: See Environment Variables Guide

Available Tools

• memorize_conversation: Store conversation memories

• retrieve_memory: Retrieve relevant memories

• search_memory: Search memories by query

• manage_memory: Update or delete memories

• get_memory_stats: Get memory statistics

Documentation

• API Reference - Detailed API documentation

• Setup Guide - Installation and configuration

• Render Deployment - Deploy to Render platform

• Environment Variables - Configuration reference

Deployment Options

Local Development

python -m memu_mcp_server.main

Docker

docker-compose up memu-mcp-server

Render (Cloud)

Use the included render.yaml Blueprint for one-click deployment to Render.

Claude Desktop Integration

Add to your Claude Desktop configuration:

{
  "mcpServers": {
    "memu-memory": {
      "command": "python",
      "args": ["-m", "memu_mcp_server.main"],
      "env": {
        "MEMU_API_KEY": "your_api_key_here"
      }
    }
  }
}

Health Monitoring

When deployed with the Web Service component, monitoring endpoints are available:

• GET /health - Health check

• GET /status - Detailed status

• GET /metrics - Performance metrics

• GET /info - Service information

Contributing

1. Fork the repository

2. Create a feature branch

3. Make your changes

4. Add tests if applicable

5. Submit a pull request

Support

• GitHub Issues: Report bugs and feature requests

• Documentation: Check the docs/ directory

• Email: support@example.com

License

MIT License