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memU MCP Server

by MonsterOne1
GitHub
Python
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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.

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

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

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

This server cannot be installed

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security - not tested
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license - not found
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quality - not tested

How are these scores calculated?

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

Enables AI applications to use advanced memory management capabilities through the memU AI framework. Supports storing conversation memories, semantic retrieval, multi-user management, and memory statistics via standardized MCP protocol.

  1. Overview
    1. Features
      1. Quick Start
        1. Prerequisites
        2. Local Development
        3. Render Deployment
        4. Usage Examples
      2. Configuration
        1. Available Tools
          1. Documentation
            1. Deployment Options
              1. Local Development
              2. Docker
              3. Render (Cloud)
              4. Claude Desktop Integration
            2. Health Monitoring
              1. Contributing
                1. Support
                  1. License

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