
memU MCP Server
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.
README
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
- 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 memoriesretrieve_memory
: Retrieve relevant memoriessearch_memory
: Search memories by querymanage_memory
: Update or delete memoriesget_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 checkGET /status
- Detailed statusGET /metrics
- Performance metricsGET /info
- Service information
Contributing
- Fork the repository
- Create a feature branch
- Make your changes
- Add tests if applicable
- Submit a pull request
Support
- GitHub Issues: Report bugs and feature requests
- Documentation: Check the
docs/
directory - Email: support@example.com
License
MIT License
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