A Model Context Protocol (MCP) server that provides access to memU AI memory framework capabilities.
This MCP server wraps the memU AI memory framework, enabling AI applications to use advanced memory management features through the standardized MCP protocol.
- 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
- Python 3.8+
- memU API key (get one at https://app.memu.so/api-key/)
# 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# 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# 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- Local Development: See
config/example.jsonfor configuration options - Render Deployment: See Render Deployment Guide
- Environment Variables: See Environment Variables Guide
memorize_conversation: Store conversation memoriesretrieve_memory: Retrieve relevant memoriessearch_memory: Search memories by querymanage_memory: Update or delete memoriesget_memory_stats: Get memory statistics
- API Reference - Detailed API documentation
- Setup Guide - Installation and configuration
- Render Deployment - Deploy to Render platform
- Environment Variables - Configuration reference
python -m memu_mcp_server.maindocker-compose up memu-mcp-serverUse the included render.yaml Blueprint for one-click deployment to Render.
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"
}
}
}
}When deployed with the Web Service component, monitoring endpoints are available:
GET /health- Health checkGET /status- Detailed statusGET /metrics- Performance metricsGET /info- Service information
- Fork the repository
- Create a feature branch
- Make your changes
- Add tests if applicable
- Submit a pull request
- GitHub Issues: Report bugs and feature requests
- Documentation: Check the
docs/directory - Email: support@example.com
MIT License