MCP UseCase Function Server

# Deployment Guide ## Local Deployment ### 1. Direct Python Execution ```bash # Start the server python3 mcp_server.py # The server will run with stdio transport # Suitable for Claude Desktop integration ``` ### 2. Docker Deployment ```bash # Build the image docker build -t mcp-usecase-server . # Run the container docker run -it mcp-usecase-server ``` ## Cloud Deployment ### AWS Lambda 1. Package your code with dependencies 2. Modify transport to handle Lambda events 3. Deploy using AWS CLI or Console ### Google Cloud Functions 1. Create a `main.py` with HTTP handler 2. Deploy using `gcloud functions deploy` ### Azure Functions 1. Create Function App 2. Deploy using Azure CLI or VS Code extension ## Production Considerations 1. **Logging**: Configure proper logging levels 2. **Error Handling**: Implement robust error handling 3. **Security**: Validate inputs and sanitize outputs 4. **Monitoring**: Add health checks and metrics 5. **Scaling**: Consider load balancing for multiple instances ## Environment Variables Set these in your deployment environment: - `LOG_LEVEL`: Control logging verbosity - `FUNCTION_TIMEOUT`: Set function execution timeout - `MAX_MEMORY_USAGE`: Limit memory usage