Example
Demonstrates Model Context Protocol (MCP) implementation with a Go-based host orchestrating services from both Go and Python servers.
About
This project showcases a Model Context Protocol (MCP) implementation featuring a Go-based host application that intelligently orchestrates specialized tools provided by both Go and Python MCP servers. It illustrates an advanced tool orchestration system where a Large Language Model (LLM), specifically DeepSeek API, analyzes natural language user queries. The LLM determines the appropriate tool and its parameters, allowing the host to automatically route the request to the correct Go or Python server for execution, and then present the results back to the user.
Key Features
- Multi-language MCP ecosystem demonstrating interoperability between Go and Python servers
- Containerized deployment with a full Docker Compose setup for easy testing and deployment
- LLM-powered tool orchestration using AI to intelligently select and call appropriate tools
- Robust container health monitoring and startup coordination for system stability
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- Automatic server routing by the host application to find the right tool across different servers
Use Cases
- Creating new users in a system via natural language commands (e.g., 'Create a new user with Id [timestamp], name 'John Doe'')
- Performing mathematical operations like addition and multiplication through natural language prompts (e.g., 'Add two numbers 5 and 10')
- Retrieving specific user information by natural language query (e.g., 'Read user with Id 2')
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