This repository provides example server and client implementations for the Model Context Protocol (MCP), designed to illustrate its usage in building distributed AI applications. It targets developers and researchers looking to integrate LLM-powered features into their systems via a standardized communication protocol.

How It Works

The project showcases MCP's capabilities through two primary examples: a basic weather server and a more complex LLM-powered chatbot client. MCP facilitates communication between different services, enabling features like context sharing and remote procedure calls, which are crucial for building sophisticated AI workflows.

Quick Start & Requirements

• Install: pip install -r requirements.txt
• Prerequisites: Python 3.7+, grpcio, grpcio-tools, protobuf.
• Demo: https://github.com/modelcontextprotocol/quickstart-resources/blob/main/weather/weather_server.py

Highlighted Details

• Demonstrates MCP for a simple weather service.
• Illustrates building an LLM-powered chatbot client using MCP.
• Provides foundational code for understanding MCP's client-server architecture.

Maintenance & Community

No specific contributors, sponsorships, or community links are mentioned in the README.

Licensing & Compatibility

The repository does not specify a license.

Limitations & Caveats

This repository contains only example code for tutorials and is not intended for production use. It may not cover all aspects of the Model Context Protocol or provide robust error handling.