This project serves as a comprehensive, hands-on learning guide and demo for the Model Context Protocol (MCP), an open standard for defining how AI models, tools, and agents manage and interact with their contextual environment, including files, code, and other resources. It provides a practical implementation in Python, featuring MCP data models, a FastAPI-based provider exposing context and actions via a REST API, and an agent script designed to interact with this provider to perform various operations, offering a clear blueprint for extending AI agent capabilities.
Key Features
01Extensible architecture for custom context types and actions
02Interactive agent script for demonstrating protocol interactions
03Reference implementation of the Model Context Protocol (MCP)
04FastAPI-based REST API provider for context and actions
05Includes example tests for verification and learning
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