Model Context Guide
bylkannan
0Provides a hands-on Python guide for understanding the Model Context Protocol, which standardizes how AI models and agents interact with their operational context.
About
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
- Extensible architecture for custom context types and actions
- Interactive agent script for demonstrating protocol interactions
- Reference implementation of the Model Context Protocol (MCP)
- FastAPI-based REST API provider for context and actions
- Includes example tests for verification and learning
- 0 GitHub stars
Use Cases
- Building and extending AI tools with robust contextual awareness
- Developing AI agents that require standardized context interaction
- Learning and demonstrating the Model Context Protocol
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