OwlPharaoh20/MCP-Agentic-AI-Demo
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The Model Context Protocol (MCP) server is designed to facilitate the integration of AI agents with external APIs, enabling them to maintain conversation context and interact dynamically with users.
Use This command to install your mcp server and add to claude config (and display in your tools list)
- uv run mcp install server/weather.py
Use this command to run the MCP CLient script
- uv run server/client.py
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MCP Agentic AI Demo
This project demonstrates the implementation of a Model Context Protocol (MCP) server with weather alert functionality and an interactive chat interface. It showcases how to build AI agents that can interact with external APIs and maintain conversation context, making it an excellent example for learning agentic AI development.
The project consists of two main components: a weather alert server and an interactive chat client. The server component (server/weather.py) integrates with the National Weather Service API to fetch and format weather alerts for US states. The chat client (server/client.py) provides an interactive interface powered by Groq's language model, allowing users to query weather information and maintain conversation context through built-in memory capabilities.
To get started, ensure you have Python 3.8+ installed and set up your environment with the required dependencies. You'll need to create a .env file with your Groq API key and install the project dependencies using uv. The project uses modern Python features like async/await for efficient API calls and includes proper error handling and session management. Run the server using uv run mcp dev server/weather.py and the chat client using python server/client.py to experience the full functionality of this agentic AI demo.