mcp-lightning-lesson

# Build Your First Agentic AI App with MCP ## Maven Lightning Lesson A Python project demonstrating the use of OpenAI GPT models and MCP (Model Context Protocol) agents to fetch and process real-world data. ## Overview This project provides an example of using a custom agent to retrieve weather forecasts for Hintertux, Austria, by fetching data from the meteoblue.com website. It leverages the `openai-agents` library and its capabilities to run and expose MCP Servers. ## Features - Custom agent implementation using OpenAI GPT models - Integration with MCP server for data fetching - Example function tool (`get_time`) for current time retrieval - Returns structured JSON output ## Requirements - Python 3.13+ - OpenAI API key ## Installation 1. Clone the repository: ```sh git clone ... cd mcp-lightning-lesson ``` 2. Create a venv using [uv](astral.sh/uv): ```sh uv venv ``` 4. Copy the example environment file and add your OpenAI API key: ```sh cp .env.example .env # Edit .env and set your OPENAI_API_KEY ``` ## Usage Run the main script: ```sh uv run python main.py ``` The agent will: - Fetch the weather forecast for Hintertux, Austria - Get the current time - Return the results as a JSON payload ## Project Structure - `main.py` – Main application logic - `pyproject.toml` – Project dependencies and metadata - `.env.example` – Example environment variable file ## Dependencies - openai-agents >= 0.0.15 - python-dotenv >= 1.1.0 ## Frontend Coming soon!