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

Clone the repository:
```
git clone ...
cd mcp-lightning-lesson
```
Create a venv using uv:
```
uv venv
```

Copy the example environment file and add your OpenAI API key:

cp .env.example .env
# Edit .env and set your OPENAI_API_KEY

Usage

Run the main script:

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!

mcp-lightning-lesson