MCP Fastapi Learning

🚀 FastAPI Hello World Application

A simple Hello World API built with FastAPI and MCP SSE support.

🚀 Quick Start

This application can be run either locally or using Docker. Follow the installation steps below to get started.

✨ Features

• Root Route: Returns a simple "Hello World" message.
• Dynamic Greeting Endpoint: Provides personalized greetings based on the provided name.
• OpenAI Integration: Utilizes OpenAI's GPT - 4o model for advanced AI chat completion.
• Automated API Documentation: Comes with Swagger UI for easy API exploration.

📦 Installation

You can choose to run this application locally or using Docker.

Local Installation

1. Clone the Repository

git clone https://github.com/xxradar/mcp-test-repo.git
cd mcp-test-repo

2. Create a Virtual Environment (Optional but Recommended)

# On macOS/Linux
python -m venv venv
source venv/bin/activate

# On Windows
python -m venv venv
venv\Scripts\activate

3. Install Dependencies

pip install -r requirements.txt

4. Run the Application

uvicorn main:app --reload

After the application starts, it will be available at http://127.0.0.1:8000.

Alternatively, you can run it directly using Python:

python main.py

Docker Installation

1. Clone the Repository

git clone https://github.com/xxradar/mcp-test-repo.git
cd mcp-test-repo

2. Build the Docker Image

docker build -t fastapi-hello-world .

3. Run the Docker Container

docker run -p 8000:8000 fastapi-hello-world

The application will be available at http://localhost:8000.

📚 Documentation

API Endpoints

• GET /: Returns a simple "Hello World" message.
• GET /hello/{name}: Returns a personalized greeting based on the provided name.
• GET /openai: Uses OpenAI's GPT - 4o model for responses (accepts an optional prompt query parameter).
• GET /docs: Swagger UI documentation interface.
• GET /redoc: ReDoc documentation interface.

OpenAI Integration

The /openai endpoint uses OpenAI's GPT - 4o model and requires the OpenAI API key to be set in the environment.

Local Installation

# Set the OpenAI API key as an environment variable
export OPENAI_API_KEY=your_api_key_here

# Run the application
uvicorn main:app --reload

Docker Installation

# Run the Docker container with the OpenAI API key
docker run -p 8000:8000 -e OPENAI_API_KEY=your_api_key_here fastapi-hello-world

💻 Usage Examples

Using curl

# Get the Hello World message
curl http://127.0.0.1:8000/

# Get a personalized greeting message
curl http://127.0.0.1:8000/hello/World

# Access the Swagger UI documentation interface
curl http://127.0.0.1:8000/docs

# Make an example request using the OpenAI endpoint
curl -X POST "http://127.0.0.1:8000/openai/?prompt=你好%2C+我是新手。你能教我什么？"

Using Swagger UI

1. Open your browser and visit http://127.0.0.1:8000/docs.
2. In the documentation interface, find the /openai endpoint.
3. Click the "Try It Out" button for this endpoint.
4. Enter your question or prompt in the prompt parameter, e.g., "你好，我是新手。你能教我什么？".
5. Click the "Execute" button to view the OpenAI response.

⚠️ Important Note

• Ensure that your Python version is 3.7 or higher during installation.
• Adjust the port mapping or other configurations as needed when using Docker.
• Before using in a production environment, make sure the OpenAI API key is correctly set, and be aware of its costs and usage limits.