mcpField
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FastAPI Hello World Application

FastAPI Hello World Application

Local
github.com/xxradarDeveloper Tools0Updated 81w ago

About FastAPI Hello World Application

FastAPI Hello World Application is a small FastAPI project with greeting endpoints and an OpenAI GPT-4o endpoint. It is suited to developers testing a basic API, API documentation, or MCP SSE support.

Key features

  1. 01Hello World root endpoint
  2. 02Personalized greeting endpoint
  3. 03OpenAI GPT-4o chat endpoint
  4. 04Swagger UI and ReDoc documentation
  5. 05Docker setup option

Use cases

  1. 01Testing a basic FastAPI API
  2. 02Trying a GPT-4o endpoint
  3. 03Viewing generated API documentation

MCP support

The application includes MCP SSE support and can be inspected with MCP Inspector. The README does not describe specific MCP tools or resources.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

FastAPI Hello World Application

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

Features

  • Root endpoint that returns a Hello World message
  • Dynamic greeting endpoint that takes a name parameter
  • OpenAI integration with GPT-4o for advanced AI-powered chat completions
  • Automatic API documentation with Swagger UI

Prerequisites

  • Python 3.7+ (for local setup)
  • pip (Python package installer)
  • OpenAI API key (for the /openai endpoint)
  • Docker (optional, for containerized setup)

Setup Instructions

You can run this application either locally or using Docker.

Local Setup
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

The application will start and be available at http://127.0.0.1:8000

Alternatively, you can run the application directly with Python:

python main.py
Docker Setup
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

API Endpoints

  • GET /: Returns a simple Hello World message
  • GET /hello/{name}: Returns a personalized greeting with the provided name
  • GET /openai: Returns a response from OpenAI's GPT-4o model (accepts an optional prompt query parameter)
  • GET /docs: Swagger UI documentation
  • GET /redoc: ReDoc documentation

OpenAI Integration

The /openai endpoint uses OpenAI's GPT-4o model and requires an OpenAI API key to be set as an environment variable:

Local Setup
# 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 Setup
# 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

Example Usage

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

# Get personalized greeting
curl http://127.0.0.1:8000/hello/John

# Get OpenAI chat completion with default prompt
curl http://127.0.0.1:8000/openai

# Get OpenAI chat completion with custom prompt
curl "http://127.0.0.1:8000/openai?prompt=Tell%20me%20a%20joke%20about%20programming"
Using MCP

Connect to MCP Inspector

npx @modelcontextprotocol/inspector
Using a web browser

Development

To make changes to the application, edit the main.py file. The server will automatically reload if you run it with the --reload flag.

Comments

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