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    Mcp Fastapi Learning

    A test repository created using the GitHub MCP server

    0 stars
    Python
    Updated Apr 15, 2025

    Table of Contents

    • Features
    • Prerequisites
    • Setup Instructions
    • Local Setup
    • 1. Clone the repository
    • 2. Create a virtual environment (optional but recommended)
    • 3. Install dependencies
    • 4. Run the application
    • Docker Setup
    • 1. Clone the repository
    • 2. Build the Docker image
    • 3. Run the Docker container
    • API Endpoints
    • OpenAI Integration
    • Local Setup
    • Docker Setup
    • Example Usage
    • Using curl
    • Using MCP
    • Using a web browser
    • Development

    Table of Contents

    • Features
    • Prerequisites
    • Setup Instructions
    • Local Setup
    • 1. Clone the repository
    • 2. Create a virtual environment (optional but recommended)
    • 3. Install dependencies
    • 4. Run the application
    • Docker Setup
    • 1. Clone the repository
    • 2. Build the Docker image
    • 3. Run the Docker container
    • API Endpoints
    • OpenAI Integration
    • Local Setup
    • Docker Setup
    • Example Usage
    • Using curl
    • Using MCP
    • Using a web browser
    • Development

    Documentation

    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

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

    2. Create a virtual environment (optional but recommended)

    bash
    # On macOS/Linux
    python -m venv venv
    source venv/bin/activate
    
    # On Windows
    python -m venv venv
    venv\Scripts\activate

    3. Install dependencies

    bash
    pip install -r requirements.txt

    4. Run the application

    bash
    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:

    bash
    python main.py

    Docker Setup

    1. Clone the repository

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

    2. Build the Docker image

    bash
    docker build -t fastapi-hello-world .

    3. Run the Docker container

    bash
    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

    bash
    # 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

    bash
    # 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

    bash
    # 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

    code
    npx @modelcontextprotocol/inspector

    Using a web browser

    • Open http://127.0.0.1:8000/ in your browser for the Hello World message
    • Open http://127.0.0.1:8000/hello/John in your browser for a personalized greeting
    • Open http://127.0.0.1:8000/openai in your browser to get a response from OpenAI with the default prompt
    • Open http://127.0.0.1:8000/openai?prompt=What%20is%20FastAPI? in your browser to get a response about FastAPI
    • Open http://127.0.0.1:8000/docs for the Swagger UI documentation

    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.

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