
mcp test repo
A test repository created using the GitHub MCP server
Repository Info
About This Server
A test repository created using the GitHub MCP server
Model Context Protocol (MCP) - This server can be integrated with AI applications to provide additional context and capabilities, enabling enhanced AI interactions and functionality.
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
/openaiendpoint) - 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 messageGET /hello/{name}: Returns a personalized greeting with the provided nameGET /openai: Returns a response from OpenAI's GPT-4o model (accepts an optionalpromptquery parameter)GET /docs: Swagger UI documentationGET /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
- 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.
Quick Start
Clone the repository
git clone https://github.com/xxradar/mcp-test-repoInstall dependencies
cd mcp-test-repo
npm installFollow the documentation
Check the repository's README.md file for specific installation and usage instructions.
Repository Details
Recommended MCP Servers
Discord MCP
Enable AI assistants to seamlessly interact with Discord servers, channels, and messages.
Knit MCP
Connect AI agents to 200+ SaaS applications and automate workflows.
Apify MCP Server
Deploy and interact with Apify actors for web scraping and data extraction.
BrowserStack MCP
BrowserStack MCP Server for automated testing across multiple browsers.
Zapier MCP
A Zapier server that provides automation capabilities for various apps.