FastAPI Hello World Application
About
A test repository created using the GitHub MCP server
Details
- Author
- xxradar
- Downloads
- 384
- Categories
- Developer Tools, API
Jump to
- Root endpoint returning a Hello World message
- Dynamic greeting endpoint with a name parameter
- OpenAI GPT‑4o chat completion endpoint
- Automatic Swagger UI and ReDoc documentation
- Supports local and Docker deployment
- MCP SSE support for integration
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
FastAPI Hello World ApplicationCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Clone the repository, install dependencies, and set the OPENAI_API_KEY environment variable if using the OpenAI endpoint. Run locally with uvicorn main:app --reload or python main.py, or use Docker with docker build -t fastapi-hello-world . then docker run -p 8000:8000 -e OPENAI_API_KEY=your_key fastapi-hello-world. The MCP server can be connected via the MCP Inspector.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"fastapi hello world application": {
"mcp-test-repo": {
"command": "python",
"args": [
"-m",
"venv",
"venv"
]
}
}
}
}McpServers
{
"mcp-test-repo": {
"command": "python",
"args": [
"-m",
"venv",
"venv"
]
}
}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)
```bash
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