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FastAPI Hello World Application MCP Server

@xxradar

代码仓库

基本信息

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开发工具

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xxradar

关于 FastAPI Hello World Application MCP Server

A test repository created using the GitHub MCP server

#fastapi#api#gpt-integration

FastAPI Hello World Application MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "mcp-test-repo": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        "venv"
      ]
    }
  }
}

FastAPI Hello World Application MCP Server 工具

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当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is FastAPI Hello World Application?

It is a simple Hello World API built with FastAPI and MCP SSE support. It provides basic greeting endpoints and an endpoint for AI‑powered chat completions using OpenAI GPT‑4o.

How to use FastAPI Hello World Application?

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.

Key features of FastAPI Hello World Application

  • 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

Use cases of FastAPI Hello World Application

  • Quick demonstration of a FastAPI‑based MCP server
  • Testing MCP SSE protocol with a simple API
  • Experimenting with OpenAI GPT‑4o via HTTP endpoint
  • Learning FastAPI with MCP integration

常见问题

1

What dependencies are required?

Python 3.7+, pip, and an OpenAI API key (only for the `/openai` endpoint). Docker is optional.

2

How do I run the application?

Locally with `uvicorn main:app --reload` or `python main.py`. Docker: build the image and run the container with port `8000` mapped and the `OPENAI_API_KEY` environment variable.

3

Where does the data live?

The application does not persist any data; it only returns responses generated by its own endpoints or the OpenAI API.

4

What transports and authentication are used?

The MCP server uses SSE as its transport. The OpenAI endpoint requires the `OPENAI_API_KEY` to be set as an environment variable; no other authentication is needed.

5

What are the known limits?

The `/openai` endpoint will fail if the `OPENAI_API_KEY` environment variable is not set. No other limitations are documented.

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