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MCP Server Practice

@Dhiraj123-star

代码仓库

基本信息

分类

其他

传输方式

stdio

作者

Dhiraj123-star

关于 MCP Server Practice

暂无概览

MCP Server Practice 配置

暂无标准配置

该服务器的 README 中没有可解析的 MCP 配置块，请前往代码仓库查看安装说明。

代码仓库

MCP Server Practice 工具

工具列表暂未提供

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 🧠 MCP Server Practice?

A modular FastAPI-based server powered by FastMCP that showcases practical implementations of AI tools, math operations, web search, audio response generation, and external API integration. It is designed for AI agents or CLI tools that need to call these tools via a standardized interface.

How to use 🧠 MCP Server Practice?

The server is launched with mcp.run(transport="stdio"). Each tool is defined using the @mcp.tool() decorator, making them accessible as callable interfaces. No installation or configuration commands are given beyond the Python + dotenv environment.

Key features of 🧠 MCP Server Practice

  • Math utilities: add and multiply for integer arithmetic.
  • Live weather data for any city via WeatherAPI.
  • Web search using OpenAI’s web search tool.
  • Audio response generation (WAV format) using OpenAI’s gpt-4o.
  • Custom resource greeting://{name} returning a personalized greeting.

Use cases of 🧠 MCP Server Practice

  • Adding or multiplying numbers through an AI agent.
  • Getting real‑time weather conditions for a city.
  • Performing live web searches and retrieving concise results.
  • Converting text queries into spoken audio files.
  • Generating personalized greeting strings from a resource route.

常见问题

1

What runtime and dependencies are required?

Python with the FastAPI, FastMCP, OpenAI, and python‑dotenv packages, plus environment variables for API keys.

2

How does audio generation work?

`audio_query(text)` uses OpenAI’s `gpt-4o` audio capabilities and saves the resulting WAV file to the `/audio` folder.

3

What transport does the server use?

The server runs with `transport="stdio"`, as shown in the startup command `mcp.run(transport="stdio")`.

4

Are there any authentication or security measures described?

The README does not mention authentication or security measures beyond using a `.env` file for environment variables.

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