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MCP Server Practice

@mybarefootstory

代码仓库

基本信息

分类

其他

传输方式

stdio

作者

mybarefootstory

关于 MCP Server Practice

暂无概览

#mcp#server#data-retrieval

MCP Server Practice 配置

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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

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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?

MCP Server Practice is a repository containing two Model Context Protocol (MCP) server implementations: one for scraping LinkedIn profiles using the Fresh LinkedIn Profile Data API (via RapidAPI), and another for retrieving weather alerts and forecasts from the National Weather Service (NWS) API. It is intended for developers integrating AI services with LinkedIn profile data or real-time weather information.

How to use MCP Server Practice?

Clone the repository, install dependencies (httpx, python-dotenv, mcp), and create a .env file with your RAPIDAPI_KEY. Run the desired server script; for LinkedIn, use the get_profile tool with a LinkedIn URL, and for weather, use get_alerts (by US state) or get_forecast (by latitude/longitude). Both servers communicate over stdio transport.

Key features of MCP Server Practice

  • LinkedIn profile scraping via Fresh LinkedIn Data API
  • Weather alerts and forecasts from NWS API
  • Asynchronous HTTP requests using httpx
  • Environment variable management with python-dotenv
  • Implements MCP servers with FastMCP framework
  • Stdio transport for tool invocation

Use cases of MCP Server Practice

  • Fetch detailed LinkedIn profile data for recruitment or lead generation
  • Retrieve active weather alerts for a specified US state
  • Obtain a weather forecast for a given latitude/longitude
  • Integrate AI assistants with up-to-date LinkedIn or weather data

常见问题

1

What external APIs does MCP Server Practice use?

It uses the Fresh LinkedIn Profile Data API (via RapidAPI) for LinkedIn scraping and the public National Weather Service (NWS) API for weather data.

2

What are the prerequisites for running MCP Server Practice?

Python 3.7+, the libraries `httpx`, `python-dotenv`, and `mcp`, plus a valid RapidAPI key stored in a `.env` file.

3

How do I set up the RapidAPI key?

Create a `.env` file in the project root and add `RAPIDAPI_KEY=your_key_here`. The key is required only for the LinkedIn scraper; the NWS weather service is free and does not need authentication.

4

What transport does the server use?

Both servers run with `transport="stdio"`, as shown in the `mcp.run()` calls. This is the standard transport for MCP tools communicating over standard input/output.

5

What are the known limitations of MCP Server Practice?

The LinkedIn scraper depends on the Fresh LinkedIn Profile Data API, which is a third‑party, likely paid service. The weather service is limited to US data (alerts by state, forecasts by coordinates) and requires an internet connection for NWS API calls.

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