MCP Server Practice

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Basic information

About MCP Server Practice

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MCP Server Practice config

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MCP Server Practice tools

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Overview

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

Frequently asked questions

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.

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.

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.

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.

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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