Server Practice 2 FAQs

Question 1

What is Server Practice 2?

Accepted Answer

Server Practice 2 provides implementations of Model Context Protocol (MCP) servers for scraping LinkedIn profiles and retrieving weather data from the National Weather Service (NWS) API. It's designed for seamless integration between AI services.

Question 2

How does the Weather Data Service work?

Accepted Answer

The Weather Data Service retrieves weather alerts and forecasts using the NWS API. It offers tools like `get_alerts` (for state-level alerts) and `get_forecast` (for location-based forecasts), both accessible via FastMCP.

Question 3

How do I install and use Server Practice 2?

Accepted Answer

Clone the repository, install the dependencies (httpx, python-dotenv, mcp), and set your RapidAPI key in a `.env` file. Then, run the individual server scripts (LinkedIn or Weather) and use the provided tools to access the data.

Question 4

What are the main features of the LinkedIn Profile Scraper?

Accepted Answer

The LinkedIn Profile Scraper uses the Fresh LinkedIn Profile Data API to fetch profile data. It's built with FastMCP and offers a `get_profile` tool to easily retrieve profile information using a LinkedIn URL.

Question 5

What technologies are used in Server Practice 2?

Accepted Answer

Server Practice 2 utilizes Python 3.7+, httpx for asynchronous HTTP requests, python-dotenv for environment variable management, and mcp for MCP server implementation.  It leverages FastMCP for efficient server creation.

Server Practice 2

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