LinkedIn Profile Scraper MCP Server

Name: LinkedIn Profile Scraper MCP Server
Author: codingaslu

@codingaslu

About LinkedIn Profile Scraper MCP Server

This MCP server uses the Fresh LinkedIn Profile Data API to fetch LinkedIn profile information. It is implemented as a model context protocol (MCP) server and exposes a single tool, get_profile, which accepts a LinkedIn profile URL and returns the profile data in JSON format.

#linkedin #profile-scraper #data-fetcher

Basic information

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "Linkedin_Mcp_Server": {
      "command": "uv",
      "args": [
        "run",
        "linkedin.py"
      ]
    }
  }
}

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is LinkedIn Profile Scraper MCP Server?

It is an MCP server that uses the Fresh LinkedIn Profile Data API to fetch LinkedIn profile information. It exposes a single tool, get_profile, which accepts a LinkedIn profile URL and returns the profile data in JSON format.

How to use LinkedIn Profile Scraper MCP Server?

Install dependencies with uv add mcp[cli] httpx requests. Create a .env file with your RAPIDAPI_KEY. Run the server using uv run linkedin.py. Then configure your MCP client to point to the server, specifying the uv command, the project directory, and the script as arguments.

Key features of LinkedIn Profile Scraper MCP Server

Fetches LinkedIn profile data via RapidAPI
Uses asynchronous HTTP requests (httpx)
Environment-based configuration (dotenv)
Exposes a single get_profile tool
Returns profile data in JSON format

Use cases of LinkedIn Profile Scraper MCP Server

Retrieve LinkedIn profile information for data enrichment
Automate background checks or candidate screening
Integrate profile data into AI-powered workflows
Enrich CRM records with external professional details

FAQ from LinkedIn Profile Scraper MCP Server

What API does the server use?

It uses the Fresh LinkedIn Profile Data API available through RapidAPI.

What are the prerequisites to run the server?

You need Python 3.7+, the MCP framework, installed dependencies (httpx, python-dotenv, etc.), and a valid RAPIDAPI_KEY.

How do I obtain an API key?

Obtain an API key from RapidAPI and add it to a .env file or set it in your environment.

What happens if the `RAPIDAPI_KEY` is missing?

The server will raise a ValueError indicating the key is missing.

What occurs if the API request fails?

The get_profile tool returns a message indicating that the profile data could not be fetched.

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