LinkedIn Profile Scraper MCP Server

@codingaslu

Basic information

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

LinkedIn Profile Scraper MCP Server config

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

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

LinkedIn Profile Scraper MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

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

Frequently asked questions

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](https://rapidapi.com/) 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.

Comments

More Browser Automation MCP servers

Nullprint

nullprintai

Let Claude Code, Claude Desktop, OpenAI Codex, Kimi and any MCP-capable AI agent create, launch, check and drive browser profiles in Nullprint, the AI antidetect browser. Install with one command.

HTML/CSS to Image

An MCP server for generating images from HTML & CSS or screenshots of URLs using htmlcsstoimage.com.

Fetcher MCP

jae-jae

MCP server for fetch web page content using Playwright headless browser.

1.1K

Playwright Mcp

microsoft

Playwright MCP server

34.8K

Fastcrw

Fast, lightweight Firecrawl/Tavily alternative in Rust. Web scraper, crawler & search API with MCP server for AI agents. Drop-in Firecrawl-compatible API (/scrape, /crawl, /search). 2.3x faster than Tavily, 1.5x faster than Firecrawl in 1K-URL benchmarks. 6 MB RAM, single binary.

286