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Linkedin-Scrap-MCP-Server

Linkedin-Scrap-MCP-Server

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github.com/itsShashankSrivastavaSocial Media2Updated 80w ago

About Linkedin-Scrap-MCP-Server

Linkedin-Scrap-MCP-Server is an MCP server for retrieving current public LinkedIn profile information from a profile URL. It uses the Fresh LinkedIn Profile Data API and returns structured JSON.

Key features

  1. 01Look up profiles by URL
  2. 02Retrieve current public profile data
  3. 03Return structured JSON
  4. 04Make asynchronous API requests

Use cases

  1. 01Check skills listed on a LinkedIn profile
  2. 02Use public profile details in research

MCP support

The server exposes one tool, get_profile, which accepts a LinkedIn profile URL and returns profile JSON or an error message.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

Linkedin-Scrap-MCP-Server

Easily fetch real-time LinkedIn profile information using our MCP (Model Context Protocol) server. This server integrates with the Fresh LinkedIn Profile Data API to return profile details like skills and other basic settings. It exposes a single tool—get_profile—that accepts a LinkedIn profile URL and responds with structured JSON data.


🚀Features

  • Real-Time LinkedIn Data: Retrieve up-to-date profile info including skills and core public data (additional extended fields are disabled by default).
  • Asynchronous Requests: Built with httpx for efficient, non-blocking HTTP calls.
  • Secure API Key Handling: Uses environment variables via dotenv for safe configuration of your RAPIDAPI_KEY.

⚙️Requirements

Before you get started, make sure you have:

  • Python 3.7+
  • MCP Framework installed
  • Required libraries: httpx, python-dotenv
  • RAPIDAPI_KEY: Sign up at RapidAPI and subscribe to the Fresh LinkedIn Profile Data API, then grab your API key.

📦Installation

1. Clone the repository:
git clone https://github.com/itsShashankSrivastava/Linkedin-Scrap-MCP-Server
2. Install dependencies:
uv add mcp[cli] httpx requests
3. Set up your environment variables:
RAPIDAPI_KEY=your_rapidapi_key_here

▶️ Running the Server

To start the MCP server:

uv run linkedin.py

This will launch the server and begin listening for incoming requests over standard I/O.


🤖 MCP Client Configuration

To connect your MCP client to the server, update your config.json with the following:

{
  "mcpServers": {
    "linkedin_profile_scraper": {
      "command": "C:/Users/shashank.srivastava/.local/bin/uv", 
      "args": [
        "--directory",
        "C:/Users/shashank.srivastava/Desktop/linkedin-scrap",  
        "run",
        "linkedin.py" 
      ]
    }
  }
}

💡 Adjust the paths as necessary based on where your server is located.


🧠 How It Works

  • Environment Setup: Uses dotenv to load your RAPIDAPI_KEY.
  • API Integration: Makes asynchronous GET requests to the Fresh LinkedIn Profile Data API using httpx.
  • MCP Tool - get_profile: Wraps the API logic and returns either a clean JSON object or an error message if the request fails.
  • Execution: Runs using the standard I/O (stdio) transport method of the MCP server framework.

🛠 Troubleshooting

  • Missing RAPIDAPI_KEY: If not set, the server will raise a ValueError. Double-check your .env file or system environment variables.
  • API Call Errors: If the LinkedIn API request fails, the tool will return a clear error message indicating what went wrong.

Feel free to ⭐️ the repo if you find it helpful or open an issue if you need support!

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