Linkedin MCP Server

🚀 LinkedIn Profile Scraper MCP Server

This MCP server utilizes the Fresh LinkedIn Profile Data API to fetch LinkedIn profile information. It implements the Model Context Protocol (MCP) and offers a tool named get_profile, which takes a LinkedIn profile URL as input and returns profile data in JSON format.

🚀 Quick Start

The LinkedIn Profile Scraper MCP Server enables you to retrieve LinkedIn profile information. Here's a simple example of using the get_profile tool:

# Assume there is a function to call get_profile
# result = get_profile('https://www.linkedin.com/in/some-profile-url')
# print(result)

✨ Features

• Profile Data Scraping: Retrieve LinkedIn profile information, including skills and other settings (most other details are disabled).
• Asynchronous HTTP Requests: Use httpx for non-blocking API calls.
• Environment-based Configuration: Read the RAPIDAPI_KEY from your environment variables via dotenv.

📦 Installation

Prerequisites

• Python 3.7+: Ensure you are using Python version 3.7 or higher.
• MCP Framework: Make sure the MCP framework is installed.
• Required Libraries: Install httpx, python-dotenv, and other dependencies.
• RAPIDAPI_KEY: Obtain an API key from RapidAPI and add it to the .env file in the project directory (or set it as an environment variable).

Steps

1. Clone the Repository

   git clone https://github.com/codingaslu/Linkedin_Mcp_Server
   cd Linkedin_Mcp_Server
   

2. Install Dependencies

   uv add mcp[cli] httpx requests
   

3. Set Environment Variables Create a .env file in the project directory with the following content:

   RAPIDAPI_KEY=your_rapidapi_key_here
   

💻 Usage Examples

Basic Usage

To run the MCP server, execute the following command:

uv run linkedin.py

The server will start and listen for incoming requests via standard input/output.

Advanced Usage

To configure your MCP client to connect to this server, add the following configuration to config.json. Adjust the paths as needed:

{
  "mcpServers": {
    "linkedin_profile_scraper": {
      "command": "C:/Users/aiany/.local/bin/uv",
      "args": [
        "--directory",
        "C:/Users/aiany/OneDrive/Desktop/linkedin-mcp/project",
        "run",
        "linkedin.py"
      ]
    }
  }
}

📚 Documentation

Code Overview

• Environment Setup: The server uses dotenv to load the required RAPIDAPI_KEY for authentication.
• API Calls: The asynchronous function get_linkedin_data sends a GET request to the API and specifies query parameters.
• MCP Tool: The get_profile tool encapsulates API calls and returns formatted JSON data or an error message if the call fails.
• Server Execution: The MCP server runs using stdio transport.

Troubleshooting

• Missing RAPIDAPI_KEY: If the key is not set, the server will throw a ValueError. Make sure to add the key to the .env file or set it in the environment.
• API Error: If the API request fails, the tool will return a message indicating that the profile data cannot be retrieved.

📄 License

This project is licensed under the MIT License. For more details, please refer to the LICENSE file.