# 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.
## Features
- **Fetch Profile Data:** Retrieves LinkedIn profile information including skills and other settings (with most additional details disabled).
- **Asynchronous HTTP Requests:** Uses `httpx` for non-blocking API calls.
- **Environment-based Configuration:** Reads the `RAPIDAPI_KEY` from your environment variables using `dotenv`.
## 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](https://rapidapi.com/) and add it to a `.env` file in your project directory (or set it in your environment).
## Installation
1. **Clone the Repository:**
```bash
git clone https://github.com/AIAnytime/Awesome-MCP-Server
cd linkedin_profile_scraper
```
2. **Install Dependencies:**
```bash
uv add mcp[cli] httpx requests
```
3. **Set Up Environment Variables:**
Create a `.env` file in the project directory with the following content:
```ini
RAPIDAPI_KEY=your_rapidapi_key_here
```
## Running the Server
To run the MCP server, execute:
```bash
uv run linkedin.py
```
The server will start and listen for incoming requests via standard I/O.
## MCP Client Configuration
To connect your MCP client to this server, add the following configuration to your `config.json`. Adjust the paths as necessary for your environment:
```json
{
"mcpServers": {
"linkedin_profile_scraper": {
"command": "C:/Users/aiany/.local/bin/uv",
"args": [
"--directory",
"C:/Users/aiany/OneDrive/Desktop/YT Video/linkedin-mcp/project",
"run",
"linkedin.py"
]
}
}
}
```
## Code Overview
- **Environment Setup:** The server uses `dotenv` to load the `RAPIDAPI_KEY` required to authenticate with the Fresh LinkedIn Profile Data API.
- **API Call:** The asynchronous function `get_linkedin_data` makes a GET request to the API with specified query parameters.
- **MCP Tool:** The `get_profile` tool wraps the API call and returns formatted JSON data, or an error message if the call fails.
- **Server Execution:** The MCP server is run with the `stdio` transport.
## Troubleshooting
- **Missing RAPIDAPI_KEY:** If the key is not set, the server will raise a `ValueError`. Make sure the key is added to your `.env` file or set in your environment.
- **API Errors:** If the API request fails, the tool will return a message indicating that the profile data could not be fetched.
## License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for more details.
