LinkedIn Profile AnalyzerSAFE

A powerful LinkedIn profile analyzer MCP (Model Context Protocol) server that interacts with LinkedIn's API to fetch, analyze, and manage LinkedIn posts data. This MCP is specifically designed to work with Claude AI.

Features

• Fetch and store LinkedIn posts for any public profile
• Search through posts with keyword filtering
• Get top performing posts based on engagement metrics
• Filter posts by date range
• Paginated access to stored posts
• Easy integration with Claude AI

Prerequisites

• Python 3.7+
• RapidAPI key for LinkedIn Data API
• Claude AI access

Getting Started

1. Get RapidAPI Key

1. Visit LinkedIn Data API on RapidAPI
2. Sign up or log in to RapidAPI
3. Subscribe to the LinkedIn Data API
4. Copy your RapidAPI key from the dashboard

2. Installation

1. Clone the repository:

git clone https://github.com/rugvedp/linkedin-mcp.git
cd linkedin-mcp

1. Install dependencies:

pip install -r requirements.txt

1. Set up environment variables:
2. Create a .env file
3. Add your RapidAPI key:

RAPIDAPI_KEY=your_rapidapi_key_here

Project Structure

linkedin-mcp/
├── main.py              # Main MCP server implementation
├── mcp.json            # MCP configuration file
├── requirements.txt    # Python dependencies
├── .env               # Environment variables
└── README.md          # Documentation

MCP Configuration

The mcp.json file configures the LinkedIn MCP server:

{
"mcpServers": {
"LinkedIn Updated": {
"command": "uv",
"args": [
"run",
"--with",
"mcp[cli]",
"mcp",
"run",
"path/to/your/script.py"
]
}
}
}

Make sure to update the path in args to