iflow-mcp_mcp-linkedin-server

# LinkedIn Browser MCP Server A FastMCP-based server for LinkedIn automation and data extraction using browser automation. This server provides a set of tools for interacting with LinkedIn programmatically while respecting LinkedIn's terms of service and rate limits. ## Features - **Secure Authentication** - Environment-based credential management - Session persistence with encrypted cookie storage - Rate limiting protection - Automatic session recovery - **Profile Operations** - View and extract profile information - Search for profiles based on keywords - Browse LinkedIn feed - Profile visiting capabilities - **Post Interactions** - Like posts - Comment on posts - Read post content and engagement metrics ## Prerequisites - Python 3.8+ - Playwright - FastMCP library - LinkedIn account ## Installation 1. Clone the repository: ```bash git clone [repository-url] cd mcp-linkedin-server ``` 2. Create and activate a virtual environment: ```bash python -m venv env source env/bin/activate # On Windows: env\Scripts\activate ``` 3. Install dependencies: ```bash pip install -r requirements.txt playwright install chromium ``` 4. Set up environment variables: Create a `.env` file in the root directory with: ```env LINKEDIN_USERNAME=your_email@example.com LINKEDIN_PASSWORD=your_password COOKIE_ENCRYPTION_KEY=your_encryption_key # Optional: will be auto-generated if not provided ``` ## Usage 1. Start the MCP server: ```bash python linkedin_browser_mcp.py ``` 2. Available Tools: - `login_linkedin_secure`: Securely log in using environment credentials - `browse_linkedin_feed`: Browse and extract posts from feed - `search_linkedin_profiles`: Search for profiles matching criteria - `view_linkedin_profile`: View and extract data from specific profiles - `interact_with_linkedin_post`: Like, comment, or read posts ### Example Usage ```python from fastmcp import FastMCP # Initialize client client = FastMCP.connect("http://localhost:8000") # Lo…