MCP Search Server

# LinkedIn Candidate Search & CSV Export Tool This tool uses playwright and filesystems MCP servers and automates searching LinkedIn for candidates matching specific criteria and exports their details to a CSV file. ## Overview The script (`main_csv.py`) uses the Model Context Protocol (MCP) framework to: 1. Search LinkedIn for candidates based on user-provided criteria 2. Extract candidate profile information 3. Export qualified candidates to a CSV file ## Prerequisites - Python 3.10 - Node.js (for Playwright) - MCP Agent configuration files: - `mcp_agent.config.yaml` - `mcp_agent.secrets.yaml` (with LinkedIn credentials) ## Required MCP Servers The tool uses two MCP servers: 1. **Playwright Server**: Handles browser automation for LinkedIn interaction - Command: `npx @playwright/mcp@latest` 2. **Filesystem Server**: Manages CSV file operations - Command: `npx @modelcontextprotocol/server-filesystem` ## Configuration 1. Set up `mcp_agent.config.yaml` with: - Server configurations for Playwright and Filesystem - Logging settings - Execution engine settings 2. Configure `mcp_agent.secrets.yaml` with: - LinkedIn credentials (username and password) - OpenAI API key - Filesystem paths ## Usage uv run main.py --criteria "Python developers in San Francisco" --max-results 7 --output "/desktop/JOB.csv" Run the script from the command line using: uv run main.py --criteria "THE POSITION YOU ARE LOOKING FOR" --max-results NUMBER OF MAX RESULTS --output "LOCATION OF SAVED RESULTS"