LinkedIn Posts Hunter
Automate LinkedIn job post search and management via AI assistants by scraping and organizing relevant opportunities with local data storage.
About
LinkedIn Posts Hunter is a powerful Model Context Protocol (MCP) server designed to give job seekers a significant edge by automating the search and management of LinkedIn job posts through AI assistants. It leverages Playwright to scrape opportunities often found on LinkedIn before they appear on traditional job boards, storing all data locally in a SQLite database for complete privacy. Users can interact with their job data through natural language commands via an MCP-compatible AI client (like Claude Desktop or Cursor) or a comprehensive React-based dashboard, allowing for efficient filtering, tracking, and management of applications with dual control.
Key Features
- AI-powered LinkedIn job post scraping and management
- Local, private SQLite database for all scraped posts and tracking data
- Interactive React dashboard for visual management and application tracking
- Dual control via AI assistant commands or a point-and-click web UI
- Persistent LinkedIn session authentication using locally stored cookies
- 0 GitHub stars
Use Cases
- Programmatically filtering and organizing LinkedIn posts based on keywords, dates, and application status
- Automating the search and discovery of early job opportunities on LinkedIn
- Efficiently tracking and managing job applications through an AI assistant or web dashboard
