LinkedIn Posts Hunter MCP Server

Automate LinkedIn job post searching and tracking with AI-powered assistance

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📖 Overview

LinkedIn Posts Hunter MCP is a Model Context Protocol (MCP) server that provides tools for automating LinkedIn job post search and management through your AI assistant (Claude Desktop, Cursor, or other MCP-compatible clients).

Why LinkedIn Posts? Job opportunities often appear in LinkedIn posts first, before they're posted on traditional job boards. By monitoring LinkedIn posts, you can discover opportunities earlier and get a competitive advantage in your job search.

How it works:

1. Authentication & Scraping

• The MCP server exposes a Playwright-based tool that your AI assistant can invoke to automate browser interactions with LinkedIn
• First-time use requires logging into LinkedIn through a browser window to capture session cookies
• These cookies are stored locally on your computer for persistent authentication
• Once authenticated, your AI assistant can call the search tool with keywords (either from your conversation or suggested by the AI) to scrape job posts

2. Local Data Storage

• All scraped posts are saved to a local SQLite database on your machine
• The database stores post content, metadata (author, dates, engagement metrics), and tracking info (whether you've applied)
• Your data never leaves your computer

3. Visual Interface

• A separate tool launches a React dashboard that renders the scraped posts from your local database
• Visualize all your scraped posts in table or card views with profile images and engagement metrics
• Track your applications by marking posts as "applied" or "saved for later" directly in the UI
• Quick actions let you filter, sort, and manage posts with point-and-click simplicity
• Changes made in the React app are written to the local database. And changes made through MCP commands are reflected in the UI.

4. Dual Control

• You can manage posts through either the React UI or through MCP tools like manage_posts and viewer_filters
• The React app updates via polling, so changes made through MCP commands are reflected in the UI
• This gives you flexibility: use natural language commands with your AI assistant, or point-and-click in the dashboard

🎬 Video Demo

https://github.com/user-attachments/assets/93f32db4-9ecf-4438-889f-ebe95b5b17e9

📹 Watch Walkthrough

Watch the complete workflow from authentication to post management

🎨 Diagram

System architecture showing components and their interactions

🛠️ Available Tools

This MCP server exposes 6 tools that can be called from your AI assistant:

1. auth

Manage LinkedIn authentication with persistent session storage.

Parameters:

• action: "authenticate" | "status" | "clear"
• force_reauth: boolean (

... View full README on GitHub