Free MCP AI LinkedIn Jobs Scraper Data API - Automated Job Extractor

🚀 FREE MCP AI LinkedIn Jobs Scraper Data API - Extract job postings automatically with Model Context Protocol technology. Professional MCP-powered AI job scraper & data extractor. Get job titles, companies, locations, salaries, descriptions. Free automated LinkedIn scraping tool with MCP technology. Best AI jobs data extractor & API for recruiters and developers.

🎯 Why Choose This FREE MCP AI Scraper?

💰 100% FREE Benefits:

• ✅ No subscription fees - Completely free to use
• ✅ Unlimited job scraping - No usage limits
• ✅ MCP-powered technology - Advanced Model Context Protocol
• ✅ AI-enhanced extraction - Smarter data recognition
• ✅ Residential proxy support - Built-in free proxy rotation
• ✅ Full job details - Complete data extraction at no cost

🧠 MCP-Optimized Data Extraction:

• 📋 Job Listings: Title, Company, Location, Posted Time, URL
• 📝 Full Details: Description, Requirements, Salary, Job Type
• 🏢 Company Info: Size, Industry (when available)
• ⏰ Metadata: Scraped timestamp, job URLs
• 🤖 AI-Enhanced: Smart pattern recognition with MCP
• 🔍 MCP-Driven: Visual page analysis for optimal selectors

Anti-Detection:

• 🌐 Residential proxy support
• 👤 Headful browser mode
• 🖱️ Human-like interaction patterns
• ⏱️ Random delays and scrolling

📁 Project Structure

linkedin-jobs-scraper/
├── linkedin-jobs-scraper.js    # Main scraper class
├── apify-actor.js              # Apify platform integration
├── test-jobs-scraper.js        # Local testing script
├── package.json                # Dependencies
├── Dockerfile                  # Container configuration
└── README.md                   # This file

🔧 Local Testing

1. Install dependencies:

   cd linkedin-jobs-scraper
   npm install
   

2. Add your LinkedIn cookies to test-jobs-scraper.js

3. Run local test:

   $node test-jobs-scraper.js
   

4. Configure residential proxies (optional):

   const proxyConfig = {
       server: 'http://proxy-server:port',
       username: 'your-username',
       password: 'your-password'
   };
   const useProxy = true;
   

🌐 Apify Deployment

1. Push to Apify:

   $npx apify-cli push
   

2. Input Schema:

   {
       "searchUrl": "https://www.linkedin.com/jobs/search/?keywords=software%20engineer",
       "cookies": [{"name": "li_at", "value": "..."}],
       "maxJobs": 50,
       "includeDetails": true,
       "proxyConfig": {"useApifyProxy": true}
   }
   

📊 Output Format

[
    {
        "jobTitle": "Software Engineer",
        "company": "Microsoft",
        "location": "Redmond, WA",
        "postedTime": "2 hours ago",
        "jobUrl": "https://www.linkedin.com/jobs/view/...",
        "description": "We are looking for a talented Software Engineer...",
        "requirements": "5+ years of experience with...",
        "salary": "$120,000 - $180,000",
        "jobType": "Full-time",
        "scrapedAt": "2026-02-07T00:00:00.000Z"
    }
]

🎯 MCP Optimization

Multi-Strategy Extraction:

1. Semantic Selectors - h3, h4, time elements
2. Pattern Matching - Location formats, salary patterns
3. Contextual Extraction - Nearby element analysis
4. Fallback Mechanisms - Multiple extraction paths

Discovered Selectors:

• Job Title: h3
• Company: h4 a
• Location: Pattern matching on generic elements
• Posted Time: time
• Job URL: a[href*="/jobs/view/"]

🚀 Performance

• ✅ 60+ jobs per search (MCP-tested)
• ✅ Full detail extraction (2-4 seconds per job)
• ✅ Residential proxy ready (anti-blocking)
• ✅ Session persistence (cookie management)

🛡️ Best Practices

• Use residential proxies for production
• Rotate search terms to avoid detection
• Limit concurrent requests (2-4 second delays)
• Monitor cookie expiration (refresh weekly)

🔥 Built with MCP-optimized selectors for maximum reliability!