Linkedin Employee Extractor
Pricing
from $5.00 / 1,000 results
Linkedin Employee Extractor
Extract employee profiles from LinkedIn company people search using authenticated requests (requires session cookies)
Pricing
from $5.00 / 1,000 results
Rating
0.0
(0)
Developer

Bhojraj Pilaniya
Actor stats
0
Bookmarked
6
Total users
3
Monthly active users
7 days ago
Last modified
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LinkedIn Employee Extractor & API
This project is unofficial and not affiliated with LinkedIn.
A lightweight LinkedIn employee extractor that uses your session cookies to fetch people profiles (no browser automation needed).
Features
- Authenticated Requests: Uses
li_atandJSESSIONIDcookies. - Fast & Lightweight: No Selenium/Puppeteer overhead.
- API Server: Built-in HTTP server to trigger scrapes remotely.
- Pagination Support: Fetch all available results for a company/role.
Setup
1. Install dependencies
$pip install -r requirements.txt
2. Get your LinkedIn cookies
- Open Chrome and go to linkedin.com
- Make sure you're logged in
- Open DevTools (
F12orCmd+Option+I) - Go to Application tab → Cookies →
https://www.linkedin.com - Copy these two values:
li_at: Your session token.JSESSIONID: Your CSRF token (remove quotes if present, e.g.,ajax:...).
3. Configure .env
Create a .env file based on the example:
GEO_URN="102713980" # India (optional)DELAY_BETWEEN_REQUESTS=2PORT=8000
Usage
Option 1: Run the API Server (Recommended)
Start the server:
$python server.py
Send a scraping request:
curl -X POST http://localhost:8000/scrape \-H "Content-Type: application/json" \-d '{"company_url": "https://www.linkedin.com/company/google","tags": ["software engineer"],"max_pages": 0,"li_at": "YOUR_LI_AT_COOKIE","jsessionid": "YOUR_JSESSIONID_COOKIE"}'
Note: If you provide
li_atandjsessionidin the request body, they will override the environment variables.
Option 2: Run as CLI Script
Edit .env with your target COMPANY_URLS and TAGS, then run:
$python scraper.py
Deployment
Docker
Build and run the container:
docker build -t linkedin-scraper .docker run -p 8000:8000 --env-file .env linkedin-scraper
Cloud (Render/Railway/Heroku)
- Push to GitHub (see instructions below).
- Connect your repo to a cloud provider.
- Add your Environment Variables (
LI_AT,JSESSIONID, etc.) in the cloud dashboard. - Deploy!