LinkedIn Profile Scraper — No Cookies 🍪

Scrape public LinkedIn profile data without login or cookies. Extract names, headlines, current titles, companies, locations, education, skills, and more from any public LinkedIn profile.

Built with CheerioCrawler (no browser overhead). Pay per result.

What it extracts

Field	Source	Always available?
Full name	JSON-LD / OG / HTML	✅
Headline	JSON-LD / OG	✅
Current title	JSON-LD / HTML	✅
Current company	JSON-LD / HTML	✅
Location	JSON-LD / OG / HTML	✅
About / bio	HTML / OG description	Usually
Profile image	JSON-LD / OG	✅
Work experience	JSON-LD + HTML	Optional
Education	JSON-LD + HTML	Optional
Skills	HTML	Optional
Follower count	OG / HTML	Sometimes
Connection count	OG / HTML	Sometimes
Data quality flag	—	✅

Input

Paste LinkedIn profile URLs (one per line). Accepts:

• https://www.linkedin.com/in/satyanadella
• https://linkedin.com/in/satyanadella/
• linkedin.com/in/satyanadella
• satyanadella (bare slug)

Options

• Include Experience — full work history (default: on)
• Include Education — education list (default: on)
• Include Skills — skills list (default: off)
• Slow Mode — add random delays for 50+ profiles (default: off)
• Max Concurrency — parallel requests, 1–20 (default: 5)
• Proxy — residential proxies strongly recommended

How it works

1. Normalizes and deduplicates input URLs
2. Fetches each public profile page via CheerioCrawler with proxy rotation
3. Extracts structured data from <script type="application/ld+json"> (JSON-LD Person object)
4. Supplements with OG meta tags and visible HTML parsing
5. Detects login walls and flags blocked profiles

No headless browser. No cookies. No account risk.

Data quality flags

• full — JSON-LD Person data found (best quality)
• partial — Name found but no JSON-LD (OG/HTML only)
• minimal — Very limited data extracted
• blocked — Login wall detected
• failed — Request failed after retries

Pricing

Pay per result: $2.00 / 1,000 profiles

No charge for blocked or failed requests.

Limitations

• LinkedIn may change their public page structure at any time. The scraper uses JSON-LD → OG meta → HTML fallback strategies.
• Some profiles are fully private and return no public data.
• Skills data is limited on public pages (usually top 3–5 only).
• Residential proxies significantly improve reliability.
• Rate limiting is common at scale. Use Slow Mode for 50+ profiles.

Deploy

1. Push to GitHub

# Create a new repo on GitHub (github.com → New repository), then:
git remote add origin https://github.com/YOUR_USERNAME/linkedin-profile-scraper.git
git branch -M main
git push -u origin main

Or with SSH: git@github.com:YOUR_USERNAME/linkedin-profile-scraper.git

2. Apify Console → Link Git repo → Build

1. Go to Apify Console → Actors → Create new → Import from Git repository.
2. Paste your repo URL (e.g. https://github.com/YOUR_USERNAME/linkedin-profile-scraper) and connect (GitHub OAuth if needed).
3. Apify will detect .actor/actor.json and use it. Click Build to build the Docker image.
4. (Optional) Set Pay per result pricing at $2/1,000 profiles, then Publish to the Apify Store.

Disclaimer

This Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by LinkedIn Corporation. LinkedIn® is a registered trademark of LinkedIn Corporation. All trademarks are property of their respective owners. Please use this tool responsibly and in accordance with applicable laws and regulations.