Extract LinkedIn Profile Data at Scale
Structured profile data from 500M+ LinkedIn professionals. Work history, education, skills, certifications, and contact info. One API call, clean JSON response.
LinkedIn Profile Data Is Trapped Behind a Wall
LinkedIn's official API restricts profile data access to narrow use cases and approved partners. If you're building a recruiting tool, enriching sales leads, or running market research, the official channels either don't give you what you need or take months to approve.
Building your own extraction infrastructure is costly and fragile. LinkedIn changes its markup frequently, breaks sessions without warning, and rate-limits aggressively. Every week you spend maintaining scrapers is a week not spent on your actual product. The maintenance compounds.
There's a simpler approach. Anysite handles the extraction, session management, and anti-detection for you. You send a profile URL, you get back structured JSON. The infrastructure self-heals when LinkedIn changes its layout, so your pipeline never breaks.
Complete Profile Data in One API Call
The /api/linkedin/user endpoint returns structured profile data organized into logical sections. You control which sections to include per request, paying only for the data you need.
| Category | Fields |
|---|---|
| Identity | First name, last name, headline, location, profile URL, profile picture, URN |
| Professional | Current title, company, industry, connections count |
| Summary | Full about section, top skills |
| Experience | Complete work history with titles, companies, dates, descriptions |
| Education | Schools, degrees, fields of study, dates |
| Skills | Listed skills with endorsement counts |
| Certifications | Certification names, issuers, dates |
| Languages | Language proficiencies |
| Honors | Awards, honors, publications |
| Patents | Patent filings and grants |
Extraction is modular: a basic profile costs 1 credit, and each additional section adds 1 credit. A full profile with all sections costs 9 credits.
API Reference
Endpoint
Parameters
| Parameter | Type | Required | Description |
|---|---|---|---|
user |
string | Yes | LinkedIn profile URL or username |
with_experience |
boolean | No | Include work history (+1 credit) |
with_education |
boolean | No | Include education history (+1 credit) |
with_skill_certificates |
boolean | No | Include skills and certifications (+1 credit) |
with_description_and_top_skills |
boolean | No | Include about section and top skills (+1 credit) |
with_honors |
boolean | No | Include awards and honors (+1 credit) |
with_languages |
boolean | No | Include language proficiencies (+1 credit) |
with_patents |
boolean | No | Include patent filings (+1 credit) |
timeout |
integer | No | Request timeout in seconds (20–1500) |
Response Example
{
"urn": "urn:li:member:123456789",
"first_name": "Jane",
"last_name": "Doe",
"headline": "Senior Software Engineer at Acme Corp",
"location": "San Francisco Bay Area",
"connections": 500,
"profile_url": "https://www.linkedin.com/in/janedoe",
"profile_picture": "https://media.licdn.com/dms/image/...",
"summary": "10+ years building distributed systems...",
"top_skills": ["Python", "System Design", "AWS"],
"experience": [
{
"title": "Senior Software Engineer",
"company": "Acme Corp",
"start_date": "2021-03",
"end_date": null,
"description": "Leading backend infrastructure team..."
}
],
"education": [
{
"school": "Stanford University",
"degree": "M.S. Computer Science",
"field_of_study": "Computer Science",
"start_date": "2012",
"end_date": "2014"
}
],
"skills": [
{
"name": "Python",
"endorsements": 42
},
{
"name": "Distributed Systems",
"endorsements": 31
}
],
"certifications": [
{
"name": "AWS Solutions Architect",
"issuer": "Amazon Web Services",
"date": "2023-06"
}
]
}
Credit Cost
| Request Type | Credits |
|---|---|
| Basic profile | 1 |
| Profile + experience | 2 |
| Full profile (all sections) | 9 |
Code Examples
import requests response = requests.post( "https://api.anysite.io/api/linkedin/user", headers={"Authorization": "Bearer YOUR_API_KEY"}, json={ "user": "https://www.linkedin.com/in/janedoe", "with_experience": True, "with_education": True, "with_skill_certificates": True } ) profile = response.json() print(profile["first_name"], profile["last_name"]) print(profile["headline"])
curl -X POST https://api.anysite.io/api/linkedin/user \ -H "Authorization: Bearer YOUR_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "user": "https://www.linkedin.com/in/janedoe", "with_experience": true, "with_education": true, "with_skill_certificates": true }'
const response = await fetch("https://api.anysite.io/api/linkedin/user", { method: "POST", headers: { "Authorization": "Bearer YOUR_API_KEY", "Content-Type": "application/json" }, body: JSON.stringify({ user: "https://www.linkedin.com/in/janedoe", with_experience: true, with_education: true, with_skill_certificates: true }) }); const profile = await response.json(); console.log(profile.first_name, profile.last_name);
anysite linkedin user "https://www.linkedin.com/in/janedoe"
anysite linkedin user "https://www.linkedin.com/in/janedoe" \ --with-experience \ --with-education \ --with-skill-certificates \ --with-description-and-top-skills \ --with-honors \ --with-languages \ --with-patents
# profiles.txt contains one LinkedIn URL per line while read url; do anysite linkedin user "$url" --with-experience --with-education done < profiles.txt
Use Cases
Recruiting and Talent Sourcing
Problem
Recruiters spend hours manually reviewing LinkedIn profiles, copying candidate details into spreadsheets, and cross-referencing qualifications. At scale, this is unsustainable.
Solution
Use the Profile Data API to automatically extract structured candidate information. Pull work history, education, skills, and certifications into your ATS or CRM with a single API call per candidate.
Result
Screen hundreds of candidates per hour instead of dozens. Consistent data format means you can filter, rank, and match candidates programmatically based on years of experience, specific skills, or education requirements.
Sales Prospecting and Lead Enrichment
Problem
Sales teams work with incomplete lead data. A name and company isn't enough to personalize outreach. Manually researching each prospect on LinkedIn doesn't scale.
Solution
Enrich your lead database by extracting profile data for each prospect. Get their current title, company, career trajectory, skills, and education to inform outreach strategy.
Result
Personalized outreach at scale. Segment prospects by seniority, industry, or skill set. Identify decision-makers faster and tailor messaging to their background and expertise.
Market Research and Competitive Intelligence
Problem
Understanding competitor teams, talent flows, and industry hiring patterns requires manually collecting data across hundreds of profiles. The data goes stale before the analysis is complete.
Solution
Extract profile data for employees at target companies. Track hiring patterns, common skill sets, team composition, and career trajectories across entire organizations.
Result
Real-time competitive intelligence. Identify which skills competitors are hiring for, where they source talent, and how their teams are structured. Spot trends before they become obvious.
Academic and Labor Market Research
Problem
Researchers studying labor markets, career mobility, or professional networks need large-scale profile data. Manual collection is impractical for studies requiring thousands of data points.
Solution
Programmatically collect structured profile data across demographics, industries, or geographies. Consistent field names and clean JSON make the data immediately usable for analysis.
Result
Datasets of thousands of profiles collected in hours, not months. Structured format integrates directly with pandas, R, or any statistical toolkit. Reproducible data collection for longitudinal studies.
How Anysite Compares
| Feature | Anysite | Proxycurl | PhantomBuster | Bright Data |
|---|---|---|---|---|
| Profile depth | Full profile with modular sections | Full profile | Basic fields only | Full profile |
| Access method | REST API, CLI, MCP | REST API | Browser automation | Proxy + parser |
| Pricing model | Pay per data section | Pay per endpoint | Pay per phantom slot | Pay per record |
| Starter cost | $49/mo (15K credits) | $49/mo (100 credits) | $69/mo (5 slots) | $500/mo minimum |
| Batch processing | Concurrent API + CLI batch | Sequential only | Queue-based | Collector-based |
| Self-healing | Yes, automatic | Manual updates | Manual phantom fixes | Partial |
| Other platforms | Google, Zillow, Amazon, and more | LinkedIn only | Multiple | Multiple |
| MCP integration | Yes, native | No | No | No |
| Data pipelines | API + CLI + Make + Clay | API only | Built-in CRM sync | API + webhooks |
Pay for the Data Depth You Need
| Profile Type | Credits | Cost at Starter ($49/15K) | Cost at Growth ($200/100K) |
|---|---|---|---|
| Basic profile | 1 | $0.0033 | $0.0020 |
| Profile + experience | 2 | $0.0065 | $0.0040 |
| Profile + exp + edu + skills | 4 | $0.013 | $0.008 |
| Full profile (all sections) | 9 | $0.029 | $0.018 |
Cost Examples by Volume
| Volume | Basic Profiles | Full Profiles |
|---|---|---|
| 1,000 profiles | $3.30 (Starter) | $29 (Starter) |
| 10,000 profiles | $20 (Growth) | $180 (Growth) |
| 50,000 profiles | $100 (Growth) | $900 (Scale) |
Frequently Asked Questions
Related Endpoints
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