The safest way to get LinkedIn data in 2026 is to collect public company, product, and showcase pages through a structured API — and to stay away from personal profiles and anything behind a login. LinkedIn is one of the most aggressively defended sites on the web and its terms prohibit automated access, so the legal and practical bar is higher than for most sources. This guide covers what is realistic to collect, where the legal lines are, and how to do it with a documented API.
Start with the legal reality
LinkedIn scraping is legally sensitive, so lead with the constraints:
- hiQ v. LinkedIn: US courts held that scraping public data is not a Computer Fraud and Abuse Act violation — but the litigation was long and costly, and LinkedIn's terms still prohibit automated access. Public access is not the same as permission.
- Personal data is high-risk. Profiles contain personal data governed by GDPR and CCPA; collecting it invites privacy claims. Avoid it.
- Terms and account bans. Logged-in or rate-abusing scraping gets accounts banned and can draw cease-and-desist letters.
Rule of thumb: stick to public, non-personal, company-level data, respect rate limits, and review LinkedIn's terms and your own compliance obligations. This is not legal advice.
What Crawlora's LinkedIn API covers
Crawlora's LinkedIn API is deliberately scoped to public company-level pages, not personal profiles:
- Company pages — see
/docs/linkedin/linkedin-company - Product pages
- Showcase pages
That scoping is intentional: company, product, and showcase data is lower-risk public business information — useful for B2B enrichment without touching personal profiles.
Example: fetch a public company page
curl https://api.crawlora.net/api/v1/linkedin/company/COMPANY_ID \
-H "x-api-key: $CRAWLORA_API_KEY"
The same call in Python:
import requests
resp = requests.get(
"https://api.crawlora.net/api/v1/linkedin/company/COMPANY_ID",
headers={"x-api-key": "YOUR_API_KEY"},
)
company = resp.json()["data"]
print(company.get("name"), company.get("industry"))
The response is normalized JSON (fields shown are illustrative — check the docs for the current schema):
{
"code": 200,
"msg": "OK",
"data": {
"name": "Example Co",
"industry": "Software",
"website": "https://example.com",
"employee_range": "201-500",
"headquarters": "Austin, TX"
}
}
Why DIY LinkedIn scraping is painful
- Aggressive anti-bot — fingerprinting, behavioral detection, and rate-based bans.
- Login walls — most profile data sits behind authentication, and collecting it crosses both terms and privacy lines.
- Account risk — bans and cease-and-desist letters are real outcomes.
A structured company-data API sidesteps the riskiest parts by scoping to public company pages and handling fetching behind the endpoint — but you remain responsible for lawful, compliant use.
Where this fits
Public company data powers B2B workflows — see the lead generation use case for building local and B2B lead lists from public business and company data (a data layer you collect and enrich, not a contact database).
FAQ
Is scraping LinkedIn legal? Accessing public data is lower-risk in the US after hiQ, but LinkedIn's terms still prohibit automated access, and personal data carries privacy risk. Treat company-level public data as the safe zone and get legal advice for anything more.
Can I scrape personal profiles? Crawlora's LinkedIn endpoints are for public company, product, and showcase pages — not personal profiles. Avoid collecting personal data.
What LinkedIn data can I collect? Public company, product, and showcase fields such as name, industry, website, size range, and location, where available.
Will my account get banned? For supported public company pages, Crawlora handles fetching behind the API, so you are not running a logged-in scraper — but you are responsible for compliant use.
Is this the official LinkedIn API? No. It extracts public LinkedIn company data and is independent of LinkedIn's official APIs.
Start collecting
Test the company endpoint in the Playground, check the schema in the API docs, and review credit costs on pricing. For the bigger picture, see how to choose a web scraping API and how to scrape Google Maps.