LinkedIn Profile Scraper — Full Career History, No Cookies avatar

LinkedIn Profile Scraper — Full Career History, No Cookies

Pricing

from $2.56 / 1,000 profile founds

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LinkedIn Profile Scraper — Full Career History, No Cookies

LinkedIn Profile Scraper — Full Career History, No Cookies

LinkedIn profile scraper alternative with no cookies. Profile URLs in, the complete career record out — every position with dates and descriptions, education, skills, certifications. $3.20 per 1,000 found (the most used profile scraper: $4); with emails & phones $8 (theirs: $10). Misses free.

Pricing

from $2.56 / 1,000 profile founds

Rating

5.0

(1)

Developer

B2B Enrich Search

B2B Enrich Search

Maintained by Community

Actor stats

0

Bookmarked

25

Total users

19

Monthly active users

6 days ago

Last modified

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$3.20 per 1,000 complete profiles. Not found costs $0. The standard row is the whole career record: every position with dates and descriptions, education, skills, certifications, patents and publications. Emails and phones are an opt-in tier at $8 per 1,000 people who have one that works.

Turn LinkedIn profile URLs into structured data. Paste links, bare handles or mobile URLs and get one row per profile, with the profile link, location and current employer in their own columns for spreadsheets.

This is a database lookup, not a live scrape: answers come back in seconds from a database of 800M+ professional profiles. No cookies, no login, no account risk.

Why this one

  1. The complete record at the standard price. Every position with its description, the whole education list, skills, languages, certifications, patents, publications, articles.
  2. You pay only for found. Unmatched URLs are free not_found rows, removed profiles free profile_removed rows.
  3. Contacts priced by whether they work. With contacts on you pay $8 per 1,000 only for people with a personal mailbox, an address at their current employer, a phone or an X, Facebook or GitHub link. An old work address alone is charged as a plain profile.

Who is this for

  • Sales and GTM teams enriching sign-ups and CRM contacts.
  • Recruiters turning sourced profile links into structured candidate data.
  • Data teams feeding scoring models with career histories.

Input

{
"profileUrls": ["satyanadella", "https://www.linkedin.com/in/williamhgates"],
"contacts": false,
"mustHave": []
}

Links, bare handles and mobile URLs all work; spellings of the same profile are looked up once.

Emails and phones: contacts

Turn on contacts to get the recorded email addresses and phone numbers with each profile. The best address and a phone are lifted into their own columns: email, emailType (work / personal), employerMatch, workEmails, personalEmails, emailCount, phone, phones.

You pay the contacts price, $8 per 1,000, only for a person with a contact that reaches them today:

  • a personal mailbox (gmail, outlook, ISP mail);
  • an address on the domain of their current employer;
  • a phone number not flagged as a company switchboard;
  • an X, Facebook or GitHub link (other than one you looked the person up by).

Everyone else is delivered at the $3.20 profile price, old work addresses included. The _tier column says which price each row was charged at. X, Facebook and GitHub links ship only with contacts; the profile alone carries the professional profile URL and website.

How often that is, measured on 30 September 2026 over 200 employed professionals per country: the contacts price applied to 53% of people in the US, 42% in India, 40% in France, 33% in the UK and 32% in Germany. Everyone else shipped at the lower price.

Only people who have what you need: mustHave

List what a person must have for you to pay: email, personalEmail, workEmail, currentWorkEmail, phone, github, twitter, facebook. A person who is found but lacks one comes back as a free missing_required row that says what was missing (and names nobody). The email, phone and social requirements need contacts on, and a run that asks for them without it is refused before anything is charged.

Output

One row per profile, aligned with your list. A real row:

{
"_status": "found",
"_input": { "profile": "satyanadella" },
"_freshness": "fresh_90d",
"profileUrl": "https://www.linkedin.com/in/satyanadella",
"location": "Redmond, Washington, United States",
"countryCode": "us",
"companyName": "Microsoft",
"companySlug": "microsoft",
"_view": "lite-v4",
"slug": "satyanadella",
"fullName": "Satya Nadella",
"headline": "Chairman and CEO at Microsoft",
"jobTitle": "Chairman and CEO",
"industry": "Software Development",
"connectionsCount": 500,
"seniority": { "totalExperienceYears": 12, "currentTenureYears": 12, "averageTenureYears": 7 },
"experience": {
"work": [
{ "title": "Chairman and CEO", "company": "Microsoft", "startDate": "2014-02-01", "endDate": null },
{ "title": "Member Board Of Trustees", "company": "University of Chicago", "startDate": "2018-01-01", "endDate": null }
]
},
"education": [
{ "school": "University of Wisconsin-Milwaukee", "degreeName": "Master’s Degree", "fieldOfStudy": "Computer Science" }
],
"contactInformation": {
"socialLinks": { "profileUrl": "https://www.linkedin.com/in/satyanadella", "twitterUrl": null, "githubUrl": null }
}
}

(trimmed for display: the row also carries every past position with its description, about, skills, languages, certifications, patents, publications and articles whenever the profile has them)

With contacts on, the same kind of row gains the contact columns (values below are made up):

{
"_status": "found",
"_tier": "contacts",
"fullName": "Jane Doe",
"companyName": "Acme",
"profileUrl": "https://www.linkedin.com/in/jane-doe-example",
"email": "jane.doe@acme.example",
"emailType": "work",
"employerMatch": true,
"workEmails": ["jane.doe@acme.example", "jdoe@oldjob.example"],
"personalEmails": ["jane.doe@example.com"],
"emailCount": 3,
"phone": "+15550100123",
"phones": [{ "number": "+15550100123", "sharedBy": 1, "companyLine": false }]
}

When the URL matched several records the row carries _matchCandidates.

The Output tab has three views: Overview, Career & education and Contacts & signals.

Pricing

EventPriceWhen
Profile found$0.0032matched URL, the complete career record
Profile found (with contacts)$0.008contacts on and a contact that reaches the person today
Not found / removed / missing_required$0always free

Prices above are for Apify's Free and Starter plans. Scale plans pay 10% less and Business plans and up 20% less, applied by Apify automatically; the Store page quotes the lowest of these as "from".

Your free $5 Apify credit is about 1,560 complete profiles.

FAQ

How fresh is the data? Every row carries a _freshness bucket (fresh_90d, updated_1y, older) and the record's exact updatedAt.

Is there a size limit? Up to 1,000 entries per run; the Actor paces itself and finishes in minutes. For bigger lists use Bulk People Enrichment.

What happens with a wrong or dead URL? A free row with _status: "not_found" or "profile_removed" and your input echoed, so the spreadsheet stays aligned.

Use LinkedIn Profile Data by URL with AI agents and MCP

This Actor works as a tool for AI agents. Add it to Claude, ChatGPT, Cursor or any other MCP client through the Apify MCP server:

https://mcp.apify.com?tools=b2bsearch/profile-lookup
  • Fast enough for a tool call. A small request finishes in seconds, so the agent gets its answer inside one call.
  • The agent pays only for results. Prices are per result (see the pricing section above) and every miss is a free row. Cap what one call may spend with maxTotalChargeUsd.
  • Rows explain themselves. Each row has a _status; a row that is not a result says why in _error, so the agent can decide what to do next without guessing.
  • Compact rows for a context window. "compact": true returns a short row — about 2 KB for a full profile instead of 10+ KB: identity, current role, the 5 latest positions, education, top skills and any contacts. Same price; leave it off to get the complete record.

Input an agent can send as is:

{
"profileUrls": [
"satyanadella"
],
"compact": true
}

The same Actor is available as a tool in LangChain, CrewAI and the OpenAI Agents SDK, and as a step in n8n, Make and Zapier through the Apify integrations.

Which actor in this family?

One database, ten doors. Misses are free on every one of them.

ActorInput → output
Profile Lookup (this one)profile URL → full career profile
Reverse Email Lookupemail → person, profile URL and employer
Name to Profilename + company domain → profile
Social Handle LookupGitHub, X/Twitter or Facebook handle → profile
Bulk People EnrichmentCSV of emails, URLs, handles or names → profiles
LinkedIn Email Finderprofile URL → email addresses on record
Work Email Findername + company domain → work email candidates
Company Employeescompany domain → current staff
People Database Searchfilters → people
B2B Leads Finderfilters → leads with a work or personal email, from $1.50/1k
Company Database Searchfilters → companies

Free Apify plan

A run started from a free Apify plan delivers the first 100 results and stops; the run's status line says so. Any paid Apify plan lifts the cap. The rows are the same rows a paid run returns.

Feedback and reviews

How did it go? A rating in the Reviews tab of this Actor tells the next buyer what to expect; we read every word, good or bad. Got a wrong or stale row? Open the Issues tab with the run ID. Issues are public, so leave out emails, phones and names; the run ID is enough for us to find the row. We check every report, fix what is ours to fix and answer in the thread.

Disclaimer

This Actor is an independent product. It is not affiliated with, endorsed by or sponsored by LinkedIn. It does not access, crawl or scrape any of them at run time: answers come from our own database of publicly available professional data, and the network names only describe the kind of data it covers. To have a person's data removed, open an issue on this Actor with only the profile link — nothing else is needed, and it is removed from every listing.