LinkedIn Profile Scraper

What does LinkedIn Profile Scraper do?

LinkedIn Profile Scraper reads the public, logged-out page of each LinkedIn profile you give it and returns one structured dataset row per unique profile. You provide /in/ profile URLs or bare public identifiers such as satyanadella, and the Actor returns the name, headline, location, about text, current positions, experience, education, follower count, recent posts and the "People also viewed" links that the page exposes.

The Actor needs no LinkedIn account, no cookies and no session token. It only requests the profile pages you list. It does not use LinkedIn search, it does not crawl company pages, and it does not open the suggested profiles it finds; those URLs are returned as output values only. Duplicate identifiers in your input are fetched once. Country sub-domains, query strings and trailing slashes are normalised to https://www.linkedin.com/in/<identifier>.

Typical uses include enriching a CRM list with headlines and current employers, checking that a list of speaker or candidate profiles is still public, building lead lists from profiles you already know, and collecting public professional background for research. This Actor is independent and has no affiliation with LinkedIn.

Two things are worth knowing before you start:

• Hidden or missing profiles. Some profiles return HTTP 999 on every attempt, usually because they are hidden from logged-out visitors or do not exist. After the retries run out, the Actor pushes a row with error: "not_public_or_blocked" (or "not_found") and does not charge for it. If no profile at all can be extracted, the run fails with an explanation.
• Limited profiles. LinkedIn sometimes serves a reduced public page with masked values. Those rows are flagged with isLimitedProfile: true. The Actor never tries to reveal masked values.

What data can you get?

Each row contains the fields below. Scalar fields that the page does not expose are null, and list fields that are unavailable are empty arrays.

Field	Type	Description
id	string	Stable public identifier, the same as publicIdentifier.
sourceUrl	string	The profile page that was requested.
url	string	Normalised public profile URL.
publicIdentifier	string	The identifier from the /in/ URL.
fullName	string	Name shown on the public profile.
headline	string	Headline under the name.
location	string	Location text shown on the profile.
countryCode	string	Country code from structured profile data, when present.
about	string	Summary or about text.
profilePictureUrl	string	Public profile picture URL.
followers	integer	Follower count when shown.
connections	string	Connection count text such as 500+.
badges	string	Short badge or descriptor text, when present.
currentPositions	array	Current employers with company, company URL, location and start date.
jobTitles	array	Job titles listed in structured data.
experience	array	Past and present roles with title, company, dates, location and description.
education	array	Schools with degree text and dates.
pastOrganizations	array	Organisations the person is an alumnus of.
languages	array	Languages listed.
awards	array	Awards listed.
websites	array	External websites listed on the profile.
recentPosts	array	Recent posts found in the page's structured data.
articles	array	Articles found in the page's structured data.
alsoViewed	array	Profile URLs shown in "People also viewed".
isLimitedProfile	boolean	True when the page contained masked values.
enrichment	object	Present only when enrich is true, see below.
error	string	Present only on rows that could not be extracted.
scrapedAt	string	ISO timestamp of the extraction.

Optional enrichment. With enrich: true, each extracted row gets an enrichment object with seniority, department, firstName, lastName, currentCompanySlug and totalYearsExperience. These are computed by rules from the fields above, with no extra requests. Enrichment does not use any AI service and sends no profile data to a third party.

How to use LinkedIn Profile Scraper

1. Open the Actor in Apify Console and go to the Input tab.
2. Paste one or more LinkedIn profile URLs or public identifiers into Profile URLs or identifiers.
3. Set Maximum profiles to the number of rows you want.
4. Leave the proxy setting on Apify residential proxy. LinkedIn commonly answers datacenter addresses with HTTP 999.
5. Turn on Derive enrichment if you want the extra enrichment object; it costs extra per result.
6. Click Start. When the run finishes, open the Output tab to view, filter and download the dataset as JSON, CSV, Excel or HTML.

The Actor keeps a modest pace: it waits at least one second between requests and retries with exponential backoff and a fresh proxy session when it sees HTTP 999, 429 or a server error.

Input

Field	Type	Description
profileUrls	array of strings	Public profile URLs or identifiers to extract. Must be a non-empty list, otherwise the run fails with a clear message.
maxItems	integer	Maximum number of unique profile rows to return, 1-1000, default 50. Hidden or blocked profiles count towards this limit.
includePosts	boolean	Include recent posts and articles found in the page's structured data. Default true.
includeSimilarProfiles	boolean	Include the "People also viewed" profile URLs in alsoViewed. They are not crawled. Default true.
enrich	boolean	Derive seniority, department, name parts, company slug and years of experience (rule-based, no AI). Costs extra per result. Default false.
maxRetries	integer	Retries for HTTP 999, 429 and server errors, 0 to 10. Default 4.
proxyConfiguration	object	Apify Proxy settings. Residential proxy is the default.

{
    "profileUrls": ["https://www.linkedin.com/in/satyanadella", "williamhgates"],
    "maxItems": 2,
    "includePosts": true,
    "includeSimilarProfiles": true,
    "enrich": false
}

Output

This is a real row from a run on linkedin.com/in/satyanadella (lists shortened):

{
    "id": "satyanadella",
    "sourceUrl": "https://www.linkedin.com/in/satyanadella",
    "url": "https://www.linkedin.com/in/satyanadella",
    "publicIdentifier": "satyanadella",
    "fullName": "Satya Nadella",
    "headline": "Chairman and CEO at Microsoft",
    "location": "Redmond, Washington, United States",
    "countryCode": "US",
    "about": "As chairman and CEO of Microsoft, I define my mission and that of my company as empowering every person and every organization on the planet to achieve more.",
    "profilePictureUrl": "https://media.licdn.com/dms/image/v2/C5603AQHHUuOSlRVA1w/profile-displayphoto-shrink_200_200/profile-displayphoto-shrink_200_200/0/1579726625398?e=2147483647&v=beta&t=Rr7WT9uBM0byOij0oT_KirejIMVE4HK4r8NGIp0zjdI",
    "followers": 12195507,
    "connections": "500+",
    "badges": "Creator, Top Voice",
    "currentPositions": [
        {
            "company": "Microsoft",
            "companyUrl": "https://www.linkedin.com/company/microsoft",
            "location": "Greater Seattle Area",
            "startDate": null
        },
        {
            "company": "University of Chicago",
            "companyUrl": "https://www.linkedin.com/school/uchicago/",
            "location": null,
            "startDate": null
        }
    ],
    "jobTitles": [
        "Chairman and CEO",
        "Member Board Of Trustees"
    ],
    "experience": [
        {
            "title": "Chairman and CEO",
            "subtitle": "Microsoft",
            "startDate": "Feb 2014",
            "endDate": "Present",
            "duration": "12 years 8 months",
            "location": "Greater Seattle Area",
            "description": null,
            "companyUrl": "https://www.linkedin.com/company/microsoft"
        },
        {
            "title": "Member Board Of Trustees",
            "subtitle": "University of Chicago",
            "startDate": "2018",
            "endDate": "Present",
            "duration": "8 years",
            "location": null,
            "description": null,
            "companyUrl": "https://www.linkedin.com/school/uchicago/"
        }
    ],
    "education": [
        {
            "title": "The University of Chicago Booth School of Business",
            "subtitle": null,
            "startDate": "1994",
            "endDate": "1996",
            "companyUrl": "https://www.linkedin.com/school/universityofchicagoboothschoolofbusiness/"
        },
        {
            "title": "Manipal Institute of Technology, Manipal",
            "subtitle": "Bachelor’s Degree Electrical Engineering",
            "startDate": null,
            "endDate": null,
            "companyUrl": "https://www.linkedin.com/school/manipal-institute-of-technology/"
        }
    ],
    "pastOrganizations": [
        {
            "name": "Starbucks",
            "url": "https://www.linkedin.com/company/starbucks",
            "type": "Organization",
            "startDate": null,
            "endDate": null
        },
        {
            "name": "The Business Council U.S.",
            "url": "https://www.linkedin.com/company/the-business-council-us",
            "type": "Organization",
            "startDate": null,
            "endDate": null
        }
    ],
    "languages": [],
    "awards": [],
    "websites": [
        "https://snscratchpad.com/"
    ],
    "recentPosts": [
        {
            "url": "https://www.linkedin.com/posts/satyanadella_the-motivation-behind-the-new-copilot-intelligence-activity-7509276499837902849-DFP-",
            "text": "The motivation behind the new Copilot: intelligence is accelerating fast. Now we need to diffuse it everywhere.",
            "datePublished": "2026-09-25T15:43:53.171Z",
            "likes": 922
        }
    ],
    "articles": [
        {
            "url": "https://www.linkedin.com/pulse/how-do-we-build-frontier-intelligence-ecosystem-satya-nadella-73jhc",
            "headline": "How do we build a frontier intelligence ecosystem?",
            "datePublished": "2026-06-02T19:41:31.000+00:00",
            "likes": 2538
        }
    ],
    "alsoViewed": [
        "https://www.linkedin.com/in/tony-bates-679227a5",
        "https://www.linkedin.com/in/charlesphillips1"
    ],
    "isLimitedProfile": false,
    "scrapedAt": "2026-09-30T18:09:57.142Z"
}

Rows for experience take location only from the location line of each card and use null when the card has none. Company and school URLs are returned without tracking parameters.

A profile that is hidden or missing produces a short row like this (illustrative), and it is not charged:

{
    "id": "example-person",
    "sourceUrl": "https://www.linkedin.com/in/example-person",
    "url": "https://www.linkedin.com/in/example-person",
    "publicIdentifier": "example-person",
    "fullName": null,
    "isLimitedProfile": false,
    "scrapedAt": "2025-01-15T12:00:00.000Z",
    "error": "not_public_or_blocked"
}

The dataset has an overview view with the most useful columns, and you can export it in any format Apify supports.

How much does it cost to scrape LinkedIn profiles?

The Actor uses pay-per-event pricing. The result event is charged once for each extracted profile row, whether it is a full or a limited profile. The enriched-result event is charged once for each row that gets an enrichment object, only when enrich is true. Rows with an error are never charged. See the Pricing tab for current rates. Platform usage such as proxy traffic and compute is shown in your run's cost summary.

Use with the API

You can start the Actor from code with the Apify API clients or plain HTTP.

Python

import os

from apify_client import ApifyClient

client = ApifyClient(os.environ["APIFY_TOKEN"])
run = client.actor("axiomworks/linkedin-profile-scraper").call(
    run_input={"profileUrls": ["satyanadella"], "maxItems": 1}
)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["fullName"], item["headline"])

JavaScript

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('axiomworks/linkedin-profile-scraper').call({
    profileUrls: ['satyanadella'],
    maxItems: 1,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
process.stdout.write(JSON.stringify(items, null, 2));

cURL

curl -X POST "https://api.apify.com/v2/acts/axiomworks~linkedin-profile-scraper/run-sync-get-dataset-items" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"profileUrls": ["satyanadella"], "maxItems": 1}'

You can also schedule runs, send results to Google Sheets, or connect the Actor to Zapier, Make and webhooks with Apify integrations.

Use with AI agents (MCP)

You can call this Actor from any MCP client through the Apify MCP server. Add this to your client configuration:

{
    "mcpServers": {
        "apify": {
            "url": "https://mcp.apify.com?tools=axiomworks/linkedin-profile-scraper"
        }
    }
}

Example prompts:

• "Get the headline, location and current company for linkedin.com/in/satyanadella."
• "Extract these five public LinkedIn profiles and tell me which ones list an education entry."
• "Scrape this profile with enrichment on and report the seniority and department."

FAQ

Does this need a LinkedIn account? No. It requests publicly visible pages without login or cookies, and it cannot see anything that requires a login.

Why is a field empty? LinkedIn may serve a limited public profile, omit that field, or change its page markup. The Actor does not reveal masked values.

Why did a profile return an error row? HTTP 999 on every attempt usually means the profile is hidden from logged-out visitors or does not exist. Raising maxRetries rarely helps for hidden profiles. Confirm the URL opens in a private browser window.

Does it fetch company pages or the suggested profiles? No. Company and suggested profile URLs are returned as values only.

Can I search by keyword or company? No. The Actor takes profile URLs or identifiers that you already have.

How many profiles can I run at once? Profiles are fetched one after another at a polite pace, so large lists take longer. Split very large lists across several runs.

Does enrichment use AI? No. It uses fixed rules on the extracted fields and makes no extra requests.

Is it legal to scrape LinkedIn?

This Actor only reads information that LinkedIn shows to anyone without logging in, and it does not bypass logins or CAPTCHAs. Data about people can still be personal data. Use it for a legitimate purpose, follow the privacy law that applies to you, such as GDPR, and check LinkedIn's terms of service and your own legal requirements before you rely on the results. This is general information and not legal advice.

Feedback

If a field is empty when the profile page clearly shows it, or you want another field added, open an issue from the Actor's Issues tab and include the profile URL and the run ID.