LinkedIn Company Scraper: company details, search, offices and recent posts, no login

Turn LinkedIn company pages, company names, websites or a keyword search into a clean table: name, website, industry, company size, exact employee count on LinkedIn, followers, founded year, specialties, headquarters and every office address, logo and cover image, plus the most recent posts with dates, reactions and comments, the number of open jobs, and the similar and affiliated pages LinkedIn shows. No LinkedIn account, login or cookies needed. Export to Excel, CSV or JSON, or read it through the API.

$1 per 1,000 companies from page URLs, names, websites and keyword searches; companies from searches narrowed by location, industry or size $2 per 1,000. Recent posts included, no start fee, platform usage and proxies included.

Four ways to pick companies

Input	Example	What you get
LinkedIn company pages	https://www.linkedin.com/company/stripe, stripe, 2135371	that company
Company names or websites	Revolut, Česká spořitelna, stripe.com	the best-matching company page for each line
Search companies by keywords	fintech, digital marketing agency	companies whose name, tagline, description, specialties, industry or address contain the words
Filters for searches	Locations Germany, Industries Software Development or LinkedIn industry IDs, Company size 11-50	only companies that pass every filter are saved and charged

All four can be combined in one run. The same company reached twice is saved and charged once.

What you get

Field	Example
id, universalName, linkedinUrl, pageType	2135371, stripe, https://www.linkedin.com/company/stripe, COMPANY or SHOWCASE
name, tagline, description	Stripe, Help increase the GDP of the internet., the full About text
website, industries, companyType	https://stripe.com, ["Technology, Information and Internet"], Privately Held
companySize, employeeCountRange, employeeCount	5,001-10,000 employees, {"start": 5001, "end": 10000}, 16722 members on LinkedIn
followerCount, foundedOn, specialities	1703831, {"year": 2010}, ["Payments", ...]
headquarter	{"line1": "354 Oyster Point Blvd", "city": "South San Francisco", "geographicArea": "California", "postalCode": "94080", "country": "US", "parsed": {"text": "South San Francisco, California, United States", "countryCode": "US", "country": "United States", "state": "California", ...}}
locations	every office listed on the page, same shape, headquarter: true on the main one (Siemens: 100 offices)
logo, logos, backgroundCover, backgroundCovers	image URLs with width, height and expiry
jobSearchUrl	the company's jobs on LinkedIn
openJobCount, openJobCountText	jobs the company lists on LinkedIn worldwide at the time of the run: 983 / "983"; above 1,000 LinkedIn rounds down and adds a plus, 2000 / "2,000+"
posts	recent posts the company published: url, exact postedAt, postedAgo, text, reactionCount, commentCount, images, hasVideo, link preview article, shared post repost
similarOrganizations, affiliatedOrganizations	related pages with name, URL, industry and location
input, scrapedAt	the page, name, website or search the record came from, time of scraping

Field names follow the most used LinkedIn company Actors (universalName, tagline, employeeCountRange, foundedOn, specialities, headquarter, locations with parsed, logos), so an existing integration keeps working.

How to use it

1. Fill one or more of LinkedIn company pages, Company names or websites and Search companies by keywords, one entry per line. Company pages accept https://www.linkedin.com/company/stripe, showcase pages, subpages such as /about or /posts, country addresses like de.linkedin.com/company/..., Sales Navigator company links, the page name alone (stripe) and numeric company IDs (2135371).
2. For searches, add Locations, Industries and Company size if you want, and set Max companies per search.
3. Keep Include recent posts and Include open jobs count on (both free) or switch them off for a smaller, faster dataset.
4. Click Start. Companies arrive in the dataset as they are scraped.

Example input:

{
  "companies": ["https://www.linkedin.com/company/stripe", "netflix", "2135371"],
  "searches": ["Revolut", "shopify.com"],
  "searchQueries": ["fintech"],
  "locations": ["Germany"],
  "companySize": ["11-50", "51-200"],
  "maxResults": 50,
  "includePosts": true
}

Output (shortened):

{
  "id": "2135371",
  "universalName": "stripe",
  "linkedinUrl": "https://www.linkedin.com/company/stripe",
  "pageType": "COMPANY",
  "name": "Stripe",
  "tagline": "Help increase the GDP of the internet.",
  "website": "https://stripe.com",
  "industries": ["Technology, Information and Internet"],
  "companyType": "Privately Held",
  "companySize": "5,001-10,000 employees",
  "employeeCount": 16722,
  "employeeCountRange": { "start": 5001, "end": 10000 },
  "followerCount": 1703831,
  "openJobCount": 983,
  "foundedOn": { "year": 2010 },
  "headquarter": { "line1": "354 Oyster Point Blvd", "city": "South San Francisco", "geographicArea": "California", "postalCode": "94080", "country": "US", "headquarter": true },
  "locations": [{ "line1": "1 Wilton Park, Wilton Terrace", "city": "Dublin", "geographicArea": "County Dublin", "postalCode": "D02 FX04", "country": "IE", "headquarter": false }],
  "posts": [{
    "url": "https://www.linkedin.com/feed/update/urn:li:activity:7504308642557345792/",
    "postedAt": "2026-09-11T22:43:23Z",
    "postedAgo": "3d",
    "text": "Latest from Stripe Economics: ...",
    "reactionCount": 158,
    "commentCount": 34,
    "images": ["https://media.licdn.com/dms/image/..."],
    "hasVideo": false
  }],
  "similarOrganizations": [{ "name": "Atlassian", "linkedinUrl": "https://www.linkedin.com/company/atlassian", "industry": "Software Development", "location": "Sydney, NSW" }],
  "input": "https://www.linkedin.com/company/stripe"
}

Use cases

• Lead lists: search marketing agency in London with 11-50 employees and get a table of company pages with websites, sizes and addresses.
• CRM enrichment: paste company names or websites from a CRM and add LinkedIn size, industry, headquarters and employee count.
• Account research and sales: see what a company posted this week before the call, and which pages LinkedIn considers similar.
• Market maps: size bands, founding years and office countries for a set of competitors in one table.
• Data teams and AI agents: a structured company profile from a single URL, name or website.

Use it from code, n8n, Make, Zapier or an AI agent

• API: POST https://api.apify.com/v2/acts/alfalfa~linkedin-company-scraper/run-sync-get-dataset-items?token=… with the JSON input above returns the companies directly (runs up to 5 minutes). Longer jobs: start the run, poll, read the dataset. Any Apify client library works.
• n8n, Make, Zapier: add the Apify node, pick alfalfa/linkedin-company-scraper, paste the same JSON input and read the run's dataset in the next step. See the Apify integrations docs.
• AI agents and MCP (Claude, Cursor, VS Code, ChatGPT): connect the Apify MCP server with this Actor as a tool, https://mcp.apify.com/?tools=alfalfa/linkedin-company-scraper, and the agent can look up any company. See Apify MCP docs.

Pricing

Event	Free plan	Starter	Scale	Business and higher
Company	$1.00 / 1,000	$0.90	$0.80	$0.70
Filtered search result: extra for a company found by a search with a location, industry or size filter	+$1.00 / 1,000	+$0.90	+$0.80	+$0.70
Searches without filters, name and website lookup, recent posts, open jobs count, locations, similar pages, start fee, platform usage, proxies	included

A filtered search checks many company pages to find the few that pass every filter; only the companies that pass are charged, so a company from a filtered search costs $2.00 per 1,000 on the Free plan and $1.40 on Business.

A run's Maximum total charge is honoured: the Actor stops before the budget is used up, so the bill never exceeds it. Companies that cannot be found, that do not pass the search filters, or that were already saved in the run are not charged.

Limits and honesty

• The data is what LinkedIn shows on the public company page to a visitor who is not logged in. Employee lists, funding data, phone numbers and the full post history are shown only to logged-in members and are not included. The Actor does not collect data about individual people: posts shared from personal profiles keep their text but not the person's name or profile link.
• A keyword search returns up to several hundred companies per search line. For a larger list, split the search by location, industry or wording.
• A search whose filters are very narrow (a niche keyword in one small city, say) stops early when hardly any of the companies it checks pass them, so it can save fewer companies than Max companies per search. Broader filters or other words find more.
• employeeCount is the number of LinkedIn members who list the company as their employer; companySize is the band the company chose. They often differ.
• LinkedIn shows the most recent posts on the public page, usually up to 10. For more posts, run the Actor on a schedule and keep the new ones.
• Numeric company IDs are not shown publicly on LinkedIn, so some cannot be matched to a page; use the page URL or the company name then. School pages need a login and are skipped.
• A company name returns the best match: the company with exactly that name (the most followed one when several share it), otherwise the first company LinkedIn suggests for the name. Check name and linkedinUrl when the name is common. A page name that LinkedIn has reassigned leads to the company that holds it now.
• Locations match the headquarters or any office. Two-letter codes are countries (CA is Canada, type California for the state); a country name such as Georgia also matches a state of that name. A city name alone matches that city in any country (London in the UK and in Canada); add the country or state to narrow it: London, UK, Austin, TX.
• A website returns the company's own LinkedIn page: the page the company points to from its website, or the page that lists the website on LinkedIn. Renamed brands (an old domain that now redirects to the new one) are followed to the new page. Well-known brands that list a campaign, careers or short link instead are matched by their brand name when their main page is clearly the best known one with that name; otherwise the website is reported as not found rather than guessed.
• openJobCount is LinkedIn's worldwide count of the company's open jobs at the time of the run. Above 1,000 LinkedIn rounds down and adds a plus (2,000+): openJobCount then holds the lower bound and openJobCountText the figure as shown. Switch Include open jobs count off to skip it.
• Links to profiles on other sites (Instagram, Facebook, Linktree ...) and placeholder addresses such as example.com are not company websites and are skipped.

FAQ

Do I need a LinkedIn account or cookies? No. Nothing is logged in and your own account is never at risk.

Can I search companies by keyword, location, industry and size? Yes. Put the keywords in Search companies by keywords and choose the filters; every saved company passes all of them. Industries can be names or LinkedIn industry IDs (the numbers other LinkedIn tools use).

Can I find a company from its website or name? Yes, one per line in Company names or websites. A website leads to the company's own LinkedIn page, also when the brand has been renamed; a brand's regional or careers page gives way to its main page.

Does it include open jobs? Yes. openJobCount is the number of jobs the company lists on LinkedIn worldwide at the time of the run, at no extra charge. For the jobs themselves use the LinkedIn Jobs Scraper.

Can I scrape company employees? No. LinkedIn shows employee lists only after a login, and this Actor does not collect data about people. employeeCount gives the headcount on LinkedIn.

How fast is it? About 20 companies in 10 to 50 seconds with the default concurrency; a search with 50 results takes one to two minutes.

Is it legal? The Actor reads public company pages without an account and stores only what those pages show. Check your local rules for how you use business data.

Related Actors by the same author

Actor	What it does	Price
LinkedIn Jobs Scraper	public LinkedIn job postings by keyword, location, date, company or URL	$0.50 per 1,000 jobs
Google Maps Scraper	places from any search and location with address, phone, website, rating and hours, plus reviews and website emails	$0.07 per 1,000 places
Amazon Product Scraper	products from searches, Best Sellers lists and ASINs in 22 Amazon stores with price, rating, BSR and details	$0.28 per 1,000 products
Google Ads Transparency Scraper	every ad of an advertiser or website domain with format, dates, regions, previews, YouTube ids	$0.50 per 1,000 ads
YouTube Scraper	videos of a search, channel, playlist or URL list with views, likes, date, tags, plus transcripts and comments	$0.50 per 1,000 rows
Facebook Ads Library Scraper	ads from the Meta Ad Library by keyword, advertiser page or URL	$0.50 per 1,000 ads
Facebook Pages Scraper	page details with email, phone, address, followers, rating, About text	from $3.50 per 1,000 pages
Facebook Posts Scraper	posts of any public page or profile with reactions, comment counts, media	$2 per 1,000 posts
Facebook Comments Scraper	comments and replies of any public post	$0.50 per 1,000 comments
Facebook Events Scraper	events by search, page or URL with dates, venue, tickets and organizer email	$5 per 1,000 events

Not affiliated with, endorsed by or connected to LinkedIn Corporation, Microsoft or Apify.