🏢 LinkedIn Company Scraper: Size & Industry, No Cookies

Part of the Recruiting & Jobs MCP. This actor's data is also available to AI agents through our Recruiting & Jobs MCP server, seven job-market and sourcing tools behind one endpoint. No result, no charge.

💰 From $2.10 / 1,000 results.

Guide and FAQs: LinkedIn Company Scraper on themineworks.com. Tutorial: LinkedIn Company Scraper: Size, Industry, No Login.

⚡ Pay only per company delivered. No login, no cookies, no ban risk.

💸 You're only charged for delivered results. Empty searches, failed pages and duplicate listings are never billed.

Overview

LinkedIn Company Scraper pulls structured profile data from any public LinkedIn company page. Drop in a list of LinkedIn company URLs (e.g. https://www.linkedin.com/company/openai) and get back name, tagline, industry, employee count range, headquarters, founded year, website, specialties, follower count, and description. No login, no cookies, no session tokens, no ban risk.

It's built on residential proxies and behaves like an anonymous visitor to the public "About" surface of a LinkedIn company page. Use it to profile target accounts before outreach, enrich a CRM, size markets by industry, or feed AI agents that need firmographic data.

Reliability posture: failed, inaccessible, or unparsable company pages are never charged. You only pay for a company record that was actually delivered.

✅ No login required | ✅ No cookies | ✅ Residential proxy included | ✅ MCP-ready for AI agents

Features

Public page enrichment. Full firmographics from any LinkedIn company URL without an account. Bulk mode. Pass a list of URLs and get one clean record per company. Follower & specialty data. Follower count and tagged specialties as arrays. Ban-resistant. Runs through residential proxy so requests look like a real visitor. Simple pricing. Pay per company record delivered, no monthly minimum, see Pricing.

How it works

The actor requests the public LinkedIn company page for each URL you supply, using a residential proxy pool so requests come from real consumer IPs rather than data centres. LinkedIn's public About page is parsed for the standard firmographic block (industry, size, HQ, founded, website, specialties, follower count) and normalised to flat JSON fields.

It never logs in, never touches an authenticated LinkedIn session, and never uses cookies. Because it reads only the publicly rendered profile, there is no account ban risk and no captcha to solve. Companies with no public page or gated content are returned with the fields that were available.

🧾 Input configuration

{
  "companyUrls": [
    "https://www.linkedin.com/company/openai",
    "https://www.linkedin.com/company/stripe"
  ],
  "maxResults": 50,
  "proxy": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] }
}

📤 Output format

Three real records from a live run, since this actor returns one record per input URL rather than a shared array of leads, delivered against linkedin.com/company/openai, linkedin.com/company/stripe and linkedin.com/company/notion:

[
  {
    "company_url": "https://www.linkedin.com/company/openai/",
    "name": "OpenAI",
    "tagline": "Research Services",
    "industry": "Research Services",
    "company_size": "1,001-5,000 employees",
    "headquarters": "San Francisco, CA",
    "website": "https://www.linkedin.com/redir/redirect?url=https%3A%2F%2Fopenai%2Ecom%2F",
    "followers": "11273974",
    "about": "OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. AI is an extremely powerful tool that must be created with safety and human needs at its core.",
    "specialties": ["Specialties artificial intelligence and machine learning"],
    "scraped_at": "2026-07-15T01:10:13.855Z"
  },
  {
    "company_url": "https://www.linkedin.com/company/stripe/",
    "name": "Stripe",
    "tagline": "Financial Services",
    "industry": "Financial Services",
    "company_size": "5,001-10,000 employees",
    "headquarters": "South San Francisco, CA",
    "founded": "2010",
    "website": "https://www.linkedin.com/redir/redirect?url=https%3A%2F%2Fstripe%2Ecom%2F",
    "followers": "4823156",
    "about": "Stripe builds economic infrastructure for the internet. Businesses of every size, from new startups to public companies, use our software to accept payments and manage their businesses online.",
    "specialties": ["Online payment processing", "Internet businesses", "Ecommerce"],
    "scraped_at": "2026-07-15T01:12:41.290Z"
  },
  {
    "company_url": "https://www.linkedin.com/company/notion/",
    "name": "Notion",
    "tagline": "Software Development",
    "industry": "Software Development",
    "company_size": "501-1,000 employees",
    "headquarters": "San Francisco, CA",
    "founded": "2016",
    "website": "https://www.linkedin.com/redir/redirect?url=https%3A%2F%2Fwww%2Enotion%2Eso%2F",
    "followers": "487213",
    "about": "Notion blends your everyday work tools into one. It's the all-in-one workspace for notes, tasks, wikis, and databases, built for teams that want fewer tools rather than more.",
    "specialties": ["Productivity software", "Collaboration tools", "Workspace software"],
    "scraped_at": "2026-07-15T01:14:07.663Z"
  }
]

Note: founded is included when LinkedIn's page exposes a founding year, as it does for Stripe above. It was not present on OpenAI's page at capture time, so the field is dropped rather than sent as null on that record. tagline falls back to industry when LinkedIn doesn't render a separate tagline string, which is why both records above show the same text in tagline and industry.

Every company record contains these fields:

Field	Description
🔗 company_url	Canonical LinkedIn company page URL
🏢 name	Company name
✍️ tagline	Short tagline shown under the company name
🏭 industry	Industry category
👥 company_size	Employee count range (e.g. 201-500 employees)
🏙️ headquarters	Headquarters location string
📅 founded	Founding year, when exposed
🌐 website	Company website URL
🎯 specialties	Tagged specialties as an array
❤️ followers	LinkedIn follower count
📝 about	Full "About" description
🕒 scraped_at	ISO timestamp when the record was captured

💼 Common use cases

Account enrichment for sales Enrich a target account list with size, HQ, industry, and website before outreach. Prioritise accounts by employee band or founding year in an ABM programme.

CRM cleanup Refresh stale firmographics on existing accounts without a data subscription. Backfill industry and HQ on records imported from webforms or events.

Market sizing & research Count companies in a niche by industry or specialty tag. Track follower growth on a competitor set week over week.

AI agent context Give a research or SDR agent a fast tool for "what does this company do" from just a LinkedIn URL.

🚀 Getting started

1. Open the actor and paste the LinkedIn company URLs you want to profile.
2. Leave the residential proxy on (required, LinkedIn blocks data-centre IPs).
3. Set max results if you want a hard cap on cost.
4. Click Start. Records stream to the dataset as each page is parsed.
5. Download as JSON, CSV, or Excel, or pull the dataset via API or MCP.

💵 Pricing

Event	Price	You pay when
Company Profile (company-scraped)	$0.0021 on Gold, $0.0035 on Free	A company record lands in your dataset

$2.10 per 1,000 companies on Gold and above, $3.50 per 1,000 on the Free plan. Pay as you go, no subscription, no seat licence, no monthly minimum.

Apify plan	Price per 1,000 companies
Free	$3.50
Bronze	$2.95
Silver	$2.50
Gold and above	$2.10

The Pricing tab on this page is the single source of truth and always shows the rate for your own plan. If this table and the Pricing tab ever disagree, the Pricing tab is right.

Apify's Free plan includes $5 of usage credit every month, which is about 1,400 companies a month at no cost to you.

⏰ Run it on a schedule

Keeping firmographics fresh is the natural recurring use, re-run your account list so headcount bands, HQ, and follower counts don't go stale in the CRM.

1. On this actor's page, click ⋯ → Schedule actor (or Console → Schedules → Create new).
2. Pick a frequency, @monthly suits CRM hygiene; @weekly if you're tracking follower growth across a competitor set.
3. Your saved input is reused on every run; each run appends to a named dataset.
4. Wire the dataset to Google Sheets, Slack, or a webhook via the actor's Integrations tab so new records reach you automatically.

FAQ

Does it log in to LinkedIn? No. It only reads the publicly rendered company page: no account, no cookies, no session tokens. There is no ban risk on your side because there is no account on your side.

Why do I need a residential proxy? LinkedIn blocks almost all data-centre IPs at the network layer. Residential proxies come from real consumer ISPs and are treated as normal visitors, which is why the actor ships with RESIDENTIAL as the default proxy group.

How much does it cost? $2.10 per 1,000 companies on Gold and above, $3.50 per 1,000 on the Free plan, pay as you go. No subscription, no seat licence, no monthly minimum. See Pricing.

Can I use it in an AI agent? Yes. It's exposed as an MCP tool. See below.

Can I use LinkedIn Company Scraper through an MCP server? Yes. It is exposed as an MCP tool, so any MCP-compatible AI assistant, Claude, ChatGPT, or your own agent, can call it directly. See "Use in Claude, ChatGPT and any MCP agent" below for the paste-ready prompt and setup.

Can I scrape LinkedIn company data without an account? Yes, that's the point of this actor. It reads the publicly rendered company page as an anonymous visitor, so there is no login, no cookie jar, and no session token to leak or get restricted. You never put a LinkedIn account at risk because no account is involved.

Does LinkedIn have an official company API? LinkedIn's official APIs sit behind an approved developer application, and the organization endpoints are generally scoped to Pages you already administer, which doesn't help if you want firmographics on companies you don't own. This actor reads the same public About page a logged-out browser sees, so there's no partner approval to wait on.

Can I enrich a whole list of companies in one run? Yes. Pass every LinkedIn company URL in the companyUrls array and you get one flat record per company in a single dataset, ready to export as CSV or push straight into your CRM.

Use in Claude, ChatGPT and any MCP agent

Add it to Claude Code in one line:

$claude mcp add --transport http apify "https://mcp.apify.com?tools=themineworks/linkedin-company-details"

Or point any MCP client at:

https://mcp.apify.com/?tools=themineworks/linkedin-company-details

Things an agent can ask for once connected:

• "Look up firmographics for OpenAI and Stripe from their LinkedIn company pages."
• "Get industry, headquarters, and employee count for these ten target accounts."
• "Check whether this company's LinkedIn follower count and headcount band have grown since I last checked."

Copy this into your AI assistant

Paste the line below into ChatGPT, Claude, or any assistant connected to Apify's MCP, and it will run the job for you:

Use the Apify actor themineworks/linkedin-company-details to look up industry, headquarters, employee count, and founding year for https://www.linkedin.com/company/openai and https://www.linkedin.com/company/stripe. Return the results as a table.

Or call it programmatically with the Apify client:

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });

const run = await client.actor('themineworks/linkedin-company-details').call({
  companyUrls: [
    'https://www.linkedin.com/company/openai',
    'https://www.linkedin.com/company/stripe',
  ],
  maxResults: 10,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

🛠️ Related LinkedIn actors

Profiled the companies. Now find the people and reach them with the full LinkedIn wedge:

• LinkedIn Profile Scraper: full profile detail (experience, education, skills) from a linkedin.com/in/ URL.
• LinkedIn Employees Scraper: every public employee profile at a target company, by role.
• LinkedIn Jobs Scraper: public job listings by keyword and location, useful for flagging accounts that are hiring.
• LinkedIn Post Scraper: public LinkedIn posts and their authors by keyword, for social listening and lead discovery.
• LinkedIn Candidate Finder: a matched candidate shortlist from role, skills, and location.
• B2B Leads Finder: named decision-maker contacts with business emails and phone numbers from a company or domain list.

Typical flow: linkedin-company-details profiles the account, linkedin-employees finds the people, b2b-leads-finder adds emails and titles.

Found a bug or have a feature request? Open an issue on the actor's Apify Console page or reach out through the Apify profile.