LinkedIn Public Company Profiles Scraper (No Cookies)

Turn exact LinkedIn company URLs or slugs into structured, export-ready firmographic records with this LinkedIn company profiles scraper. No LinkedIn account or cookies are needed. Company names are not searched or guessed. A run-start charge applies, and only successfully saved company profiles incur a result charge.

Use it for CRM enrichment, account research, recruiting analysis, investment research, and recurring competitor monitoring. Every submitted input ends as either a company record or an explicit failed/skipped outcome, so duplicates and entries above the cap never disappear silently.

Quick start

1. Paste exact LinkedIn company URLs or slugs into LinkedIn company URLs or slugs.
2. Start with a small maxCompanies value, such as 10, and run the Actor.
3. Open the default dataset to export company records as JSON, CSV or Excel. Check the Input errors dataset and OUTPUT summary for inputs without a record.

Only public company information is available. Login-gated or challenged pages may return no company record.

Example input:

{
  "companyUrls": [
    "https://www.linkedin.com/company/apify/",
    "openai"
  ],
  "maxCompanies": 10,
  "includeFieldProvenance": true,
  "includeJobOpeningCount": false
}

Prefer a video guide? This short Apify walkthrough shows you how to set up and run an Actor. It uses a different Actor, but the setup steps are the same.

What you get

• Requested, actual final, source canonical, and normalized LinkedIn company identity
• LinkedIn company ID when publicly exposed
• Company name, tagline, description, website, and website domain
• Displayed industry plus taxonomy ID/URN when available
• Company type and founded year
• Employee range, associated member count, and follower count as separate values
• Headquarters, public locations, and specialties
• Public logo and cover image URLs
• Optional aggregate job-opening count when publicly displayed
• Per-field provenance, missing fields, fetch timestamp, and schema version

This actor is company-metadata only. It does not collect employee identities, personal profiles, work histories, email addresses, phone numbers, Sales Navigator data, or inferred contacts.

Who is it for?

• B2B sales and RevOps teams enriching exact known company accounts.
• Recruitment analysts reviewing public employer size, location and industry context.
• Market researchers assembling source-backed firmographic snapshots.
• Competitive-intelligence and data teams comparing their own repeat exports without substituting guessed companies.

How you can use the data

• Enrich a known account pair. Use the existing Apify company URL and openai slug with a small company cap and field provenance enabled. Keep requested, canonical and resolved identities with source notes rather than searching or guessing company names.
• Keep different public size signals separate. Export employeeRange, associatedMemberCount and followerCount as different fields. They are not interchangeable measures or inferred employee identities.
• Request aggregate hiring context deliberately. Enable the optional public job-opening count for a bounded exact-company lookup. This is an aggregate when exposed rather than job listings, and disabled optional fields are omitted.
• Reconcile your own account list. Preserve input indexes and inspect the separate Input errors dataset and OUTPUT for failed, duplicate, capped or mismatched outcomes. Join exact IDs and collection times in your own CRM or later comparison without treating missing companies as deleted or private.

Input settings

Field	Type	Default	Description
LinkedIn company URLs or slugs (companyUrls)	string[]	required	Exact company URLs or slugs, not company names or websites.
Maximum companies (maxCompanies)	integer	100	Up to 1,000 unique inputs. The form example is 10.
Include field provenance (includeFieldProvenance)	boolean	true	Source notes for available fields.
Include public job opening count (includeJobOpeningCount)	boolean	false	Optional aggregate count, not job listings.

Inputs are normalized while preserving original indexes and order. Duplicate entries and valid entries above maxCompanies receive explicit uncharged outcomes.

Enrich a CRM account list

Submit canonical company URLs exported from your CRM and keep includeFieldProvenance enabled for auditable enrichment.

Monitor competitors

Schedule the same slug list daily or weekly, then compare follower count, employee range, description, and headquarters over time.

Validate a mixed list safely

Submit URL and slug entries together. Invalid websites, names, and personal profiles appear in the errors dataset instead of being silently treated as searches.

Example inputs

Use the Quick start input as a small first run. Adjust the fields described above for your own data.

Output data

Illustrative record shape, not a current snapshot of the company. Optional values vary between runs.

{
  "requestedUrl": "https://www.linkedin.com/company/apify/",
  "requestedSlug": "apify",
  "finalUrl": "https://www.linkedin.com/company/apify/",
  "sourceCanonicalUrl": "https://www.linkedin.com/company/apify/",
  "canonicalUrl": "https://www.linkedin.com/company/apify/",
  "resolvedSlug": "apify",
  "linkedinCompanyId": "10608457",
  "identityMatch": "exact",
  "name": "Apify",
  "tagline": null,
  "description": "Apify is the largest marketplace of tools for AI...",
  "website": "https://apify.com/",
  "websiteDomain": "apify.com",
  "industryDisplayed": "Technology, Information and Internet",
  "companyType": "Privately Held",
  "foundedYear": 2016,
  "employeeRange": "201-500 employees",
  "associatedMemberCount": 244,
  "followerCount": 27073,
  "headquarters": "Prague",
  "locations": [{ "address": "Prague", "isHeadquarters": true }],
  "specialties": ["Web scraping", "Browser automation", "AI agents"],
  "logoUrls": [],
  "coverUrls": [],
  "missingFields": ["tagline", "industryId", "industryUrn"],
  "fetchedAt": "2026-07-10T12:55:25.574Z",
  "schemaVersion": "1.0"
}

Unavailable optional public fields remain null or empty and are listed in missingFields. They are never guessed. jobOpeningCount and fieldProvenance are omitted when their respective options are off.

More output fields

Field	Type	Description
requestedUrl, requestedSlug	string	Normalized identity requested by the input.
canonicalUrl, resolvedSlug	string	Canonical public company URL and the slug returned for it.
linkedinCompanyId	string or null	Public LinkedIn company identifier when exposed.
finalUrl, sourceCanonicalUrl	string	Actual HTTP response URL and the page's original canonical URL (falling back to the final URL when absent).
identityMatch	string	exact, redirected, or canonicalized. Canonicalization preserves a requested route served without an observed redirect and requires consistent first-party profile evidence. Never a fuzzy name substitution.
name, tagline, description	string or null	Public company name and profile text.
website, websiteDomain	string or null	Public company website and normalized domain.
industryDisplayed	string or null	Industry label displayed on the public profile.
industryId, industryUrn	string or null	Public industry taxonomy identifiers when available.
companyType, foundedYear	string/integer or null	Public ownership/type label and founding year.
employeeRange	string or null	Displayed employee range. Kept separate from member counts.
associatedMemberCount, followerCount	integer or null	Public aggregate member and follower counts.
headquarters, locations	string/array	Headquarters label and public location objects.
specialties	string[]	Public company specialties.
logoUrls, coverUrls	string[]	Public profile image URLs.
jobOpeningCount	integer or null	Optional public aggregate job-opening count.
fieldProvenance	object	Optional source notes for available fields.
missingFields	string[]	Fields that were unavailable rather than guessed.
fetchedAt, schemaVersion	string	UTC extraction timestamp and output contract version.

Download your results

Open your run's dataset, choose Export and select JSON, CSV or Excel. JSON keeps nested fields together. CSV and Excel are useful when you want to review the records in a spreadsheet.

See Apify's download and export guide for the available formats and field options.

Pricing

The start event charges once when a run begins, including runs without company results. The result event charges for each successfully saved, identity-checked company profile. Failed, duplicate, capped and mismatched inputs do not incur a result charge.

Keep the company cap small when checking a list. See the live Pricing tab for current rates and plan discounts.

Tips for best results

• Use exact company URLs or slugs rather than names or websites. Identity is checked rather than replaced by a fuzzy name match.
• Retain requested, final and canonical identity together. A company can redirect to a new route, or serve a corroborated canonical profile at an older route without a redirect.
• Keep field provenance when reviewing important attributes. Missing source values are not inferred.
• Inspect the separate errors dataset before calling a list complete. Duplicate and above-cap entries have explicit uncharged outcomes.
• Choose aggregate job count only when needed. It does not add vacancies or employee records.

Limits and caveats

Only publicly exposed company metadata is supported, without a LinkedIn account or cookies. No employee identities, personal profiles, work histories, email addresses, phone numbers, Sales Navigator data or inferred contacts are collected. Names, websites and non-company targets are not treated as discovery searches.

Company URLs or slugs that redirect to a public showcase page can be supported, preserving the showcase route in canonicalUrl while checking the resolved slug. Direct showcase URLs are not accepted as inputs. A redirect is not a fuzzy company-name substitution. Some company routes instead serve a canonical profile without changing the actual response URL. These are labeled canonicalized only when canonical, Open Graph and Organization routes agree with the primary profile, including its scoped company identifier and profile links. Ambiguous or conflicting identity still produces an uncharged IDENTITY_MISMATCH. This parser support does not bypass access blocks or enable a paid fallback.

Public fields vary and missing values remain null or empty with missingFields. Login gates, rate limits and challenges can produce bounded BLOCKED failures rather than partial company records. Optional field provenance and job-opening count are omitted when disabled, and the opening count is aggregate only.

Up to one thousand unique inputs are processed with bounded concurrency, preserving original indexes and explicit terminal outcomes. Successful companies are separate from uncharged failed or skipped input records. Check Input errors and OUTPUT when no company record appears. Inaccessibility alone does not establish deletion or privacy. Repeat-export comparisons and monitoring are your own workflow.

Automation and integrations

Save your settings for next time

Once you have an input that works for you, save it as an Apify task. This keeps your settings together so you can use them again without filling in the form from scratch.

Run on a schedule

Need fresh results regularly? You can schedule the Actor or a saved task to run at a time that suits you.

Each scheduled run collects the data again. If you want to compare results or highlight changes, add that step in your own workflow.

Send results to your other tools

Use n8n, Make or Zapier to connect this scraper to the rest of your workflow. For example, you could pass its results to an AI assistant or add records to a spreadsheet. Follow the Apify integration guides for your chosen tool.

For a custom connection, an Apify webhook can notify your app when a run finishes or fails. Your app can then fetch the results or handle the failure.

API usage

Want to collect this data from your own app or automation? The examples below send input to the scraper and show how to collect its results.

The Node.js and Python examples wait for the run to finish before reading its results. The cURL example starts the run and returns its details. Wait for that run to finish, then use its defaultDatasetId to fetch the results.

For setup instructions, see Apify's JavaScript client guide, Python client guide and Actor runs API reference.

cURL

curl -X POST 'https://api.apify.com/v2/acts/fetch_cat~linkedin-company-profiles-scraper/runs' \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H 'Content-Type: application/json' \
  --data @- <<'JSON'
{
  "companyUrls": [
    "https://www.linkedin.com/company/apify/",
    "openai"
  ],
  "maxCompanies": 10,
  "includeFieldProvenance": true,
  "includeJobOpeningCount": false
}
JSON

Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('fetch_cat/linkedin-company-profiles-scraper').call({
  "companyUrls": [
    "https://www.linkedin.com/company/apify/",
    "openai"
  ],
  "maxCompanies": 10,
  "includeFieldProvenance": true,
  "includeJobOpeningCount": false
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Python

import os
from apify_client import ApifyClient

client = ApifyClient(os.environ['APIFY_TOKEN'])
run = client.actor('fetch_cat/linkedin-company-profiles-scraper').call(run_input={'companyUrls': ['https://www.linkedin.com/company/apify/', 'openai'], 'maxCompanies': 10, 'includeFieldProvenance': True, 'includeJobOpeningCount': False})
print(client.dataset(run['defaultDatasetId']).list_items().items)

MCP and AI agents notes

• “Fetch the public company profiles for the exact LinkedIn slugs apify and openai, and compare their displayed industries and employee ranges.”
• “Retrieve this exact public LinkedIn company URL and report any missing fields without inferring values: https://www.linkedin.com/company/apify/.”

MCP and AI agents

You can ask your AI assistant to collect data with LinkedIn Public Company Profiles Scraper (No Cookies) and help you work with the results. The scraper returns the data, and your assistant can then summarize it, compare records or prepare notes.

Connect your assistant through the Apify MCP server. MCP gives your assistant a way to find this scraper, run it and read the results. Follow the official setup and sign-in guide for your app.

Easier setup with an Apify plugin

If you use a supported coding assistant, the official Apify plugin can set up the connection for you. It connects your assistant to Apify and includes instructions for common tasks. Follow the guide for your particular app.

Use Apify AI in Console

Prefer to keep everything in Apify? Open Apify AI in Console and ask it to find Fetch Cat's LinkedIn Public Company Profiles Scraper (No Cookies). You can describe the data you want and ask questions about the results.

Apify AI is currently in beta. It asks for confirmation before starting an Actor, and normal run charges apply.

Choose your assistant

• Claude and Claude Code (Anthropic): Apify setup guide.
• ChatGPT and Codex (OpenAI): Apify setup guides.
• Grok Bot (xAI): Apify plugin guide.
• Gemini CLI (Google): MCP server setup guide. Use the server URL below with the HTTP configuration supported by Gemini CLI.

Connect just this scraper

To keep your setup focused on this scraper, add this server configuration to a compatible MCP client:

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com?tools=fetch_cat/linkedin-company-profiles-scraper"
    }
  }
}

Sign in to Apify when your client asks. If your client uses a Bearer token instead, follow its setup guide and keep the token in its secure configuration. Configuration formats vary by app, so use the linked guide if your client needs a different format.

Use Apify's general server

Already connected to the general Apify MCP server at https://mcp.apify.com? You can use it to find this scraper without adding another server. Ask your assistant to use LinkedIn Public Company Profiles Scraper (No Cookies) by Fetch Cat, or give it the identifier fetch_cat/linkedin-company-profiles-scraper.

Your assistant can check the available settings and retrieve the results from the returned run. If the run is still working, it should follow that run rather than start it again. Both connection options use Apify's hosted service.

Example requests

• “Use Fetch Cat’s LinkedIn Public Company Profiles Scraper (No Cookies) to retrieve https://www.linkedin.com/company/apify/ and slug openai with a two-company cap, field provenance on and job-opening count off. Keep requested and resolved identities with missing fields visible.”
• “Collect the exact Apify LinkedIn company profile with a one-company cap, provenance on and public job-opening count enabled. Keep that aggregate separate from employee range, member count and follower count without retrieving jobs or employee identities.”
• “Retrieve the Apify company URL and openai slug in that order with a one-company cap, provenance on and opening count off. Reconcile the result with Input errors and OUTPUT so the capped second input is not mistaken for a missing company.”

Normal Apify charges apply. Check the live Pricing tab before asking your assistant to run a larger batch.

Pay with x402

If your AI agent has a funded wallet, it can pay for Apify usage through x402. This experimental option lets an agent use Apify without a conventional account.

Apify AGI provides a prepaid API token with a spending cap after payment. Your agent can use that token to run this scraper through the Apify API or an authenticated MCP connection.

Some MCP setups also support paying for each request directly. That is a different payment option, so check the official guide for its availability.

Follow the official guide for wallet setup, supported payment options and current terms. Apify handles the payments. Keep wallet keys and payment tokens in your agent's secure configuration.

Other ways for agents to pay

Apify also supports MPP for prepaid access through AGI and Skyfire for eligible Actors. If your agent already uses one of these, see the agentic payment guide to choose the right setup.

Results and errors

Successful profiles are written to the default Company profiles dataset. Failed and skipped terminal outcomes are written separately to the Input errors dataset with the zero-based input index, original input, status, outcome code, HTTP status, retry count, message, and timestamp. The OUTPUT record reports requested and terminal-outcome totals plus successful, failed, skipped-duplicate, and capped counts.

Error/skipped rows are never charged as company results. Common codes are INVALID_INPUT, DUPLICATE_INPUT, MAX_COMPANIES_EXCEEDED, NOT_FOUND, BLOCKED, IDENTITY_MISMATCH, HTTP_ERROR, and PARSE_ERROR.

FAQ

Does it need LinkedIn cookies or an account?

No. It processes publicly available company pages without user cookies or LinkedIn credentials.

Can I submit a company name or website?

No. Names, arbitrary websites, search queries, and non-company LinkedIn URLs are rejected. This prevents wrong-company substitutions.

Why are some fields null?

Companies choose which optional details to publish, and page layouts vary. Missing values are reported rather than inferred.

Are employee profiles included?

No. The product intentionally stays within a company-only privacy boundary.

Do failed inputs cost money?

They do not incur the per-company result charge. The one-time run-start event still applies.

Can I use this as a LinkedIn company API alternative?

Use the Apify API examples above for exact company URLs or slugs. This is an independent public-data Actor, not the official LinkedIn API. It does not provide employee identities or account-only fields.

What if the dataset is empty?

Check the Input errors dataset and OUTPUT totals. Unavailable, challenged or invalid inputs can produce no company records. An access failure alone does not establish that a company was deleted or made private.

Related Actors

• LinkedIn Jobs Scraper for public job listings
• Google Ads Transparency Scraper for advertiser and campaign research
• Website Content Crawler Lite for separate public website content collection
• GLEIF LEI Records Scraper for global legal-entity identifiers
• UK Companies House Scraper for UK company records

Support and feedback

For custom additions or integrations, email hello@fetchcat.dev.

Found an error or have a feature request? Open an issue with the run URL, a non-sensitive input example and what you expected.

Need help sharing it? See Apify’s guide to sharing a run when reporting an issue. Sharing a run can give the developer access to its input, logs and results, so use a run that contains no sensitive data. Please leave out API tokens, passwords, cookies, private documents and personal data. Use a public sample URL or a redacted example instead.

Tried this scraper? We'd love to hear how it worked for you. Leave a review to help others choose the right tool and help us improve it. Your feedback means a lot to us.

Made with care for curious people, AI agents and the possibilities in data. ♥