# LinkedIn Company Lookup: linkedin company scraper from $5/1k (`accountable_eel/linkedin-company-lookup`) Actor

LinkedIn company scraper with no cookies and no account. Give it public LinkedIn company page links and get one flat row each: name, tagline, industry, company size, employees on LinkedIn, headquarters, founded, website, specialties, followers and logo. Nothing found, nothing charged.

- **URL**: https://apify.com/accountable\_eel/linkedin-company-lookup.md
- **Developed by:** [Adrian Voss](https://apify.com/accountable_eel) (community)
- **Categories:** Lead generation, Business
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks
- **User rating**: No ratings yet

## Pricing

from $3.80 / 1,000 company founds

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## LinkedIn Company Lookup: LinkedIn Company Scraper, No Cookies

Hand this actor a list of public LinkedIn company page links and it fetches each one the way a
signed-out browser does, then returns a flat row per company: name, tagline, the About paragraph,
industry, the size band the company claims, how many members actually list it as their employer,
headquarters, founding year, ownership type, website, specialty tags, follower count and logo.
No login. No cookies. No `li_at` session token to paste in, no account of yours at risk, and
nothing read from behind LinkedIn's sign-in wall.

Most of each row comes from the `schema.org` Organization block LinkedIn itself publishes in the
page source, so it is the company's own structured description of itself rather than text scraped
off a layout that changes every quarter. When LinkedIn decides a request should sign in first, the
actor says so in the row's `status` and charges you nothing.

### Who it's for

Account executives working an ABM list who need every target company's headcount, industry and
headquarters in the same spreadsheet the links came in on. RevOps teams filling the empty
firmographic columns behind a CRM field that only ever stored a LinkedIn URL. Investors and
analysts sizing a market by pulling founding year, ownership type and employee count across
forty portfolio candidates at once. Recruiters qualifying which employers on a longlist are
actually 200 people rather than the 2,000 their careers page implies. And anyone wiring an agent
or a workflow that already holds a company page link and needs the organisation behind it in a
shape a script can read, with no logged-in LinkedIn session kept alive anywhere.

If you do not have the company links yet, this is the wrong tool. It looks up companies you
already name; it does not search LinkedIn for companies matching a description.

### Why this one

- **Two headcount numbers, not one, because they disagree.** `companySize` is the band the
  company picked for itself. `employeesOnLinkedIn` is how many members actually list it as their
  employer. Stripe reports "5,001-10,000 employees" while 16,949 members name it. Tools that
  collapse these into one number throw away exactly the signal that tells you a company has
  outgrown its own About page.
- **No cookies, no session token, no account.** Every request is the plain public page. You are
  never asked for a `li_at` cookie, and no LinkedIn account of yours can be restricted because of
  a run here.
- **Read from LinkedIn's own structured data.** Name, About text, employee count, address, logo,
  tagline and website come out of the `schema.org` Organization block in the page source. The
  five fields LinkedIn does not put there are read from stable `data-test-id` hooks, not from CSS
  classes chasing a redesign. Field names stay put, which is what an agent or a Clay column needs.
- **A block is a labelled miss, not a silent hole.** If LinkedIn asks the request to sign in, the
  row says `status: BLOCKED` with a plain explanation and costs nothing. A page that no longer
  exists says `NOT_FOUND`. A member profile pasted by mistake says `BAD_FORMAT` without ever
  spending a request.
- **Never charged for a miss.** Billing fires only on a row where a real company came back.
- **Schools and showcase pages work too.** `/company/`, `/school/` and `/showcase/` links all
  parse, because a pasted CRM column has all three mixed in.
- **Residential proxy by default.** LinkedIn's sign-in wall is driven by the reputation of the IP
  asking, so the actor ships with residential proxy already selected and retries a blocked request
  on a fresh address rather than handing you the failure.

### What you get

One row per company you submit. Every row opens with the same five bookkeeping fields (`query`,
`found`, `status`, `message`, `scrapedAt`), then the company itself:

| Field | What it is |
|---|---|
| `companyUrl`, `slug` | Canonical page link, and the stable identifier after `/company/`. `slug` is your join key. |
| `name`, `tagline` | Company name, and the one-line tagline under it. |
| `description` | The full About-us paragraph the company wrote about itself. |
| `industry` | LinkedIn's industry label, e.g. "Technology, Information and Internet". |
| `companySize` | The employee band the company reports for itself, as text: "5,001-10,000 employees". |
| `employeesOnLinkedIn` | How many members actually list this company as their employer, as a number. |
| `headquarters`, `founded`, `companyType` | Location as printed, founding year as a number, and ownership type ("Privately Held", "Public Company"). |
| `website` | The company's own site, unwrapped from LinkedIn's tracking redirect. |
| `specialties` | Specialty tags from the About section, as an array. Empty for companies that publish none, which is common. |
| `followerCount`, `logoUrl` | Exact follower count, not the rounded "1.7M" the signed-in UI shows, and the logo URL. |
| `source`, `masked` | Whether the row came from the page's structured data or the HTML fallback, and whether LinkedIn trimmed the page. |

Two things worth knowing before you rely on a column. `specialties` is genuinely empty for many
companies: Stripe publishes none, Shopify publishes twenty. And `followerCount` is read from the
top card and the page's own meta description rather than pattern-matched across the page, because
a company page also carries the follower counts of the "similar pages" in its sidebar.

### Pricing

$5 per 1,000 companies, plus a $0.00005 start fee. Misses (`found:false`) are never charged.

### Use it from Clay, n8n, Make, or an AI agent

This actor runs synchronously over plain HTTP — call it directly from a script, a workflow tool, or an AI agent, no Apify Console needed once you have an API token.

```bash
curl "https://api.apify.com/v2/acts/accountable_eel~linkedin-company-lookup/run-sync-get-dataset-items?token=<YOUR_TOKEN>" \
  -X POST \
  -H "Content-Type: application/json" \
  -d '{"companies":["https://www.linkedin.com/company/stripe","shopify"]}'
```

**n8n.** Add an HTTP Request node: Method `POST`, URL `https://api.apify.com/v2/acts/accountable_eel~linkedin-company-lookup/run-sync-get-dataset-items?token=<YOUR_TOKEN>`, Body Content Type `JSON`, JSON Body `{"companies":["https://www.linkedin.com/company/stripe","shopify"]}` (swap in an expression from an earlier node for a real value).

**Clay.** Add an "HTTP API" column: Method `POST`, URL `https://api.apify.com/v2/acts/accountable_eel~linkedin-company-lookup/run-sync-get-dataset-items?token=<YOUR_TOKEN>`, Body `{"companies":["{{company}}"]}`, mapping the row's company into the `companies` array.

**MCP.** In Claude, Cursor, or any MCP client with the Apify MCP server, ask for "LinkedIn Company Scraper, No Cookies | Apify" — the agent will find and run this actor.

### How to use

1. **In the Apify Console.** Open the actor page and click **Start** — the `companies` field is already pre-filled with a working example. Results land in the run's dataset as soon as each item is found.
2. **Via the API.** Call it directly with a POST request — no Console needed once you have an API token:
   ```bash
   curl "https://api.apify.com/v2/acts/accountable_eel~linkedin-company-lookup/run-sync-get-dataset-items?token=<YOUR_TOKEN>" \
     -X POST \
     -H "Content-Type: application/json" \
     -d '{"companies":["https://www.linkedin.com/company/stripe","shopify"]}'
   ```
3. **On a schedule.** Save this actor as an Apify **Task** with the input you want, then add a **Schedule** (hourly, daily, weekly) so it runs on its own — no server of your own required.

### Input

```json
{
  "companies": [
    "https://www.linkedin.com/company/stripe",
    "shopify"
  ]
}
```

One company per line. Paste the full company page link, or just the part after /company/. Accepted formats: https://www.linkedin.com/company/stripe, linkedin.com/company/stripe, stripe.

Optional fields: `onlyFound` drops the misses, `includeKeywords` / `excludeKeywords` filter rows
by the text they contain, `maxResults` caps a trial run, `testRun` processes only the first five,
and `columns` picks which fields come back. Concurrency and proxy live under **Advanced**.

### Output

One row per item, for example:

| query | found | status | companyUrl | slug | name | tagline | description | industry | companySize | employeesOnLinkedIn | headquarters | founded | companyType | website | specialties | followerCount | logoUrl | source | masked | scrapedAt |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| stripe | true | OK | https://www.linkedin.com/company/stripe | stripe | Stripe | Help increase the GDP of the internet. | Stripe builds programmable financial services. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Headquartered in San Francisco and Dublin, the company aims to increase the GDP of the internet. | Technology, Information and Internet | 5,001-10,000 employees | 16918 | South San Francisco, California | 2010 | Privately Held | https://stripe.com | \[] | 1687463 | https://media.licdn.com/dms/image/v2/D560BAQE2ZfJyfn-VCg/company-logo\_200\_200/B56ZlyKwpUKIAI-/0/1758557047806/stripe\_logo | jsonld | false | 2026-09-08T17:42:24.662Z |

A miss comes back as a row with `"found": false` and is never charged.

### Tips

- `slug` is the join key, not `name`. Companies rebrand and rename their display name; the
  identifier after `/company/` is what survives, and it is what you should key your table on.
- Compare `employeesOnLinkedIn` against `companySize` rather than picking one. A company whose
  member count sits well above its stated band is either growing fast or has not updated its
  About page in years, and either one is a useful thing to know before a call.
- Treat an empty `specialties` array as "publishes none", not as an error. Plenty of large
  companies fill in nothing there.
- A wave of `BLOCKED` rows means the addresses you are running from are being asked to sign in.
  Lower **Max concurrency**, leave residential proxy on, and re-run those rows later. They cost
  you nothing the first time.
- Feed the `website` field straight into a domain-based enrichment step. It is the clean
  destination URL, already unwrapped from LinkedIn's redirect, so it joins cleanly to anything
  keyed on domain.
- Store `founded` as a number and `companySize` as text. The size band is a display string with a
  comma and a hyphen in it, and forcing it into a numeric column loses it entirely.

### vs. alternatives

| | What it costs | What you get | Trade-off |
|---|---|---|---|
| **This actor** (`linkedin-company-lookup`) | $0.005 per company found at the FREE tier, less on paid tiers, $0.00005 actor start, nothing for a miss | One flat row per public company page: name, tagline, About text, industry, self-reported size band, employees on LinkedIn, headquarters, founding year, ownership type, website, specialties, followers and logo | Public company pages only. No funding, revenue or employee lists, because the logged-out page does not publish them. It looks up companies you name; it does not search for them. |
| **HarvestAPI's `linkedin-company`** | Listed at $4 per 1,000 companies | The category leader by some distance: 5,011 users in the last 30 days at a 4.48 rating, inside the store's top 50, and part of a family that also covers people search and posts | Cheaper per row and far more proven. Pick this one for the two-number headcount split, the free misses, and a start fee of $0.00005 rather than a per-run floor. |
| **Clay** | $0.08 to $0.40 per enriched row in credits, on top of a seat | A whole enrichment workspace: waterfalls across dozens of providers, plus the table and the sequencing around it | If you want one place that does everything and you are not counting rows, that is Clay. This is one column, priced per column, callable *from* Clay via its HTTP step. |
| Doing it yourself | Your time, plus residential proxy spend, plus keeping up with a sign-in wall that moves | The same fields | What this absorbs: pulling the real Organization node out of a JSON-LD graph that also contains eight post-author stubs, unwrapping a website URL whose dots are percent-encoded, reading a follower count without catching the sidebar's other companies, and retrying a blocked address instead of failing the row. |

Prices for third-party tools are their published list prices as of September 2026 and are not
tracked here. Check the vendor before relying on the comparison.

### FAQ

**Do I need a LinkedIn account, or to paste in a cookie?**
No. It reads the public company page exactly as a signed-out browser gets it. You are never asked
for credentials, a session cookie or an `li_at` token, and no account of yours is put at risk.

**Why are there two headcount fields?**
Because LinkedIn publishes two different numbers and they mean different things. `companySize` is
the band the company selected for its own About section. `employeesOnLinkedIn` counts the members
who list it as their employer. For Stripe those are "5,001-10,000 employees" and 16,949. Keeping
both is the honest answer; picking one for you would be a guess about which question you are
asking.

**Why did a row come back with `found: false`?**
One of four reasons, and `status` says which. `BLOCKED`: LinkedIn asked that request to sign in
instead of serving the page. `NOT_FOUND`: no public company page exists at that address any more.
`BAD_FORMAT`: the input was not a company page, most often an `/in/` member profile pasted by
mistake. `REQUEST_FAILED`: the request did not complete after retries. None of the four is charged.

**Why is `specialties` empty for some companies?**
Because those companies publish none. The specialties list is an optional field the company fills
in itself, and plenty of large, well-run pages leave it blank. An empty array means "nothing
listed", never "we could not read it".

**Does it return funding, revenue or a list of employees?**
No. None of those are on the logged-out company page. Employee-level data in particular sits
behind the sign-in wall, and this actor does not go there.

**What is `masked`?**
It is a guard carried over from the member-profile side of LinkedIn, where the site sometimes
serves a trimmed page with values replaced by rows of asterisks. No company page captured while
building this actor behaved that way, so expect `false`. If LinkedIn ever does trim a company
page, the asterisks are stripped rather than passed through and the row is flagged so you can
re-run it instead of importing placeholder text.

**Can I pass a school or a showcase page?**
Yes. `/company/`, `/school/` and `/showcase/` links all use the same public template and all
parse. A member profile (`/in/`) does not, and is rejected as `BAD_FORMAT` before a request is
spent.

**Am I charged for a miss?**
No. Billing fires only when a real company page was read. Blocked pages, missing pages and
malformed input all produce a row explaining themselves, unless you turn on "Hide rows with no
result", and none of them cost anything.

**Do I need to configure a proxy?**
It is already configured. Residential proxy is the shipped default because LinkedIn's sign-in wall
keys on the reputation of the address asking. You can change the group under Advanced, but
lowering it is the most common reason a list comes back mostly blocked.

**Is this a live fetch or a stored database?**
Live. Every run fetches the current page, and nothing is stored between runs. A company that
updated its About section yesterday shows the new version today.

**Can an AI agent call this directly?**
Yes. It is on the Apify MCP server, so an agent in Claude, Cursor or any other MCP client can find
and run it by name, and the REST endpoint above works from any script or workflow tool.

### Personal data, and your responsibility

This actor reads public LinkedIn company pages. Most of what it returns is information about an
organisation rather than an individual, but company pages can still carry personal data, and in
the EU and UK a small company's details can identify the people behind it. The actor reads nothing
behind the sign-in wall and holds nothing between runs: each row is fetched live and written to
your own dataset, which only you control.

Whether you may collect, store and use that data is a question about you and your purpose, not
about this tool. If the GDPR applies to what you do next, you need a lawful basis, plus the duties
around transparency, retention and honouring a request to be erased. LinkedIn's own User Agreement
also restricts automated collection, and it binds anyone using it under an account. Nothing here
is legal advice, and running this actor is not a determination that your use is lawful. That call,
and the compliance work behind it, is yours.

### Related actors

- [LinkedIn Profile Lookup](https://apify.com/accountable_eel/linkedin-profile-lookup) the same
  approach for the people side: public member profiles, no cookies, one row each.
- [Company Domain Enrichment](https://apify.com/accountable_eel/company-domain-enrichment) take
  the `website` this actor returns and add registration, DNS, tech stack and hiring signal.
- [LinkedIn Jobs Search Lookup](https://apify.com/accountable_eel/linkedin-jobs-search-lookup) run
  a public LinkedIn job search by keyword and location and get one row per posting.
- [ATS Jobs Unified Lookup](https://apify.com/accountable_eel/ats-jobs-unified-lookup) check what
  a company is hiring for across the six major applicant tracking systems.

# Actor input Schema

## `companies` (type: `array`):

One company per line. Paste the full company page link, or just the part after /company/. Accepted formats: https://www.linkedin.com/company/stripe, linkedin.com/company/stripe, stripe. You're only charged for the ones we actually find — a miss costs nothing.

## `testRun` (type: `boolean`):

Turn this on to test your input on a small sample before running the full list. Turn it off to process everything.

## `onlyFound` (type: `boolean`):

Only keep rows where something was actually found. Misses are always free, whether or not you show them here.

## `includeKeywords` (type: `array`):

Optional. Only keep results that mention at least one of these words (e.g. a job title, a city, a product name). Leave empty to keep everything.

## `excludeKeywords` (type: `array`):

Optional. Drop any result that mentions one of these words. Leave empty to skip nothing.

## `maxResults` (type: `integer`):

Optional. Stop the run once this many results have been found — useful for a quick, cheap sample. Leave blank for no limit.

## `columns` (type: `array`):

Choose which pieces of information to include in each result row. All are included by default.

## `maxConcurrency` (type: `integer`):

Parallel requests. Keep conservative — this target has no browser fallback, so getting blocked costs more than slow-and-steady.

## `proxyConfiguration` (type: `object`):

Apify Proxy config. Residential recommended for anti-bot-sensitive targets.

## Actor input object example

```json
{
  "companies": [
    "https://www.linkedin.com/company/stripe",
    "shopify"
  ],
  "testRun": false,
  "onlyFound": false,
  "includeKeywords": [],
  "excludeKeywords": [],
  "columns": [
    "companyUrl",
    "slug",
    "name",
    "tagline",
    "description",
    "industry",
    "companySize",
    "employeesOnLinkedIn",
    "headquarters",
    "founded",
    "companyType",
    "website",
    "specialties",
    "followerCount",
    "logoUrl",
    "source",
    "masked"
  ],
  "maxConcurrency": 2,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ]
  }
}
```

# Actor output Schema

## `results` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "companies": [
        "https://www.linkedin.com/company/stripe",
        "shopify"
    ],
    "includeKeywords": [],
    "excludeKeywords": []
};

// Run the Actor and wait for it to finish
const run = await client.actor("accountable_eel/linkedin-company-lookup").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "companies": [
        "https://www.linkedin.com/company/stripe",
        "shopify",
    ],
    "includeKeywords": [],
    "excludeKeywords": [],
}

# Run the Actor and wait for it to finish
run = client.actor("accountable_eel/linkedin-company-lookup").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "companies": [
    "https://www.linkedin.com/company/stripe",
    "shopify"
  ],
  "includeKeywords": [],
  "excludeKeywords": []
}' |
apify call accountable_eel/linkedin-company-lookup --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,accountable_eel/linkedin-company-lookup"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/G5gLGwShbU4KZCnco/builds/bah8pF3VrdDZXrZem/openapi.json