# LinkedIn Company Pages Scraper (`barefoot_grade/linkedin-company-scraper`) Actor

Smoke build.

- **URL**: https://apify.com/barefoot_grade/linkedin-company-scraper.md
- **Developed by:** [Philip Kirkbride](https://apify.com/barefoot_grade) (community)
- **Categories:** Social media, Lead generation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.75 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

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

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## LinkedIn Company Pages Scraper

Turn a list of LinkedIn company links or company names into clean company profiles. Every company becomes one row with its name, tagline, description, industry, company size band, number of employees on LinkedIn, follower count, headquarters and street address, founding year, organization type, specialties, website, logo and cover image, plus the similar and affiliated companies LinkedIn shows next to it and the company's most recent public posts.

Use it to enrich a CRM or lead list, size up competitors, track follower growth over time, or build a market map from a handful of seed companies. Only public company information is collected: nothing about individual members, and no LinkedIn account is needed.

### Quick Start

```json
{
  "companies": [
    "https://www.linkedin.com/company/apify/",
    "https://www.linkedin.com/company/mercadolibre/",
    "microsoft"
  ],
  "maxItems": 100,
  "includeUpdates": true,
  "followSimilarPages": false
}
```

Company links can be full page links (`linkedin.com/company/...`, any country version such as `uk.linkedin.com`), showcase page links (`linkedin.com/showcase/...`) or just the company name as it appears in the link.

### Input

| Input | Type | Default | Meaning |
| --- | --- | --- | --- |
| `companies` | array | required | Company or showcase page links, or bare company names such as `microsoft`. Duplicates are removed. |
| `maxItems` | integer | `100` | Total cap on company rows for the run, including companies discovered through similar pages. |
| `includeUpdates` | boolean | `true` | Add the company's most recent public posts to each row. Only posts by the company itself are included. |
| `followSimilarPages` | boolean | `false` | Also collect the companies listed under each page's similar and affiliated pages, and keep going until `maxItems` is reached. Handy for building a market map from a few seeds. |

### What it returns

The dataset contains one row per company:

| Field | Meaning |
| --- | --- |
| `kind` | `company` or `showcase`. |
| `companyId`, `slug`, `url` | LinkedIn's numeric organization id, the name used in the link, and the canonical page link. |
| `inputUrl` | What you supplied (or the similar page that led to this company). |
| `name`, `tagline`, `description` | The company's name, one-line tagline and "About us" text. |
| `website` | The company's own website, as listed on the page. |
| `industry`, `organizationType`, `foundedYear`, `specialties` | Industry, type (for example Public Company or Privately Held), founding year and the specialties list. |
| `companySize`, `companySizeMin`, `companySizeMax` | The size band shown on the page (for example `201-500 employees`) and its bounds as numbers. |
| `employeesOnLinkedIn` | Members who list this company as their employer. |
| `followerCount` | Page followers. |
| `headquarters`, `address` | Headquarters as shown, plus the street address split into street, city, region, postal code and country when published. |
| `logoUrl`, `coverImageUrl` | Logo and cover image links. |
| `similarPages`, `affiliatedPages` | Companies shown alongside this one, each with name, link, industry and location. |
| `updates` | Recent public posts by the company: link, text, publish time and like count. |
| `scrapedAt` | Collection time (UTC, ISO 8601). |
| `error` | Always `null` in the dataset. Failures are reported in the run summary instead. |

Fields the company has not filled in on LinkedIn are `null` (or an empty list), never guessed.

The run summary (`OUTPUT`) reports `companiesRequested`, `companies` (rows delivered), `errors` and the list at `companyErrors`.

### Example queries

- **Enrich a lead list:** paste the LinkedIn links from your CRM and export the rows as CSV or Excel.
- **Competitor watch:** schedule a daily run over your competitors and chart `followerCount` and `employeesOnLinkedIn` over time.
- **Market map:** start from three companies in a niche, enable `followSimilarPages` and set `maxItems` to 200.
- **Content research:** keep `includeUpdates` on to see what each company posted recently and how it performed.

### Output example

```json
{
  "kind": "company",
  "companyId": "10608457",
  "slug": "apify",
  "url": "https://www.linkedin.com/company/apify/",
  "inputUrl": "https://www.linkedin.com/company/apify/",
  "name": "Apify",
  "tagline": "Thousands of Actors to automate your business, get real-time web data, and equip your AI agents.",
  "description": "Apify is the largest marketplace of tools for AI. More than 50,000 Actors to automate your business. Get real-time web data, track competitors, generate leads, …",
  "website": "https://apify.com/",
  "industry": "Technology, Information and Internet",
  "companySize": "201-500 employees",
  "companySizeMin": 201,
  "companySizeMax": 500,
  "employeesOnLinkedIn": 274,
  "followerCount": 43252,
  "headquarters": "Prague",
  "address": {
    "street": "Vodickova 704/36",
    "city": "Prague",
    "region": null,
    "postalCode": "11100",
    "country": "CZ"
  },
  "organizationType": "Privately Held",
  "foundedYear": 2016,
  "specialties": [
    "Web scraping",
    "Browser automation",
    "AI agents",
    "API integration",
    "Data pipelines"
  ],
  "logoUrl": "https://media.licdn.com/dms/image/v2/D4D0BAQF7OnC-r1njIA/company-logo_200_200/B4DZwd3LFrHEAI-/0/1770027528966/apify_logo",
  "coverImageUrl": "https://media.licdn.com/dms/image/v2/D4E3DAQGvTIu7j6RvRg/image-scale_325_1920/B4EaEMa2.aJkAI-/0/1791209730321/apify_cover",
  "similarPages": [
    {
      "name": "n8n",
      "url": "https://www.linkedin.com/company/n8n/",
      "industry": "Software Development",
      "location": "Berlin, BE"
    }
  ],
  "affiliatedPages": [],
  "updates": [
    {
      "url": "https://www.linkedin.com/posts/apify_security-guardrails-reliability-evals-activity-7517937690013659136-sYNU",
      "text": "Security, guardrails, reliability, evals...\n\nThese were the topics at AI Engineer NYC.\n\nAI engineering has moved from no…",
      "publishedAt": "2026-10-19T13:20:21.825Z",
      "likeCount": 13
    }
  ],
  "scrapedAt": "2026-10-19T22:30:00Z",
  "error": null
}
```

### Failed companies

A company that cannot be retrieved (for example a mistyped name, or a page that no longer exists) is reported in the run summary at `OUTPUT.companyErrors` with its input, link, `code` and `message`. Failed companies are never dataset rows and are not charged. If no company at all could be collected, the run ends with an error instead of finishing green with an empty dataset.

### Limits and caveats

- Only what LinkedIn shows publicly on a company page is returned. Locations beyond the headquarters, the full employee list and post comments are not part of the public page.
- `updates` holds the posts shown publicly on the page, usually up to ten of the latest.
- LinkedIn sometimes sends an old or ambiguous company name to a different page; the row's `url` and `slug` always show the page that was actually collected, next to your `inputUrl`.
- Automated access is subject to LinkedIn's terms; use this actor only where you have the necessary permissions and a lawful basis.

### FAQ

**Do I need a LinkedIn account or cookies?** No. Only public company pages are read.

**Does it collect people's profiles?** No. Member names, photos and profiles are never collected, and only posts written by the company itself are included in `updates`.

**Can I mix links and names?** Yes. Links from any LinkedIn country site, showcase pages and bare names can all go in `companies`; duplicates are returned once.

### Price

**$0.00175 per company** delivered, plus **$0.005 per run start**. The run-start event is charged per GB of memory; the default 512 MB run is one start event. The start is charged even if the run saves no results. Failed companies are not charged. Platform usage is included in these prices.

# Actor input Schema

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

LinkedIn company page links (linkedin.com/company/...), showcase page links (linkedin.com/showcase/...) or bare company names as they appear in the link, such as microsoft. Duplicates are removed.

## `maxItems` (type: `integer`):

Total cap on company rows for the run, including companies discovered through similar pages.

## `includeUpdates` (type: `boolean`):

Add the company's most recent public posts (text, link, date and like count) to each row. Only posts by the company itself are included.

## `followSimilarPages` (type: `boolean`):

Discover more companies from each page's similar and affiliated pages, and collect them too until the maximum is reached.

## Actor input object example

```json
{
  "companies": [
    "https://www.linkedin.com/company/apify/",
    "https://www.linkedin.com/company/mercadolibre/",
    "microsoft"
  ],
  "maxItems": 100,
  "includeUpdates": true,
  "followSimilarPages": false
}
```

# Actor output Schema

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

No description

## `summary` (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/apify/",
        "https://www.linkedin.com/company/mercadolibre/",
        "microsoft"
    ],
    "maxItems": 100,
    "includeUpdates": true,
    "followSimilarPages": false
};

// Run the Actor and wait for it to finish
const run = await client.actor("barefoot_grade/linkedin-company-scraper").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/apify/",
        "https://www.linkedin.com/company/mercadolibre/",
        "microsoft",
    ],
    "maxItems": 100,
    "includeUpdates": True,
    "followSimilarPages": False,
}

# Run the Actor and wait for it to finish
run = client.actor("barefoot_grade/linkedin-company-scraper").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/apify/",
    "https://www.linkedin.com/company/mercadolibre/",
    "microsoft"
  ],
  "maxItems": 100,
  "includeUpdates": true,
  "followSimilarPages": false
}' |
apify call barefoot_grade/linkedin-company-scraper --silent --output-dataset

```

## MCP server setup

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

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/qO3OvxZ1mLGGorgOl/builds/l8m2K10DqUhHNgBS1/openapi.json