# LinkedIn Company Scraper — $1/1K, No Cookies (`meka.im/linkedin-company-scraper`) Actor

Bulk public LinkedIn company details from URLs or slugs: website, industry, size, employees, followers, address, specialties, and more. No LinkedIn account or cookies. Pay only for delivered results.

- **URL**: https://apify.com/meka.im/linkedin-company-scraper.md
- **Developed by:** [Meka.im](https://apify.com/meka.im) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$1.00 / 1,000 delivered companies

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?

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 Scraper — $1/1K, No Cookies

Extract public LinkedIn company details from URLs or slugs for **$1 per 1,000 successfully delivered companies**. No LinkedIn account, cookies, or browser session required.

- Website, industry, company type and size
- Employee and follower counts when publicly exposed
- Headquarters and structured address fields
- Specialties, logo, description and founding year when available
- Stable input order, duplicate suppression and safe retries
- Failed, invalid and unresolved inputs are skipped and are not charged as Dataset results

Two independent cold URL validation batches processed 100 confirmed public company pages in about 56–57 seconds. This is an observed result, not an SLA.

### Quick start

```json
{
  "companyUrls": [
    "https://www.linkedin.com/company/openai/",
    "microsoft"
  ],
  "maxCompanies": 100,
  "maxConcurrency": 3
}
```

`companyUrls` accepts LinkedIn company URLs, slugs, and common `/about` or `/jobs` paths. URL inputs are the reliable bulk workflow; duplicate canonical URLs are processed once.

### Input behavior

- `maxCompanies` limits the number of unique input companies processed. Invalid or unresolved inputs may reduce delivered records.
- `maxConcurrency` controls bounded batch and name-resolution concurrency; it is an advanced option and does not guarantee linear speedup.
- `companyNames` is optional best-effort exact-name resolution. For reliable bulk processing, use company URLs or slugs; ambiguous or unresolved names are skipped.
- Empty input completes with zero Dataset items.
- Valid company and Showcase pages are supported. Invalid slugs, 404 responses, and pages without a parseable company identity are skipped rather than emitted as fabricated records.

### Output example

```json
{
  "name": "OpenAI",
  "linkedinUrl": "https://www.linkedin.com/company/openai",
  "website": "https://openai.com",
  "description": "...",
  "industry": "Research Services",
  "companySize": "201-500 employees",
  "employeeCount": 350,
  "followerCount": 1200000,
  "headquarters": "San Francisco, California",
  "city": "San Francisco",
  "country": "United States",
  "specialties": ["Artificial Intelligence", "Research"],
  "logoUrl": "https://...",
  "scrapedAt": "2026-09-17T00:00:00.000Z"
}
```

Optional fields are omitted when LinkedIn does not expose them. Values such as follower counts can change between requests.

### Compatibility boundary

The URL workflow is compatible with common public LinkedIn company scraper inputs. This actor focuses on public firmographic data and does not claim compatibility with private or login-only company fields. Name resolution is intentionally conservative and only accepts an exact public suggestion match.

This is an independent tool and is not affiliated with or endorsed by LinkedIn.

### Pricing

The charge event is **$0.001 per successfully written company Dataset item** ($1 per 1,000). Platform usage is included. Invalid, duplicate, unresolved, and failed inputs do not create successful Dataset items and are not charged as results.

# Actor input Schema

## `companyUrls` (type: `array`):

LinkedIn company URLs or slugs. Valid company and Showcase pages are supported.

## `companyNames` (type: `array`):

Optional best-effort exact-name resolution. For reliable bulk delivery, use LinkedIn company URLs or slugs.

## `maxCompanies` (type: `integer`):

Maximum number of unique input companies to process. Invalid or unresolved inputs may reduce the number of delivered records.

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

Maximum number of company batches and name resolutions processed in parallel.

## Actor input object example

```json
{
  "companyUrls": [
    "https://www.linkedin.com/company/openai/"
  ],
  "companyNames": [],
  "maxCompanies": 100,
  "maxConcurrency": 3
}
```

# Actor output Schema

## `companies` (type: `string`):

No description

## `runSummary` (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 = {
    "companyUrls": [
        "https://www.linkedin.com/company/openai/"
    ],
    "companyNames": [
        "Microsoft"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("meka.im/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 = {
    "companyUrls": ["https://www.linkedin.com/company/openai/"],
    "companyNames": ["Microsoft"],
}

# Run the Actor and wait for it to finish
run = client.actor("meka.im/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 '{
  "companyUrls": [
    "https://www.linkedin.com/company/openai/"
  ],
  "companyNames": [
    "Microsoft"
  ]
}' |
apify call meka.im/linkedin-company-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,meka.im/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/m67Kz0NebrMPjgXzQ/builds/ow6sp5ZDsKMGgNebh/openapi.json