# LinkedIn Company Employees Scraper (`automationagents/linkedin-company-employees-export`) Actor

Export the employees of a target LinkedIn company as structured leads. Build account-based prospecting lists fast.

- **URL**: https://apify.com/automationagents/linkedin-company-employees-export.md
- **Developed by:** [Alex Jordan](https://apify.com/automationagents) (community)
- **Categories:** Lead generation
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.70 / 1,000 result blocks

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/platform/actors/running/actors-in-store#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

### What does LinkedIn Company Employees Export do?

**LinkedIn Company Employees Export** collects employee results for a target LinkedIn company using an authenticated session. It is useful for hiring research, org mapping, and lead generation workflows.

Built on the **Apify platform**, this Actor supports scheduling, webhooks, and dataset exports.

### Why use LinkedIn Company Employees Export?

- **Org mapping** - Export employee results for a target company
- **Lead generation** - Find people connected to a company search workflow
- **Automation-ready output** - Move results into spreadsheets, CRMs, or enrichment pipelines

### How to use LinkedIn Company Employees Export

1. Open the Actor on Apify
2. Enter the target company URL or company search input and authenticated session fields
3. Start the run
4. Review the dataset output

### Input

This Actor accepts the fields required to export LinkedIn employee results for a company.

#### Proxy object

Use the `proxy` object to define how requests should be routed. Common fields are:

- `ip` - Proxy host or endpoint URL
- `port` - Proxy port
- `username` - Proxy username
- `password` - Proxy password

**Example input:**

```json
{
  "liCompanyUrl": "https://www.linkedin.com/company/example-software/",
  "maxCountCompanyEmployees": 50,
  "li_at": "AQEDAR_EXAMPLE_SESSION_TOKEN",
  "JSESSIONID": "ajax:1234567890123456789",
  "bcookie": "v=2&example-browser-cookie",
  "bscookie": "v=1&example-secure-browser-cookie",
  "csrf-token": "ajax:1234567890123456789",
  "user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/145.0.0.0 Safari/537.36",
  "txSmSelfProfileUrl": "https://www.linkedin.com/in/example-self-profile/",
  "texAuVariables": {},
  "proxy": {
    "ip": "http://proxy.example.com",
    "port": "1080",
    "username": "user_example|session_demo",
    "password": "example_proxy_password"
  }
}
```

### Output

The Actor writes the collected company employee results to the default dataset.

**Example output:**

```json
{
  "success": true,
  "response": [
    {
      "fullName": "Avery Stone",
      "headline": "Revenue Operations Manager at Example Software",
      "profileUrl": "https://www.linkedin.com/in/avery-stone/",
      "companyName": "Example Software",
      "location": "Austin, Texas, United States",
      "timestamp": "2026-06-24T08:00:00.000Z"
    }
  ]
}
```

### Pricing / Cost estimation

**$0.0017 per started block of up to 50 results** on Apify.

- `1-50` results: `$0.0017`
- `51-100` results: `$0.0034`
- `101-150` results: `$0.0051`

No result means no result-charge event.

### Support

If you need adjustments for your workflow, use the Actor Issues tab or your internal support channel.

# Actor input Schema

## `liCompanyUrl` (type: `string`):

liCompanyUrl

## `maxCountCompanyEmployee` (type: `number`):

maxCountCompanyEmployee

## `li_at` (type: `string`):

li\_at

## `JSESSIONID` (type: `string`):

JSESSIONID

## `bcookie` (type: `string`):

bcookie

## `liap` (type: `string`):

liap

## `li_theme_set` (type: `string`):

li\_theme\_set

## `li_theme` (type: `string`):

li\_theme

## `timezone` (type: `string`):

timezone

## `bscookie` (type: `string`):

bscookie

## `user-agent` (type: `string`):

user-agent

## `timezoneOffset` (type: `string`):

timezoneOffset

## `csrf-token` (type: `string`):

csrf-token

## `User-Agent` (type: `string`):

User-Agent

## `x-li-track` (type: `string`):

x-li-track

## `x-li-lang` (type: `string`):

x-li-lang

## `X-Restli-Protocol-Version` (type: `string`):

X-Restli-Protocol-Version

## `txSmSelfProfileUrl` (type: `string`):

txSmSelfProfileUrl

## `proxy` (type: `object`):

proxy

## Actor input object example

```json
{}
```

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("automationagents/linkedin-company-employees-export").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 = {}

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

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

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

```

## CLI example

```bash
echo '{}' |
apify call automationagents/linkedin-company-employees-export --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=automationagents/linkedin-company-employees-export",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/DwSkal8T6z89Mhvha/builds/6bwknm7HknFuGfRXk/openapi.json