# LinkedIn Job Library Scraper for Paid Jobs (`twocores/linkedin-job-library-scraper`) Actor

Extract LinkedIn paid job campaigns by company, payer, keyword, country and date, including descriptions, campaign dates, EU impressions and targeting.

- **URL**: https://apify.com/twocores/linkedin-job-library-scraper.md
- **Developed by:** [Two Cores](https://apify.com/twocores) (community)
- **Categories:** Jobs, Lead generation, Marketing
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $3.00 / 1,000 job campaigns

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 Job Library Scraper

Extract paid and promoted job campaign data from LinkedIn's public Job Library. Search by company, payer, keyword, country and date, then export clean records to JSON, CSV, Excel or any other Apify dataset format.

No LinkedIn account, cookies or login credentials are required.

### What you can collect

Every result includes:

- LinkedIn job ID
- Job title, company and location
- Promoted status and Job Library URL
- Company page and logo when available
- Payer and campaign run dates
- Full job description in text and HTML
- EU impression estimates and targeting parameters when LinkedIn publishes them
- Source query and scrape timestamp

The Actor writes one flat dataset item per job, making the results straightforward to export, deduplicate and load into a database.

Each saved job is one billable dataset item. Apify displays the current per-item price and maximum run charge before the run starts.

### Common uses

- Monitor which companies are paying to promote hiring campaigns
- Track hiring demand by job family, employer or country
- Compare advertised roles across competitors
- Research recruitment advertising and employer-brand activity
- Study EU job-ad targeting and impression disclosures
- Build recurring hiring-intelligence datasets

### Input

Use any combination of the following filters:

| Field | Description |
| --- | --- |
| `organizationName` | Company name |
| `payer` | Organization paying for the campaign |
| `keyword` | Keyword or job title |
| `countries` | ISO two-letter country codes, or `ALL` by itself |
| `dateOption` | Standard LinkedIn range or a custom range |
| `startDate`, `endDate` | Custom dates in `YYYY-MM-DD` format |
| `sortOrder` | `newest` or `oldest` |
| `maxResults` | Maximum number of unique jobs to save |
| `includeDetails` | Fetch descriptions, payer, dates, impressions and targeting |
| `proxyConfiguration` | Optional Apify Proxy configuration |

Example:

```json
{
  "keyword": "software engineer",
  "countries": ["GB", "DE"],
  "dateOption": "last-30-days",
  "sortOrder": "newest",
  "maxResults": 100,
  "includeDetails": true
}
```

### Example result

```json
{
  "jobId": "4448271117",
  "title": "Software Engineer",
  "company": "Example Ltd",
  "location": "London, England, United Kingdom",
  "promoted": true,
  "payer": "Example Ltd",
  "ranFrom": "2026-08-03",
  "isActive": true,
  "descriptionText": "Build and operate dependable software...",
  "detailUrl": "https://www.linkedin.com/ad-library/job/detail/4448271117",
  "detailStatus": "success",
  "scrapedAt": "2026-08-05T15:00:00.000Z"
}
```

### Reliability

The Actor uses LinkedIn's server-rendered public Job Library pages rather than browser automation. It includes bounded concurrency, request retries, session and cookie persistence, pagination deduplication, optional Apify Proxy support and a fallback summary record when an individual detail page fails.

If LinkedIn publishes no impression or targeting data for a campaign, those optional fields are omitted rather than guessed.

### Responsible use

This Actor accesses public transparency information. You are responsible for using the data in accordance with applicable laws, LinkedIn's terms and the rights of individuals represented in downstream datasets. Do not use it for unlawful discrimination, spam or intrusive profiling.

LinkedIn is a trademark of LinkedIn Corporation. This Actor is independently developed and is not affiliated with or endorsed by LinkedIn.

### Support

Open an issue from the Actor's Issues tab in Apify Console. Include the run ID and a small input example so the problem can be reproduced.

# Changelog

This Actor's version history is a separate document: https://apify.com/twocores/linkedin-job-library-scraper/changelog.md

# Actor input Schema

## `organizationName` (type: `string`):

Return jobs promoted by companies whose names match this value.

## `payer` (type: `string`):

Return job campaigns paid for by an organization matching this value.

## `keyword` (type: `string`):

Search job titles and descriptions for a keyword.

## `countries` (type: `array`):

ISO 3166-1 alpha-2 country codes. Use ALL by itself for all countries.

## `dateOption` (type: `string`):

Filter campaigns by one of LinkedIn's standard date ranges. Select custom to use the start and end date fields.

## `startDate` (type: `string`):

Inclusive start date in YYYY-MM-DD format. Required for a custom range.

## `endDate` (type: `string`):

Inclusive end date in YYYY-MM-DD format. Required for a custom range.

## `sortOrder` (type: `string`):

Order campaigns by their first run date.

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

Stop after this many unique jobs have been added to the dataset.

## `includeDetails` (type: `boolean`):

Fetch descriptions, payer, campaign dates, impressions and targeting data when available.

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

Maximum number of LinkedIn pages fetched at once. Lower this if the source starts throttling requests.

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

Optional Apify Proxy configuration. Direct requests are used by default.

## Actor input object example

```json
{
  "keyword": "software engineer",
  "countries": [
    "GB"
  ],
  "dateOption": "last-30-days",
  "sortOrder": "newest",
  "maxResults": 10,
  "includeDetails": true,
  "maxConcurrency": 5,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}
```

# Actor output Schema

## `jobs` (type: `string`):

Flat job campaign records from the default dataset.

## `dataset` (type: `string`):

Default dataset page in Apify Console.

## `summary` (type: `string`):

Counts, source totals and the normalized query for this run.

# 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 = {
    "keyword": "software engineer",
    "countries": [
        "GB"
    ],
    "maxResults": 10
};

// Run the Actor and wait for it to finish
const run = await client.actor("twocores/linkedin-job-library-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 = {
    "keyword": "software engineer",
    "countries": ["GB"],
    "maxResults": 10,
}

# Run the Actor and wait for it to finish
run = client.actor("twocores/linkedin-job-library-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 '{
  "keyword": "software engineer",
  "countries": [
    "GB"
  ],
  "maxResults": 10
}' |
apify call twocores/linkedin-job-library-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,twocores/linkedin-job-library-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/yd5rBcl9f6by4UuUq/builds/v4sgNJf8Z7syM68Gp/openapi.json