# Linkedin Jobs Scraper (`hungryai/apify-scraper-linkedin`) Actor

LinkedIn job scraper powered by Playwright and Apify. Collects job URLs, titles, companies, locations, descriptions, and optional AI-generated summaries. Perfect for hiring pipelines, automation workflows, and data-driven analysis.

- **URL**: https://apify.com/hungryai/apify-scraper-linkedin.md
- **Developed by:** [Bhavesh Walankar](https://apify.com/hungryai) (community)
- **Categories:** AI, Automation, Agents
- **Stats:** 35 total users, 1 monthly users, 0.0% runs succeeded, 2 bookmarks
- **User rating**: No ratings yet

## Pricing

$10.00 / 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?

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 Job Scraper (Apify Actor)

This Apify actor scrapes **job listings from LinkedIn** based on keywords, location, and optional skills.\
It outputs clean job links into both a dataset (on Apify) and a CSV file (`jobs.csv`) for local usage.

***

### 🚀 How it Works

- The actor builds a LinkedIn Jobs search URL from:
  - **Keywords**
  - **Location**
  - **Optional Skills**
- It sends a request to LinkedIn, extracts job links from the results, and removes duplicates.
- Results are saved to:
  - Apify Dataset (when running on Apify)
  - `jobs.csv` file (when running locally)

> ✅ On Apify: Each job link is pushed to the default dataset.\
> ✅ Locally: A `jobs.csv` file is generated in your working directory.

***

### 📊 What Data You Get

For each job found, the scraper collects:

- 🔗 **Job posting URL**

This actor focuses on collecting **job links** for further enrichment.\
You can chain it with other scrapers or workflows to extract full job descriptions, company details, and applicant requirements.

***

### ⚙️ Getting Started

#### 1. Run on Apify

1. Add the actor to your Apify console.
2. Provide input:
   ```json
   {
     "keywords": "Data Scientist",
     "location": "USA",
     "maxJobs": 20,
     "skills": "Python, SQL"
   }
   ```

# Actor input Schema

## `keywords` (type: `string`):

Search keywords or phrases (separate by newline or commas). Example: medical billing
mental health

## `location` (type: `string`):

Target location for job search.

## `maxJobs` (type: `integer`):

Maximum number of job links to collect for a run.

## `skills` (type: `string`):

Optional skills to narrow results (e.g., Python, FHIR).

## `days` (type: `integer`):

Include jobs posted within the last N days (0 to ignore).

## Actor input object example

```json
{
  "keywords": "medical billing\nmental health",
  "location": "United States",
  "maxJobs": 50,
  "skills": "",
  "days": 3
}
```

# 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("hungryai/apify-scraper-linkedin").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("hungryai/apify-scraper-linkedin").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 '{}' |
apify call hungryai/apify-scraper-linkedin --silent --output-dataset

```

## MCP server setup

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

```

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/umWOjFtkc7Id6qcBp/builds/sTqufXY2NLjr1D09n/openapi.json