# Linkedin Jobs Guest Scraper (`outstanding_vegetable/linkedin-jobs-guest-scraper`) Actor

- **URL**: https://apify.com/outstanding\_vegetable/linkedin-jobs-guest-scraper.md
- **Developed by:** [Peter Skotte](https://apify.com/outstanding_vegetable) (community)
- **Categories:** Jobs, Business, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.50 / 1,000 jobs

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 Jobs Scraper — no login, full details, salary as numbers, dead-listing check

Search LinkedIn jobs by keyword and location using LinkedIn's own filters, and get every job with
the data the search page hides: the **full description**, seniority level, employment type, job
function, industries, **applicant count**, **salary parsed to numbers**, and whether the listing is
**still live**. Uses LinkedIn's public guest endpoints, so there is no login, no cookies, nothing to get
banned.

### What makes this one different

Most LinkedIn job scrapers return the search card: title, company, location, link. This one opens each
job (optional, on by default) and adds:

- **Salary as numbers** — `salaryMin`, `salaryMax`, `salaryCurrency`, `salaryPeriod`, parsed from
  LinkedIn's salary field or, when the company only writes it in the description, from the description.
- **Applicant count** — "Over 200 applicants" and the number 200.
- **Live check** — `isLive` is `false` when LinkedIn reports the job closed, so stale listings never
  reach your pipeline.
- **Apply URL** — the external application link when the company uses its own ATS.

### Input

| Field | Default | Notes |
|---|---|---|
| `keywords` | `python developer` | |
| `location` | `Austin, Texas` | City, region or country |
| `postedWithin` | `any` | `day`, `week`, `month` |
| `workplace` | all | `onsite`, `remote`, `hybrid` |
| `jobType` | all | `fulltime`, `parttime`, `contract`, `temporary`, `internship`, `volunteer` |
| `experience` | all | `internship`, `entry`, `associate`, `mid-senior`, `director`, `executive` |
| `sortBy` | `relevance` | or `recent` |
| `fetchDetails` | `true` | Off = cards only, one request per 25 jobs |
| `maxItems` | `10` | LinkedIn serves at most ~1,000 per search |

### Output

```json
{
  "jobId": "4436943086",
  "title": "Senior Backend Engineer",
  "jobUrl": "https://www.linkedin.com/jobs/view/4436943086",
  "companyName": "Kizen",
  "companyUrl": "https://www.linkedin.com/company/growwithkizen",
  "companyLogo": "https://media.licdn.com/dms/image/…",
  "location": "Austin, TX",
  "postedAt": "2026-09-06", "postedText": "10 hours ago",
  "salaryText": "OTE $207,000-$253,000", "salaryMin": 207000, "salaryMax": 253000, "salaryCurrency": "$", "salaryPeriod": "year",
  "seniorityLevel": "Not Applicable", "employmentType": "Full-time",
  "jobFunction": "Engineering and Information Technology", "industries": "Technology, Information and Internet",
  "applicantsText": "Over 200 applicants", "applicants": 200,
  "description": "Location: Austin (Domain), TX (In-office 4x per week) …",
  "descriptionHtml": "<strong>Location:</strong> Austin …",
  "applyUrl": "https://jobs.ashbyhq.com/kizen/…",
  "isLive": true, "detailsFetched": true,
  "searchKeywords": "python developer", "searchLocation": "Austin, Texas",
  "scrapedAt": "2026-09-06T21:00:00.000Z"
}
```

### Use cases

Job-market research and salary benchmarking, recruiting lead lists (companies hiring for a role, with
their ATS), competitor hiring monitoring, and feeding job boards and aggregators with listings that are
verified live.

### Notes

- Salary numbers come from LinkedIn's field when present, otherwise from a compensation sentence in the
  description; `salaryText` shows the source text so you can check it.
- LinkedIn caps a search at ~1,000 results. Split by location or posting window for full coverage.

# Actor input Schema

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

Job title, skill or company, e.g. python developer, product manager, nurse.

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

City, region or country as you would type it on LinkedIn, e.g. 'Austin, Texas', 'London', 'Germany', 'United States'.

## `postedWithin` (type: `string`):

Only jobs posted in this window.

## `workplace` (type: `array`):

On-site, remote, hybrid. Leave empty for all.

## `jobType` (type: `array`):

Leave empty for all.

## `experience` (type: `array`):

Leave empty for all.

## `sortBy` (type: `string`):

Relevance or most recent.

## `fetchDetails` (type: `boolean`):

Open each job to get the full description, seniority, employment type, job function, industries, applicant count and salary. Also confirms the listing is still live. Costs one extra request per job.

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

LinkedIn returns at most ~1,000 jobs per search (40 pages of 25). Narrow keywords or location for full coverage.

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

Residential proxy is required.

## Actor input object example

```json
{
  "keywords": "python developer",
  "location": "Austin, Texas",
  "postedWithin": "any",
  "workplace": [],
  "jobType": [],
  "experience": [],
  "sortBy": "relevance",
  "fetchDetails": true,
  "maxItems": 10,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ],
    "apifyProxyCountry": "US"
  }
}
```

# Actor output Schema

## `records` (type: `string`):

Dataset of scraped job listings (JSON).

# 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("outstanding_vegetable/linkedin-jobs-guest-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 = {}

# Run the Actor and wait for it to finish
run = client.actor("outstanding_vegetable/linkedin-jobs-guest-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 '{}' |
apify call outstanding_vegetable/linkedin-jobs-guest-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,outstanding_vegetable/linkedin-jobs-guest-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/D7L92hFXNunfjGHP5/builds/tLsqheDYQlYAsjAML/openapi.json