# LinkedIn Jobs Scraper — No Login, Full Job Details (`technicaldost/linkedin-jobs-scraper-no-login`) Actor

Scrape LinkedIn job postings without login or cookies: title, company, location, salary, posted date, applicants, seniority, employment type, industries and full description. Filter by date, remote/hybrid, job type and experience. $1 per 1,000 jobs.

- **URL**: https://apify.com/technicaldost/linkedin-jobs-scraper-no-login.md
- **Developed by:** [Technical Dost Solutions](https://apify.com/technicaldost) (community)
- **Categories:** Jobs, Lead generation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$1.00 / 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?

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 Jobs Scraper extracts job postings from LinkedIn's public job search, **without a LinkedIn account, cookies or login**. Search by keywords and location, filter by date posted, remote/hybrid/on-site, job type and experience level, and get every job with **title, company, location, salary (when published), posted date, number of applicants, seniority level, employment type, industries and the full job description**. Ideal for job boards, recruiters, sales teams tracking hiring signals and labour-market research.

### What you get

- No login, cookies or LinkedIn account needed: only public job listings are read.
- Full job details included: description (clean text and HTML), seniority level, employment type, job function, industries and applicant count.
- Filters: date posted (24 hours, week, month), workplace (remote, hybrid, on-site), job type, experience level, Easy Apply only, newest first.
- Several keywords and locations in one run, with de-duplication across searches.
- Or paste LinkedIn job search URLs from your browser, filters included.
- Pay only per job saved: $1 per 1,000 jobs.

### How to use LinkedIn Jobs Scraper

1. Enter **Keywords** such as `data engineer` or `marketing manager`.
2. Enter **Locations** (`United States`, `London`, `Remote`...).
3. Optionally set **Date posted**, **Workplace type**, **Job type** and **Experience level**.
4. Set **Maximum jobs per search** and run. Download results as Excel, CSV or JSON, or schedule the Actor daily to catch new jobs.

### Input example

```json
{
  "keywords": [
    "data engineer"
  ],
  "locations": [
    "United States"
  ],
  "maxJobs": 25,
  "datePosted": "past week"
}
```

All fields are described in the **Input** tab.

### Output example

```json
{
  "jobId": "4454862094",
  "title": "Senior Data Engineer, DX",
  "company": "Atlassian",
  "companyUrl": "https://au.linkedin.com/company/atlassian",
  "location": "Salt Lake City, UT",
  "salary": null,
  "postedAt": "2026-10-18",
  "postedText": "4 days ago",
  "benefits": "Actively Hiring",
  "applicants": 200,
  "applicantsText": "Over 200 applicants",
  "seniorityLevel": "Mid-Senior level",
  "employmentType": "Full-time",
  "jobFunction": null,
  "industries": "Software Development",
  "description": "Overview\nWorking at Atlassian\nAtlassians can choose where they work – whether in an office, from home, or a combination of the two...",
  "jobUrl": "https://www.linkedin.com/jobs/view/4454862094/",
  "searchKeyword": "data engineer",
  "searchLocation": "United States",
  "scrapedAt": "2026-10-22T23:05:00.000Z"
}
```

#### Output fields

| Field | Description |
|---|---|
| `jobId` | LinkedIn job ID. |
| `title` | Job title. |
| `company` | Hiring company. |
| `companyUrl` | Company's LinkedIn page. |
| `location` | Job location. |
| `salary` | Salary range when published. |
| `postedAt` | Date posted (YYYY-MM-DD). |
| `postedText` | Posted time as shown, e.g. 3 days ago. |
| `benefits` | Highlights such as Actively Hiring. |
| `applicants` | Number of applicants (approximate). |
| `applicantsText` | Applicant count as shown. |
| `seniorityLevel` | Seniority level. |
| `employmentType` | Employment type. |
| `jobFunction` | Job function. |
| `industries` | Industries. |
| `description` | Full job description as text. |
| `descriptionHtml` | Full job description as HTML. |
| `companyLogo` | Company logo URL. |
| `jobUrl` | Job posting URL. |
| `searchKeyword` | Keyword that found the job. |
| `searchLocation` | Location searched. |
| `scrapedAt` | Time of extraction. |

Export results as JSON, CSV, Excel, XML or HTML, or read them with the API.

### Use cases

- Feed a job board or newsletter with fresh postings every day.
- Recruiters and agencies: find open roles and the companies hiring for them.
- Sales teams: use hiring as a buying signal (for example companies hiring RevOps or data engineers).
- Salary and labour-market research by role, location and seniority.

### How much does LinkedIn Jobs Scraper cost?

This Actor uses **pay-per-event** pricing: **$0.001 per job** ($1 per 1,000). Platform usage is included. Full job details (description, seniority, applicants) are included in the price. Searches with no results are free.

Set **Maximum cost per run** in the run options to cap your spend; the Actor stops when the limit is reached.

### Use LinkedIn Jobs Scraper with AI agents (MCP)

Give Claude, ChatGPT, Cursor or any MCP client this Actor as a tool through the hosted [Apify MCP server](https://mcp.apify.com):

```bash
claude mcp add --transport http apify "https://mcp.apify.com/?tools=technicaldost/linkedin-jobs-scraper-no-login" --header "Authorization: Bearer YOUR_APIFY_TOKEN"
```

Or in a JSON MCP config:

```json
{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com/?tools=technicaldost/linkedin-jobs-scraper-no-login",
      "headers": { "Authorization": "Bearer YOUR_APIFY_TOKEN" }
    }
  }
}
```

The tool is named `technicaldost--linkedin-jobs-scraper-no-login`. Ask your agent, for example, to *"run LinkedIn Jobs Scraper with {"keywords": \["data engineer"], "locations": \["United States"], "maxJobs": 25, "datePosted": "past week"}"*.

### Run LinkedIn Jobs Scraper via API

```bash
curl -X POST "https://api.apify.com/v2/acts/technicaldost~linkedin-jobs-scraper-no-login/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"keywords": ["data engineer"], "locations": ["United States"], "maxJobs": 25, "datePosted": "past week"}'
```

```python
from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("technicaldost/linkedin-jobs-scraper-no-login").call(run_input={"keywords": ["data engineer"], "locations": ["United States"], "maxJobs": 25, "datePosted": "past week"})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)
```

```js
import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('technicaldost/linkedin-jobs-scraper-no-login').call({"keywords": ["data engineer"], "locations": ["United States"], "maxJobs": 25, "datePosted": "past week"});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);
```

### Integrations

Schedule runs (daily, hourly) in Apify Console and send results to Google Sheets, Slack, Make, Zapier, n8n, Airbyte or your own webhook.

### FAQ

#### Do I need a LinkedIn account or cookies?

No. The Actor reads LinkedIn's public job search, the same pages anyone can open without logging in. Your own account is never used, so it cannot be restricted.

#### How many jobs can I get per search?

Up to 1,000 per keyword and location, which is the most LinkedIn shows for one search. Use more specific keywords, locations or filters to cover more jobs.

#### Why is the salary empty for some jobs?

LinkedIn only shows a salary when the employer publishes one. The field is filled whenever it is shown publicly.

#### Can I get only new jobs every day?

Yes: set Date posted to Past 24 hours and schedule the Actor daily in Apify Console.

#### Is it legal to scrape this data?

The Actor collects publicly available information only and does not log in or bypass access controls. Use the data in line with the website's terms and the laws that apply to you, especially when processing personal data.

# Actor input Schema

## `keywords` (type: `array`):

Job titles or skills to search, e.g. data engineer, product manager. Each keyword runs in every location.

## `locations` (type: `array`):

Countries, cities or regions as you would type them on LinkedIn, e.g. United States, London, Germany. Leave empty for worldwide.

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

Maximum jobs to save for each keyword and location (LinkedIn shows up to 1,000).

## `datePosted` (type: `string`):

Only jobs posted within this period.

## `workplaceType` (type: `array`):

On-site, remote and/or hybrid.

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

Employment types to include.

## `experienceLevel` (type: `array`):

Seniority levels to include.

## `easyApplyOnly` (type: `boolean`):

Only jobs with LinkedIn Easy Apply.

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

Most relevant or most recent first.

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

Open each job to add the description, seniority, employment type, industries and applicant count. Turn off for faster runs with card data only (same price).

## `startUrls` (type: `array`):

LinkedIn job search URLs copied from your browser, e.g. https://www.linkedin.com/jobs/search/?keywords=python\&location=Berlin\&f_WT=2. Filters in the URL are kept.

## Actor input object example

```json
{
  "keywords": [
    "data engineer"
  ],
  "locations": [
    "United States"
  ],
  "maxJobs": 25,
  "datePosted": "any",
  "easyApplyOnly": false,
  "sortBy": "relevant",
  "includeDetails": true
}
```

# 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 = {
    "keywords": [
        "data engineer"
    ],
    "locations": [
        "United States"
    ],
    "maxJobs": 25
};

// Run the Actor and wait for it to finish
const run = await client.actor("technicaldost/linkedin-jobs-scraper-no-login").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 = {
    "keywords": ["data engineer"],
    "locations": ["United States"],
    "maxJobs": 25,
}

# Run the Actor and wait for it to finish
run = client.actor("technicaldost/linkedin-jobs-scraper-no-login").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 '{
  "keywords": [
    "data engineer"
  ],
  "locations": [
    "United States"
  ],
  "maxJobs": 25
}' |
apify call technicaldost/linkedin-jobs-scraper-no-login --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,technicaldost/linkedin-jobs-scraper-no-login"
        }
    }
}
```

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/HdxPU7d1qECrQOHoo/builds/tZSanQ3FnyPDYDGaR/openapi.json