# LinkedIn Jobs Scraper (`agentx/linkedin-jobs-scraper`) Actor

LinkedIn Jobs Scraper is a LinkedIn jobs scraper for 98 countries that returns 41 structured job, salary, company, application, and public contact fields without login.

- **URL**: https://apify.com/agentx/linkedin-jobs-scraper.md
- **Developed by:** [AgentX](https://apify.com/agentx) (community)
- **Categories:** Jobs, Lead generation, Agents
- **Stats:** 488 total users, 60 monthly users, 99.9% runs succeeded, 9 bookmarks
- **User rating**: 5.00 out of 5 stars

## Pricing

from $2.10 / 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.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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 is a linkedin jobs scraper that searches 98 LinkedIn country choices and returns 41 structured job, salary, company, application, and public contact fields.** It is built for recruiting research, workforce intelligence, job products, and repeatable data workflows.

[![Apify Users](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.apify.com%2Fv2%2Facts%2Fagentx~linkedin-jobs-scraper\&query=%24.data.stats.totalUsers\&style=for-the-badge\&label=Apify%20Users\&color=ff9013)](https://apify.com/agentx/linkedin-jobs-scraper) [![Apify Runs](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.apify.com%2Fv2%2Facts%2Fagentx~linkedin-jobs-scraper\&query=%24.data.stats.totalRuns\&style=for-the-badge\&label=Apify%20Runs\&color=ff9013)](https://apify.com/agentx/linkedin-jobs-scraper) [![Price](https://img.shields.io/badge/%240.00280%20%2F%20result-4285f4?style=for-the-badge)](https://apify.com/agentx/linkedin-jobs-scraper/pricing) [![Capability](https://img.shields.io/badge/98%20countries-34a853?style=for-the-badge)](https://console.apify.com/actors/nmdyrR62YooFl1bBS/input) [![API + MCP ready](https://img.shields.io/badge/API%20%2B%20MCP%20ready-fbbc05?style=for-the-badge)](https://apify.com/agentx/linkedin-jobs-scraper/api)

- **98 countries in the public search contract.**
- **9 public inputs with 3 required.**
- **41 normalized Dataset fields.**
- **$0.00280 per Result on FREE plus a $0.01000 minimum Actor Start event.**

The smallest useful test sets `max_results` to `1` and costs $0.01280 on FREE when one Result is published and one Actor Start event is charged.

### Why Choose LinkedIn Jobs Scraper

**Source-focused coverage.** LinkedIn Jobs Scraper searches 98 LinkedIn country choices while keeping the public source URL on every accepted record, so reviewers can trace individual listings.

**A stable 41-field contract.** Job content, location, salary, company, application, contact, and processing fields use the same names across repeat runs. Source omissions stay empty instead of being filled with guesses.

**Explicit filter boundaries.** Location, distance, recency, remote, and employment-type inputs can be combined for the public job search. Optional inputs affect a request only when supplied.

**Low-risk evaluation.** One result is enough to inspect relevance, salary coverage, employer detail, and application URLs before increasing volume or adding a schedule.

**Apify delivery surfaces.** The same input works through Console, API clients, Datasets, schedules, webhooks, and MCP without changing the result schema.

LinkedIn's [official filter documentation](https://www.linkedin.com/help/linkedin/answer/a507441/filter-and-sort-job-search-results?lang=en) describes location, date, employment type, and other filters used by its job search.

### Quick Start Guide

#### Step 1: Configure

Open the Actor input, keep the prefilled working values or use the shared Business Analyst scenario, and set only fields listed in Input Parameters.

#### Step 2: Run

Start with `max_results: 1`. The limit is the maximum number of published jobs for this single-platform Actor.

#### Step 3: Collect

Inspect the default Dataset, especially `platform_url`, `official_url`, nullable salary fields, `company_name`, and `processed_at`. Export JSON, CSV, Excel, XML, or another Apify-supported Dataset format after the shape fits the workflow.

### Input Parameters

LinkedIn Jobs Scraper exposes 9 public inputs in schema order, with 3 required and every other filter optional.

| Parameter | Type | Required | Description | Example |
| --- | --- | :---: | --- | --- |
| `max_results` | integer | Yes | Maximum number of LinkedIn job results to return. | `12` |
| `keyword` | string | Yes | Job title, skill, or company search term sent to LinkedIn. | `Machine Learning Engineer` |
| `country` | select | Yes | Country used for the LinkedIn search endpoint. | `Japan` |
| `location` | string | No | City, area, or postal code used for the LinkedIn search. | — |
| `posted_since` | date | No | Earliest posting date requested from LinkedIn where supported. | — |
| `remote_only` | boolean | No | Request only remote roles from LinkedIn where supported. | — |
| `distance` | integer | No | Search radius in miles around the LinkedIn location. | — |
| `job_type` | select | No | Employment type requested from LinkedIn. | — |
| `currency` | select | No | Optional target currency for converting salary amounts returned by LinkedIn. | — |

`country` has 98 accepted values; `job_type` has 5 accepted values; `currency` has 166 accepted values. Inputs are prefilled with a working example, while optional fields without values stay non-restrictive.

Shared scenario:

```json
{
  "max_results": 1,
  "keyword": "Business Analyst",
  "country": "France",
  "location": "Paris",
  "currency": "USD"
}
```

### Output Data Schema

Each Dataset item represents one accepted public job listing in a 41-field schema, with missing source values left empty.

| Field group | Fields |
| --- | --- |
| Source and links | `platform`, `platform_url`, `official_url` |
| Job identity | `title`, `description`, `job_type`, `job_level`, `job_function`, `listing_type`, `skills`, `experience_range` |
| Dates and availability | `posted_date`, `valid_through`, `applicant_count`, `vacancy_count` |
| Location and work mode | `location`, `is_remote`, `work_mode` |
| Compensation | `salary_period`, `salary_minimum`, `salary_maximum`, `salary_currency` |
| Application | `easy_apply` |
| Company | `company_name`, `company_type`, `company_founded`, `company_industry`, `company_url`, `company_website`, `company_logo`, `company_addresses`, `company_revenue`, `company_description`, `company_rating`, `employee_count`, `review_count` |
| Public contact signals | `emails`, `phones`, `social_links` |
| Processing metadata | `processor`, `processed_at` |

The following JSON is abbreviated and illustrative; a real item uses all 41 public field names even when some values are null:

```json
{
  "platform": "LinkedIn",
  "platform_url": "https://example.com/linkedin-jobs-scraper/listing-123",
  "official_url": null,
  "title": "Business Analyst",
  "location": {
    "raw": "Paris",
    "country": "France"
  },
  "salary_minimum": null,
  "salary_maximum": null,
  "salary_currency": null,
  "company_name": "Example Employer",
  "processed_at": "2026-08-10T12:00:00.000Z"
}
```

Results can be exported through Apify Datasets in JSON, CSV, Excel, XML, RSS, and other supported formats.

### Integration Examples

Call LinkedIn Jobs Scraper with public Actor ID `nmdyrR62YooFl1bBS` or name form `agentx/linkedin-jobs-scraper`; every example uses the same Business Analyst scenario.

#### Actor ID

```text
nmdyrR62YooFl1bBS
```

#### HTTP

```bash
curl -X POST "https://api.apify.com/v2/acts/nmdyrR62YooFl1bBS/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"max_results":1,"keyword":"Business Analyst","country":"France","location":"Paris","currency":"USD"}'
```

#### Python

```python
from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("nmdyrR62YooFl1bBS").call(run_input={'max_results': 1, 'keyword': 'Business Analyst', 'country': 'France', 'location': 'Paris', 'currency': 'USD'})
items = client.dataset(run["defaultDatasetId"]).list_items().items
```

#### JavaScript

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

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('nmdyrR62YooFl1bBS').call({"max_results": 1, "keyword": "Business Analyst", "country": "France", "location": "Paris", "currency": "USD"});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
```

#### Make.com and n8n

Use the Apify module or node with Actor ID `nmdyrR62YooFl1bBS`, paste the same JSON input, wait for completion, and read the default Dataset. Store the Apify token in the platform's credential manager.

#### MCP

```json
{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com?tools=agentx/linkedin-jobs-scraper",
      "headers": {"Authorization": "Bearer <APIFY_TOKEN>"}
    }
  }
}
```

Use the [API page](https://apify.com/agentx/linkedin-jobs-scraper/api) for generated SDK and OpenAPI examples.

### Pricing

LinkedIn Jobs Scraper costs $0.00280 per Result on FREE plus $0.01000 per minimum Actor Start event; one published-result test totals $0.01280.

| Event or tier | Price | Billing unit |
| --- | ---: | --- |
| Actor Start | $0.01000 | One event per GB of selected memory, minimum one |
| FREE Result | $0.00280 | One default Dataset item |
| BRONZE Result | $0.00252 | One default Dataset item |
| SILVER Result | $0.00224 | One default Dataset item |
| GOLD Result | $0.00210 | One default Dataset item |
| PLATINUM Result | $0.00210 | One default Dataset item |
| DIAMOND Result | $0.00210 | One default Dataset item |

Smallest run: $0.01000 + 1 × $0.00280 = **$0.01280**. A representative 100-result FREE run with one minimum start event is $0.01000 + 100 × $0.00280 = **$0.29000**. Batched results share the run start instead of paying a new start for each item. [Prices can change; check live pricing](https://apify.com/agentx/linkedin-jobs-scraper/pricing).

### Use Cases

**Role-demand monitoring by country, city, function, and seniority.** Use the documented filters to define the cohort, retain `platform_url` for traceability, and compare only fields actually published by LinkedIn. Start with a one-result run before turning the input into a recurring workflow.

**Hiring-intent analysis using company and posted-role signals.** Use the documented filters to define the cohort, retain `official_url` for traceability, and compare only fields actually published by LinkedIn. Start with a one-result run before turning the input into a recurring workflow.

**Recurring LinkedIn vacancy alerts with source URLs.** Use the documented filters to define the cohort, retain `processed_at` for traceability, and compare only fields actually published by LinkedIn. Start with a one-result run before turning the input into a recurring workflow.

**Compensation comparisons from disclosed salary fields.** Use the documented filters to define the cohort, retain `company_name` for traceability, and compare only fields actually published by LinkedIn. Start with a one-result run before turning the input into a recurring workflow.

**Job-product ingestion with normalized role taxonomy.** Use the documented filters to define the cohort, retain `salary_currency` for traceability, and compare only fields actually published by LinkedIn. Start with a one-result run before turning the input into a recurring workflow.

### Alternatives

Manual LinkedIn browsing is reasonable for checking a handful of listings, reading final descriptions, and making application decisions. It becomes difficult to repeat when a team needs structured snapshots, nullable fields, exports, or scheduled delivery.

The source's own search is the best choice for interactive discovery, account features, saved jobs, alerts, and applications. LinkedIn Jobs Scraper is the better fit when the requirement is a repeatable Dataset and API/MCP delivery; it does not replace the source experience or claim affiliation.

An unnamed multi-source job-data service may suit teams that want a vendor-managed feed with a broader commercial contract. A custom integration offers maximum control but leaves source changes, normalization, retries, storage, and monitoring with the engineering team.

Choose something else if the project needs private candidate profiles, resume databases, automated applications, guaranteed field completeness, historical vacancies that are no longer public, or a legal determination about downstream use.

### Limits and Troubleshooting

The main limits come from live public source inventory and the Actor-specific input contract.

- **Public search can expose fewer jobs than the result cap; broaden the query** — Treat this as expected source behavior, not a promise that the cap will be filled; first verify the same search on the source and then broaden only the restrictive input.
- **Applicant counts, salary, skills, and seniority are not visible on every listing** — Keep the unsupported dimension out of the request and, when it matters analytically, filter the normalized Dataset after collection.
- **A separate employer application URL may be absent; keep `platform_url` for attribution** — Reproduce the condition with `max_results: 1`, preserve the exact input, and use the source URL to distinguish a parser problem from changing source inventory.
- **Listings can close or change between snapshots** — Model nullable values explicitly in downstream storage and calculations; an absent value must not be converted into zero or a fabricated category.
- **No private profile, resume, messaging, or application data is collected** — For scheduled monitoring, store `processed_at` and source URLs, expect listings to change, and compare snapshots instead of assuming a permanent record.

For a reproducible issue, run `max_results: 1` with the exact keyword and country, then open [Apify Issues](https://apify.com/agentx/linkedin-jobs-scraper/issues) with the run URL, expected behavior, and affected source. Never include an API token or private data.

### Trust and Reliability

Apify records each run, Dataset, input, status, and billed event under the user's account. This Actor declares one Result event per default Dataset item and an Actor Start event tied to selected memory.

The documented Dataset contract contains 41 fields, keeps source URLs, and leaves unavailable public values empty. The Actor does not guarantee relevance, inventory, salary coverage, company completeness, or contact availability that the source does not publish.

### Legal and Compliance

**Data scope.** The Actor collects accessible public job and employer information; it does not request source-account credentials or private candidate data.

**User responsibility.** Review applicable laws, source terms, database rights, privacy obligations, and retention rules for every country and workflow. This documentation is not legal advice.

**Responsible use.** Keep attribution where required, verify listings before acting, protect stored data, and do not use public contact fields for spam, unlawful profiling, or discriminatory decisions.

### Frequently Asked Questions

#### How do I scrape linkedin jobs by keyword and location?

Set the required `max_results`, `keyword`, and `country` values, add only supported optional filters, and inspect a one-result Dataset before scaling.

#### Can I use this as a linkedin job postings api?

Yes. The Actor can be called by API or MCP and returns normalized Dataset items; it is independent of LinkedIn and does not claim official affiliation.

#### Does LinkedIn Jobs Scraper require source credentials?

No source username, password, cookie, or API key is a public input. Apify authentication is required for API and MCP execution.

#### Why are salary, company, or contact fields empty?

Those fields depend on public source and employer pages. Empty means unavailable, not zero, and the Actor does not invent missing values.

#### Is there a free jobs API?

The Actor uses pay-per-event pricing under your Apify plan. Start with the one-result calculation in Pricing to measure relevance and populated fields before increasing volume.

#### Can I schedule runs to monitor LinkedIn jobs over time?

Yes. Use Apify schedules after testing the input, and retain `processed_at` plus source URLs because listings can update, close, or reappear.

#### How does Result billing work?

Each item written to the default Dataset bills one Result event. Actor Start event count depends on memory, with a minimum of one event per run.

### Related AgentX Actors

AgentX publishes 77 Actors; the three closest choices appear first, followed by the complete catalog grouped by category.

Closest to this Actor:

- [All Jobs Scraper](https://apify.com/agentx/all-jobs-scraper) — multi-board coverage.
- [Indeed Jobs Scraper](https://apify.com/agentx/indeed-jobs-scraper) — Indeed market search.
- [Glassdoor Jobs Scraper](https://apify.com/agentx/glassdoor-jobs-scraper) — employer ratings and salary context.

#### Business and Market Intelligence

- **[All Web Search Scraper](https://apify.com/agentx/all-web-search-scraper)** — multi-engine web search across ten independent indexes
- **[Google Keyword Trends](https://apify.com/agentx/google-keyword-trends)** — Google Trends keyword interest, compared five at a time
- **[Google Trends Scraper](https://apify.com/agentx/google-trends-scraper)** — Google Trends trending searches
- **[Google Maps Store Scraper](https://apify.com/agentx/google-maps-store-scraper)** — Google Maps business listings
- **[LinkedIn Company Lookup](https://apify.com/agentx/linkedin-company-lookup)** — LinkedIn company records
- **[LinkedIn Profile Lookup](https://apify.com/agentx/linkedin-profile-lookup)** — LinkedIn profile records
- **[Weather Forecast API](https://apify.com/agentx/weather-forecast-api)** — forecast and historical weather data

#### Jobs and Hiring

- **[All Jobs Scraper](https://apify.com/agentx/all-jobs-scraper)** — multi-platform job listings
- **[Bayt Jobs Scraper](https://apify.com/agentx/bayt-jobs-scraper)** — Bayt job listings
- **[Glassdoor Jobs Scraper](https://apify.com/agentx/glassdoor-jobs-scraper)** — Glassdoor job listings
- **[Indeed Jobs Scraper](https://apify.com/agentx/indeed-jobs-scraper)** — Indeed job listings
- **[JobStreet Company Profile](https://apify.com/agentx/jobstreet-company-profile)** — JobStreet employer records
- **[Jooble Jobs Scraper](https://apify.com/agentx/jooble-jobs-scraper)** — Jooble job listings
- **[Naukri Jobs Scraper](https://apify.com/agentx/naukri-jobs-scraper)** — Naukri job listings
- **[Talent Jobs Scraper](https://apify.com/agentx/talent-jobs-scraper)** — Talent.com job listings
- **[ZipRecruiter Jobs Scraper](https://apify.com/agentx/ziprecruiter-jobs-scraper)** — ZipRecruiter job listings

#### Social Media

- **[All Forums Thread Scraper](https://apify.com/agentx/all-forums-thread-scraper)** — multi-platform forum and Q\&A threads
- **[Instagram Creator Scraper](https://apify.com/agentx/instagram-creator-scraper)** — Instagram creator profiles
- **[Instagram Reels Scraper](https://apify.com/agentx/instagram-reels-scraper)** — Instagram Reels metadata
- **[Instagram Trending Scraper](https://apify.com/agentx/instagram-trending-scraper)** — Instagram trending content
- **[Medium Scraper](https://apify.com/agentx/medium-scraper)** — Medium articles
- **[Medium Profile Scraper](https://apify.com/agentx/medium-profile-scraper)** — Medium author profiles
- **[Reddit Profile Scraper](https://apify.com/agentx/reddit-profile-scraper)** — Reddit user profiles
- **[Reddit Viral Scraper](https://apify.com/agentx/reddit-viral-scraper)** — Reddit viral posts
- **[SubReddit Info Scraper](https://apify.com/agentx/subreddit-info-scraper)** — subreddit metadata
- **[Subreddit Members Scraper](https://apify.com/agentx/subreddit-members-scraper)** — subreddit member lists
- **[Subreddit Posts Scraper](https://apify.com/agentx/subreddit-posts-scraper)** — subreddit post feeds
- **[Telegram Chat Scraper](https://apify.com/agentx/telegram-chat-scraper)** — Telegram chat messages
- **[Telegram Info Scraper](https://apify.com/agentx/telegram-info-scraper)** — Telegram channel metadata
- **[Telegram Member Adder](https://apify.com/agentx/telegram-member-adder)** — Telegram group membership management
- **[Telegram Member Scraper](https://apify.com/agentx/telegram-member-scraper)** — Telegram group members
- **[Telegram Private Group Scraper](https://apify.com/agentx/telegram-private-group-scraper)** — private Telegram group data
- **[TikTok Creator API](https://apify.com/agentx/tiktok-creator-api)** — TikTok creator profiles
- **[TikTok User Lookup](https://apify.com/agentx/tiktok-user-lookup)** — TikTok account records
- **[X Twitter Community API](https://apify.com/agentx/x-twitter-community-api)** — X community data
- **[X Twitter Profile Lookup](https://apify.com/agentx/x-twitter-profile-lookup)** — X profile records
- **[YouTube Creator Email Scraper](https://apify.com/agentx/youtube-creator-email-scraper)** — YouTube creator contact data

#### Video, Transcripts and Downloads

- **[All Video Scraper](https://apify.com/agentx/all-video-scraper)** — multi-platform video metadata
- **[Video Transcript](https://apify.com/agentx/video-transcript)** — multi-platform transcripts
- **[Video Captions Downloader](https://apify.com/agentx/video-captions-downloader)** — caption files
- **[Video to Social Post](https://apify.com/agentx/video-to-social-post)** — video repurposed into social copy
- **[YouTube Transcript](https://apify.com/agentx/youtube-transcript)** — YouTube transcripts
- **[TikTok Transcript](https://apify.com/agentx/tiktok-transcript)** — TikTok transcripts
- **[X Twitter Transcript](https://apify.com/agentx/x-twitter-transcript)** — X video transcripts
- **[Facebook Transcript](https://apify.com/agentx/facebook-transcript)** — Facebook video transcripts
- **[Bilibili Transcript](https://apify.com/agentx/bilibili-transcript)** — Bilibili transcripts
- **[Dailymotion Transcript](https://apify.com/agentx/dailymotion-transcript)** — Dailymotion transcripts
- **[Rutube Transcript](https://apify.com/agentx/rutube-transcript)** — Rutube transcripts
- **[Loom Transcript](https://apify.com/agentx/loom-transcript)** — Loom transcripts
- **[Wistia Transcript](https://apify.com/agentx/wistia-transcript)** — Wistia transcripts
- **[Instagram Reels Downloader](https://apify.com/agentx/instagram-reels-downloader)** — Reels downloads
- **[Kick Clip Downloader](https://apify.com/agentx/kick-clip-downloader)** — Kick clip downloads
- **[Linkedin Video Downloader](https://apify.com/agentx/linkedin-video-downloader)** — LinkedIn video downloads
- **[Pinterest Video Downloader](https://apify.com/agentx/pinterest-video-downloader)** — Pinterest video downloads
- **[Reddit Video Downloader](https://apify.com/agentx/reddit-video-downloader)** — Reddit video downloads
- **[Snapchat Video Downloader](https://apify.com/agentx/snapchat-video-downloader)** — Snapchat video downloads
- **[TED Talk Downloader](https://apify.com/agentx/ted-talk-downloader)** — TED talk downloads
- **[TikTok Live Downloader](https://apify.com/agentx/tiktok-live-downloader)** — TikTok live downloads
- **[Twitch VOD Downloader](https://apify.com/agentx/twitch-vod-downloader)** — Twitch VOD downloads
- **[Zoom Recording Downloader](https://apify.com/agentx/zoom-recording-downloader)** — Zoom recording downloads

#### E-Commerce and Retail

- **[All Shopping Scraper](https://apify.com/agentx/all-shopping-scraper)** — multi-platform product data
- **[AliExpress Product Scraper](https://apify.com/agentx/aliexpress-product-scraper)** — AliExpress products
- **[Amazon Storefront Scraper](https://apify.com/agentx/amazon-storefront-scraper)** — Amazon Brand Store pages
- **[Bol Product Scraper](https://apify.com/agentx/bol-product-scraper)** — Bol.com products
- **[eBay Seller Leads API](https://apify.com/agentx/ebay-seller-leads-api)** — eBay seller records
- **[Hepsiburada Product Scraper](https://apify.com/agentx/hepsiburada-product-scraper)** — Hepsiburada products
- **[Kakaku Product Scraper](https://apify.com/agentx/kakaku-product-scraper)** — Kakaku.com products
- **[Rakuten Product Scraper](https://apify.com/agentx/rakuten-product-scraper)** — Rakuten products

#### Classifieds and Automotive

- **[All Vehicle Scraper](https://apify.com/agentx/all-vehicle-scraper)** — multi-platform vehicle listings
- **[AutoTrader Vehicle Search](https://apify.com/agentx/autotrader-vehicle-search)** — AutoTrader US listings
- **[AutoTrader UK Vehicle Search](https://apify.com/agentx/autotrader-uk-vehicle-search)** — AutoTrader UK listings

#### Real Estate

- **[All Property Scraper](https://apify.com/agentx/all-property-scraper)** — multi-platform property listings
- **[Homes Property Scraper](https://apify.com/agentx/homes-property-scraper)** — Homes.com listings
- **[MagicBricks Property Scraper](https://apify.com/agentx/magicbricks-property-scraper)** — MagicBricks listings
- **[NoBroker Property Scraper](https://apify.com/agentx/nobroker-property-scraper)** — NoBroker listings
- **[Property24 Property Scraper](https://apify.com/agentx/property24-property-scraper)** — Property24 listings
- **[Realtor Property Scraper](https://apify.com/agentx/realtor-property-scraper)** — Realtor.com listings
- **[Zillow Property Scraper](https://apify.com/agentx/zillow-property-scraper)** — Zillow listings

### Support and Community

Ask about LinkedIn job search, input filters, Dataset fields, API, MCP, and billing in the [AgentX community on Telegram](https://t.me/Apify_Actor); for a reproducible bug, open an Issue with the run ID and exact input.

AgentX is an Arcyton brand — [arcyton.com](https://arcyton.com).

**Last Updated:** August 10, 2026

# Actor input Schema

## `max_results` (type: `integer`):

Maximum LinkedIn job rows to return

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

Job title, skill, or company query to search on LinkedIn

## `country` (type: `string`):

Country-specific LinkedIn market used for the search

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

Optional city, area, or postal code for the LinkedIn search

## `posted_since` (type: `string`):

Optional earliest posting date for the LinkedIn search

## `remote_only` (type: `boolean`):

Optional remote-only filter for the LinkedIn search

## `distance` (type: `integer`):

Optional search radius in miles around the LinkedIn location

## `job_type` (type: `string`):

Optional employment type for the LinkedIn search; `all` disables this filter

## `currency` (type: `string`):

Optional target currency for normalized LinkedIn salary amounts

## Actor input object example

```json
{
  "max_results": 12,
  "keyword": "Machine Learning Engineer",
  "country": "Japan"
}
```

# Actor output Schema

## `results` (type: `string`):

Default dataset overview of normalized job listings and company fields collected by All Jobs Scraper.

# 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 = {
    "max_results": 12,
    "keyword": "Machine Learning Engineer",
    "country": "Japan"
};

// Run the Actor and wait for it to finish
const run = await client.actor("agentx/linkedin-jobs-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 = {
    "max_results": 12,
    "keyword": "Machine Learning Engineer",
    "country": "Japan",
}

# Run the Actor and wait for it to finish
run = client.actor("agentx/linkedin-jobs-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 '{
  "max_results": 12,
  "keyword": "Machine Learning Engineer",
  "country": "Japan"
}' |
apify call agentx/linkedin-jobs-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,agentx/linkedin-jobs-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/nmdyrR62YooFl1bBS/builds/Jb202TzlU01msgFcP/openapi.json