# LinkedIn Job Details Scraper (`neuton/linkedin-job-details-scraper`) Actor

Extract full public LinkedIn job posting details from job URLs or IDs. Export title, company, location, description, criteria, posted date, applicant count text, company URL, and job URL without login.

- **URL**: https://apify.com/neuton/linkedin-job-details-scraper.md
- **Developed by:** [Ashwin Prasad](https://apify.com/neuton) (community)
- **Categories:** Jobs
- **Stats:** 3 total users, 2 monthly users, 73.3% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage

## 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 Details Scraper - No Login

Turn public LinkedIn job URLs or job IDs into structured job-detail records. This actor is designed for teams that already have LinkedIn job links from search, CRM notes, alerts, spreadsheets, or another crawler and need clean JSON/CSV output.

### Use cases

- Enrich LinkedIn job URLs with full descriptions
- Monitor hiring signals for target accounts
- Build job market datasets for salary, skill, and location analysis
- Feed recruiting workflows, job boards, Airtable, Clay, HubSpot, or BI dashboards
- Convert LinkedIn job IDs from search results into detailed structured records
- Run scheduled checks on high-value roles, competitors, and account lists

### Agent and automation workflows

Use this actor after a LinkedIn jobs search to turn saved job IDs, URLs, alerts, spreadsheets, CRM notes, or lead lists into structured job-detail rows. It is shaped for Make, Zapier, n8n, Clay, Airtable, Google Sheets, ATS enrichment, sales triggers, and AI agents that need job descriptions and criteria without scraping personal profile data.

Common automation patterns:

- Enrich newly discovered jobs with descriptions and criteria
- Monitor high-value companies for new roles and reposts
- Feed job descriptions into skill extraction, lead scoring, and market maps
- Convert LinkedIn job URLs from emails, alerts, or spreadsheets into JSON/CSV
- Build weekly hiring-intelligence reports for recruiters, sales teams, and analysts

### Output

Rows include job ID, title, company, location, posted date text, applicant count text, job URL, company URL, logo URL, full description, seniority level, employment type, job function, and industries.

### SEO keywords

LinkedIn job details scraper, LinkedIn job description scraper, LinkedIn job URL scraper, LinkedIn job ID scraper, LinkedIn hiring intelligence, LinkedIn job enrichment API, LinkedIn job posting extractor, public LinkedIn jobs no login.

### Example input

```json
{"jobUrlsOrIds":["4442141976"]}
```

### Pricing recommendation

Launch around $0.70 per 1,000 detailed job rows. This keeps the actor cheaper than broad LinkedIn enrichment tools while preserving more margin than the lightweight search actor because each detailed row requires a heavier page fetch and parser path.

### Responsible use

This actor only targets public job posting pages. Do not use the output for spam, unlawful discrimination, or platform abuse.

# Actor input Schema

## `jobUrlsOrIds` (type: `array`):

LinkedIn job URLs or numeric job IDs.

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

Maximum job detail rows to save.

## Actor input object example

```json
{
  "jobUrlsOrIds": [
    "4442141976"
  ],
  "maxResults": 100
}
```

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("neuton/linkedin-job-details-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("neuton/linkedin-job-details-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).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 neuton/linkedin-job-details-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=neuton/linkedin-job-details-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/qGHlZWOF1bqzv5Q6h/builds/KFL8mQngX5jZKmVfE/openapi.json