# LinkedIn Jobs Scraper — FULL (All Info) (`nomad-agent/linkedin-full-info-scraper`) Actor

Extract comprehensive public LinkedIn job data without login, including salary, structured location, expiry, company details, job criteria, applicants, contacts, description HTML, and raw JSON-LD.

- **URL**: https://apify.com/nomad-agent/linkedin-full-info-scraper.md
- **Developed by:** [Nomad.Dev](https://apify.com/nomad-agent) (community)
- **Categories:** Jobs
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$0.90 / 1,000 job 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/platform/actors/running/actors-in-store#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 — FULL (All Info)

Extract the complete public LinkedIn job record without login, cookies, a browser, or a proxy. Each result combines the guest search card, visible public-page metadata, and schema.org `JobPosting` JSON-LD in one flat, nullable record.

Use the existing **LinkedIn Jobs Scraper — Short Output** for compact job-alert payloads. Use this Actor when you need every available field, including raw source objects.

### Output

Every row keeps the compact fields (`id`, `title`, `company`, `location`, `url`, `postedAt`, `description`, `snippet`) and adds:

- LinkedIn job URN and external/ATS identifier
- company LinkedIn ID, page URL, and logo
- exact `datePosted`, relative posted text, and `validThrough`
- visible employment type, seniority, job function, industries, applicants, and listing badge
- structured country/city/region/address plus latitude and longitude
- workplace type and applicant-location restrictions
- raw and normalized salary, including currency, minimum, maximum, exact value, and period
- education and experience requirements, skills, benefits, qualifications, responsibilities, work hours, incentive compensation, and occupational category when supplied
- hiring contact and apply metadata when publicly shown
- plain-text description, original HTML description, and the complete raw `jsonLd` object

LinkedIn does not populate every field on every posting. Missing source values are `null`; the Actor never guesses them. The raw `jsonLd` field preserves additional present or future JobPosting keys even when they do not yet have a flattened column.

### Input

The search and filtering inputs match the compact Actor:

- `keyword`, `location`, `remote`, `timeFilter`, `maxItems`
- `postedSince`, `titleExclude`, `companyExclude`

There are no partial-detail toggles: this Actor always requests the full public record.

### Example

```json
{
  "id": "4446226935",
  "jobUrn": "urn:li:jobPosting:4446226935",
  "title": "Software Engineer I - New Grad, SF",
  "company": "Samsara",
  "companyLinkedInUrl": "https://www.linkedin.com/company/samsara",
  "location": "San Francisco, California, United States",
  "locationCountry": "US",
  "locationCity": "San Francisco",
  "jobLocationType": "TELECOMMUTE",
  "salary": "USD 136850-161000 YEAR",
  "salaryCurrency": "USD",
  "salaryMin": 136850,
  "salaryMax": 161000,
  "salaryUnit": "YEAR",
  "employmentType": "Full-time",
  "seniorityLevel": "Entry level",
  "datePosted": "2026-08-03T16:52:58.000Z",
  "validThrough": "2026-09-02T16:52:48.000Z",
  "description": "Full plain-text posting…",
  "descriptionHtml": "<p>Full HTML posting…</p>",
  "jsonLd": {"@context": "http://schema.org", "@type": "JobPosting"}
}
```

### Run through the API

```bash
curl -X POST \
  "https://api.apify.com/v2/acts/nomad-agent~linkedin-full-info-scraper/run-sync-get-dataset-items?token=<YOUR_APIFY_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"keyword":"software engineer","location":"Spain","maxItems":10}'
```

The public full page is substantially larger than LinkedIn's guest fragment, so this Actor is intentionally the richer, slower counterpart to the compact Actor. LinkedIn's terms restrict automated access; review the target site's terms and applicable law for your use case.

# Actor input Schema

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

Job title, skill or role to search for (e.g. <code>software engineer</code>, <code>product manager react</code>). Leave empty to search all recent postings for the given location.

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

City, region or country to filter by (e.g. <code>Spain</code>, <code>London</code>, <code>European Union</code>). Leave empty for worldwide results.

## `remote` (type: `boolean`):

When enabled, restricts results to remote-eligible postings.

## `timeFilter` (type: `string`):

Restrict to postings published within the chosen window.

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

Maximum number of job postings to return. Hard ceiling: LinkedIn's guest search endpoint only paginates to ~200 postings per run regardless of this setting (its offset stops returning new results past that point) — set higher than 200, or 0 for <code>no limit</code>, and you still get at most ~200.

## `postedSince` (type: `integer`):

Drop results whose posting date is older than this many days. Items without a known posting date are not filtered out. Set 0 to disable.

## `titleExclude` (type: `array`):

Drop a result if its title contains any of these words or phrases (case-insensitive).

## `companyExclude` (type: `array`):

Drop a result if its company name contains any of these words or phrases (case-insensitive).

## `skipJobId` (type: `array`):

Explicit dedup list: drop any posting whose numeric LinkedIn job id is in this array (exact match). Use it to skip ids from a prior run or dataset in a single call.

## `cacheTtlSeconds` (type: `integer`):

Reuses the last fetch for this many seconds so rapid re-runs don't hit LinkedIn again. Set 0 to always fetch live.

## Actor input object example

```json
{
  "keyword": "frontend developer typescript",
  "location": "Germany",
  "remote": false,
  "timeFilter": "r86400",
  "maxItems": 100,
  "postedSince": 0,
  "titleExclude": [],
  "companyExclude": [],
  "skipJobId": [],
  "cacheTtlSeconds": 1800
}
```

# Actor output Schema

## `dataset` (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("nomad-agent/linkedin-full-info-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("nomad-agent/linkedin-full-info-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 nomad-agent/linkedin-full-info-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,nomad-agent/linkedin-full-info-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/4NY60JkLPL9iC8ySe/builds/TvRaVpWBpg48dtfwm/openapi.json