Use a URL, an ID, or the current-job starter
Supply the exact public LinkedIn job URLs or numeric IDs you already have. For a first test, leave the list empty and use the starter query. The Actor resolves one current public posting at run time, so the example does not depend on an old fixed job remaining live.
{
"jobUrlsOrIds": [],
"starterSearchQuery": "data engineer",
"starterSearchLocation": "London",
"maxResults": 1
}Try a current job by market
Each public Task resolves one current posting at run time and returns at most one complete row. Use these to test the same workflow against a market relevant to your hiring research.
| Market and role | Bounded public Task |
|---|---|
| Singapore AI hiring | Run one AI engineer job |
| India product hiring | Run one product manager job |
| US revenue operations | Run one sales operations job |
Start from Python or n8n
Download the one-job starter ZIP. Start with one job, then use the included Python CSV runner for up to ten known job IDs. The download also includes an inactive n8n template, spreadsheet headers, and offline tests. No email signup or credentials are needed to download it.
The CSV runner previews locally before you explicitly start a paid run. It requests a $0.05 pay-per-event ceiling, saves the run ID, and can resume retrieval without launching another run. Platform charges are separate. Its batch behavior is offline-tested; review the included README and live Actor pricing before execution.
The examples request one result with a $0.05 pay-per-event charge ceiling and a 120-second Actor timeout. Review current Apify charges before running. Required-field validation prevents incomplete rows from being saved locally; it does not reverse a charge already incurred. The n8n template has not been verified in a live n8n account and does not write to Google Sheets.
Inspect one row before scaling
Open the Dataset after the run. Confirm that the title, company, location, description, disclosed criteria, and source URL match the public posting. Then replace the starter with your own URLs or IDs and increase the cap gradually.
RUN_SUMMARY are free.Choose this Actor for known jobs
| Your input | Use this workflow |
|---|---|
| Known LinkedIn job URLs or IDs | Use Job Details directly for complete public records. |
| Only a role and location | Use LinkedIn Jobs Search Scraper first, then enrich selected IDs. |
| A specialist condition such as contract, salary, remote, or sponsorship | Use the relevant evidence-backed intelligence Actor in the LinkedIn jobs collection. |
Use it through Apify, API, or MCP
Save a tested input as an Apify Task, call the Actor through the API, trigger it from a schedule or webhook, or expose it to ChatGPT and Claude through Apify MCP. Keep the first automated run bounded and validate the Dataset before sending rows into an ATS, CRM, warehouse, or agent workflow.
Hosted MCP endpoint: https://mcp.apify.com/?tools=neuton/linkedin-job-details-scraper
Read the first-time setup guide for exact inputs, output-field checks, troubleshooting, and automation examples.
Frequently asked questions
Does it require a LinkedIn account?
No. The Actor reads public job-posting surfaces without a LinkedIn login or cookies.
Can I paste a full LinkedIn job URL?
Yes. Supply public job URLs, numeric job IDs, or both. Invalid and expired inputs remain explicit non-billable failures.
Does it infer missing salary or applicant counts?
No. It keeps unavailable public fields null and does not guess compensation, applicant counts, recruiter identities, or hidden criteria.
What should I run first?
Use the public one-job Task, inspect its Dataset and free RUN_SUMMARY, then replace the starter with one of your own URLs.
Test one complete job record
Use a current public posting and a one-result cap before importing a larger list.