| LinkedIn Public Data Suite • 11 Actors, one codebase, one row billed once | ||
| LinkedIn Scraper API ➤ You are here | LinkedIn Jobs Search Scraper API Filters That Hold | LinkedIn Job Details Scraper API By URL or Job ID |
| LinkedIn Company Jobs Scraper API Open Jobs by Company | LinkedIn New Jobs Scraper API Last 24 Hours, Change-Only | LinkedIn Company Scraper API Exact Employees, Followers |
| LinkedIn Company Posts Scraper API Newest Posts, Exact Counts | LinkedIn Post Scraper API Text, Exact Counts, Top Comments | LinkedIn Pulse Article Scraper API Full Text, Author |
| LinkedIn Profile Scraper API Public Profiles, Exact Followers | LinkedIn Profile Posts Scraper API A Person's Recent Posts | |
At Accenture Federal Services, ...
" }, "searchQuery": "data engineer | United States" } ``` `postedAt` is the exact date from LinkedIn's listing, not a "1 week ago" estimate. `city`, `region` and `countryCode` (ISO) are read from `location`; a metro area such as "Greater Seattle Area" names no country, so it takes the country of the search it came from, when that search names one, and `countrySource` says `search`. `isRemote` is true when the posting's workplace, its location or its title says remote, false when the workplace is on-site or hybrid, and null when nothing says. `salary` is filled only when the posting states one (`source` says whether it came from a salary element or the description text); "€50.000", "45 000 kr", "$120K" and "10-15 LPA" are read as written, and `period` is null unless the posting states it. With **Add company pages for job results** on, each job row also carries `companyInfo` (website, size band, members on LinkedIn, industry, headquarters, followers and the numeric company id) from the company's page (null when that page cannot be read), at no extra charge. `applicants.count` is null when LinkedIn only says "Be among the first 25 applicants". #### A company row ```json { "type": "company", "id": "microsoft", "numericId": 1035, "name": "Microsoft", "industry": "Software Development", "companySize": "10,001+ employees", "employeesOnLinkedIn": 232762, "followers": 29007369, "headquarters": "Redmond, Washington", "organizationType": "Public Company", "website": "https://news.microsoft.com/", "specialties": ["Business Software", "Developer Tools", "Home & Educational Software", "..."], "address": { "street": "1 Microsoft Way", "locality": "Redmond", "region": "Washington", "postalCode": "98052", "country": "US" }, "locations": [{ "primary": true, "street": "1 Microsoft Way", "cityLine": "Redmond, Washington 98052, US" }, "... 44 more"], "affiliatedPages": [{ "name": "GitHub", "industry": "Software Development", "location": "San Francisco, CA", "url": "https://www.linkedin.com/company/github" }, "..."], "recentPosts": [{ "activityId": "7500677397822775296", "url": "https://www.linkedin.com/posts/microsoft_..." }, "..."] } ``` `employeesOnLinkedIn` is the exact number of members who list the company, which is what LinkedIn actually counts; `companySize` is the band the company chose. Both are given so you are never guessing which one you are looking at. #### A post row ```json { "type": "post", "activityId": "7498030724533522432", "url": "https://www.linkedin.com/posts/microsoft_august-2026-ai-powered-discovery-activity-7498030724533522432-IzKE", "author": { "name": "Microsoft", "url": "https://www.linkedin.com/company/microsoft", "type": "company", "followers": 29006766 }, "text": "Curiosity drives discovery, sparking questions about how we can better understand our world ...", "publishedAt": "2026-08-25T14:57:11.372Z", "reactions": 745, "comments": 98, "mediaType": "article", "article": { "title": "August 2026: AI-powered discovery", "url": "https://www.linkedin.com/pulse/..." }, "commentsShownCount": 10 } ``` `reactions` and `comments` are exact. With comments on, each comment LinkedIn shows on the page (about ten) is its own `comment` row with the commenter, their profile URL, the text, the date and its like count. #### An article row ```json { "type": "article", "title": "The turbulent AI era is here. The choices we make now are critical.", "author": { "name": "Bill Gates", "url": "https://www.linkedin.com/in/williamhgates", "followers": 40617215 }, "publishedAt": "2026-08-26T07:03:26.000Z", "likes": 9984, "comments": 1990, "readingTimeMinutes": 25, "text": "We need a plan to ensure that the good outweighs the bad ...", "newsletter": { "name": "Gates Notes", "subscribers": 6552252 } } ``` ### What it costs | You pay for | Price | |---|---| | Each job found by a search, delivered with its full posting | **$1.50 per 1,000 jobs** | | Each job you name by URL or id, delivered with its full posting (one request per row) | **$4.00 per 1,000 jobs** | | Each job delivered as a listing card only ("Read the full posting" off) | **$0.50 per 1,000 jobs** | | Each job search that delivered something: a keyword-and-location search, a pasted search link or a company's open jobs (never more than 250 a run) | **$2.00 per 1,000 searches** | | Each company page delivered (once per company, never per job) | **$4.00 per 1,000 companies** | | Each post delivered | **$1.50 per 1,000 posts** | | Add-on: each comment shown on a post | **$2.00 per 1,000 comments** | | Each Pulse article delivered | **$3.00 per 1,000 articles** | **Free, always:** a job that has closed, a company, post or article that does not exist, a page LinkedIn only shows to signed-in members, a malformed URL, every error row, the coverage row and the run summary, a job skipped by your title filters or id list, and a posting whose stated seniority or job type does not match the filter you set. A run that reads nothing costs nothing. On a one-off run a search is billed only when it delivered at least one job. With **Monitor** on, every search LinkedIn answered is billed, because that check is the work you scheduled — so a day with no new postings costs $2.00 per 1,000 searches and nothing else. A search the run's time limit cut before it delivered anything is free. A query LinkedIn cannot match (it returns unrelated "similar" jobs) is detected, delivers nothing and costs nothing. Searches never count against your result cap. Set **Cost ceiling (USD)** to stop any run before it passes a number you choose; the free summary row reports what the run actually spent. ### Limits, stated plainly LinkedIn shows its search results (people, companies, content), employee lists, reaction lists and Sales Navigator only to signed-in members, and serves member profiles to visitors only at its own discretion (measured 2026-09-02 from Apify's own exits: 35 of 50 ordinary profiles, and the refused ones stay refused). This Actor reads public pages only and never signs in, so it sells none of those — and says so here rather than on your invoice. A public post page shows about ten comments and no repost count; the exact reaction and comment totals are always there. LinkedIn's public job search stops at about 1,000 results per query and applies its experience-level and workplace filters inconsistently; seniority and job type are re-checked on the posting, workplace is not. The external "Apply" link and the hiring team are behind LinkedIn's sign-in and are not sold. Salary is delivered when the posting states it. ### Use it from n8n, MCP, the API or a schedule Built to be called by a workflow, not only from the Store form. The Actor is `vonsensey/linkedin-scraper-api`; every snippet below sends `{}`, which runs the defaults shown on the form — replace it with your own input. #### n8n Install the **Apify** community node (`@apify/n8n-nodes-apify` under *Settings → Community Nodes*, or search "Apify" on n8n Cloud). Add **Apify → Run Actor** with Actor `vonsensey/linkedin-scraper-api` and your input JSON, then **Apify → Get Dataset Items** on the run's `defaultDatasetId` and pipe the rows anywhere. For scheduled runs, the **On new Apify Event** trigger fires when a run of this Actor finishes. #### MCP (Claude, Cursor, VS Code, any MCP client) ```json { "mcpServers": { "apify": { "url": "https://mcp.apify.com?tools=vonsensey/linkedin-scraper-api", "headers": { "Authorization": "Bearer