Posts Scraper for LinkedIn - Profiles, Pages & Search

Four ways in, one clean table out. Point it at a person, a company page, a keyword, or a post URL and get the posts back with the full text, exact reaction and comment counts, and the comments themselves. No login, no cookies, no session tokens.

Most LinkedIn post scrapers make you buy the pieces separately - one actor for profile posts, another for company posts, another for keyword search, and another again for comments. This one does all four, and the comments come included.

Four inputs

Input	What you get	Typical use
profileUrls	A person's recent public posts	Track a founder, exec, or competitor's spokesperson
companyUrls	A company page's recent posts	Competitor content monitoring, brand tracking
searchKeywords	Public posts mentioning a phrase	Social listening, buying-signal hunting ("hiring a CTO")
postUrls	Exactly the posts you name	Enrich a list you already have

Mix them freely in one run. Every row says which source found it via sourceType.

What each post row contains

{
  "type": "post",
  "postUrl": "https://www.linkedin.com/posts/supabase_today-were-open-sourcing-supabase-evals-activity-7489047352075460608-EGgJ",
  "activityId": "7489047352075460608",
  "authorName": "Supabase",
  "authorType": "company",
  "authorUrl": "https://www.linkedin.com/company/supabase",
  "text": "Today we're open-sourcing Supabase Evals, our benchmark for how well AI coding agents build with Supabase...",
  "textLength": 1001,
  "datePublished": "2026-07-31T20:00:28.487Z",
  "postedAgoText": "1w",
  "reactionCount": 286,
  "commentCount": 25,
  "engagementTotal": 311,
  "topComments": [
    {
      "text": "Nice. The part I'd want as a user is a way to know the copy in the warehouse still matches Postgres...",
      "authorName": "Renee Romero",
      "authorUrl": "https://www.linkedin.com/in/renee-romero",
      "postedAgoText": "2w"
    }
  ],
  "hashtags": ["postgres"],
  "mentions": [],
  "externalLinks": ["https://lnkd.in/gbRHqH-e"],
  "imageUrl": "https://media.licdn.com/dms/image/...",
  "hasMedia": true,
  "detailFetched": true,
  "sourceType": "company",
  "scrapedAt": "2026-08-07T04:10:00.000Z"
}

Filters that run while it crawls

postedAfter / postedBefore for a date window, and minReactions to keep only the posts that actually performed. They are applied during the crawl, not to a truncated sample afterwards, so a filtered run still fills up to your maxResults.

What LinkedIn does and does not serve logged-out

Measured on this actor's own runs, so you know what you are buying.

• Recent posts, not the full archive. A profile or company page publishes roughly its latest 6-20 posts to a logged-out visitor. There is no way to page back through years of history without an account, and this actor will not pretend otherwise. To go deeper on a topic rather than an author, use searchKeywords.
• Engagement counts need the post page. Company page listings do not publish reaction counts; the post's own page does. That is why fetchPostDetails defaults to on - turning it off is faster and cheaper but returns text and author only.
• Post pages carry a relative age, not a timestamp. Posts discovered from a profile or company page carry an exact ISO datePublished; posts reached only by URL or keyword may have just postedAgoText ("1w"). Both fields are emitted separately rather than converting a guess into a fake timestamp.
• Comments are the ones LinkedIn shows publicly - typically the top ~10, with author, relative age and (where published) a like count. Not the full thread.
• Never returned: anything behind the login wall - private posts, full reaction lists, connection graphs, or personal contact details.

Pricing

Pay-per-event: $0.004 per post, comments included. A run that finds nothing charges nothing, and every finished run tells you what to change.

Use with AI assistants (MCP)

This actor works as a tool in any MCP-compatible assistant through the Apify MCP server - ask your agent to "find what our competitors posted on LinkedIn this month and how it performed" and it can call this actor directly.

Agent-ready: autonomous payments (x402 & Skyfire)

This actor is agent-ready — AI agents can discover it, run it, and pay for it autonomously, with no Apify account and no human in the loop. It uses pay-per-event pricing and limited permissions, so it qualifies for Apify's agentic-payment standards:

• x402 — an open, HTTP-native payment protocol. Agents pay per run in USDC on the Base network directly through the Apify MCP server — no account, no API key.
• Skyfire — agent-to-service payments for fully autonomous AI-agent workflows.

Building an AI agent, MCP tool, or autonomous data pipeline? This scraper is ready to plug in and pay as it goes.

Legal

This actor reads only what LinkedIn publishes to logged-out visitors. It does not log in, use cookies or session tokens, or attempt to reach private content. Post text and commenter names relate to identifiable people, so if you are in the EU or UK you are the data controller for whatever you do with the output: have a lawful basis, and honour deletion requests. Do not use it for spam.

This actor is not affiliated with, endorsed by, or sponsored by LinkedIn Corporation. LinkedIn is a trademark of LinkedIn Corporation.