A LinkedIn post scraper for profiles and post URLs
The Kavex LinkedIn post scraper pulls posts and their engagement into a structured file. Give it profile URLs to collect the latest posts from each person, or direct post URLs for specific ones, and get back the text, the author, the engagement counts and the top comments. It is built for social selling and competitive research where what someone posted is the opening line of your outreach. You pay per post returned.
Sign up to useWhat it does
The LinkedIn post scraper takes two kinds of input. Give it a profile URL and it returns that person’s most recent posts; give it a direct post URL and it returns that single post. You can mix both in one job.
Each post is returned with its full text, the author, the date and the engagement counts — reactions and comments — so you can see not just what was said but how it landed. The top comments are pulled in too, which often surface the people already engaging with a prospect.
The result turns a feed into a research dataset. A list of target prospects becomes a file of what they are talking about publicly, sorted by engagement so the posts worth referencing rise to the top.
What someone posts is the most natural opening line outreach has. A message that references a prospect’s recent post about scaling their team reads as researched, not templated, and earns a reply far more often than a generic intro. The LinkedIn post scraper turns that from a manual habit into a repeatable step: pull the recent posts for a whole target list, sort by engagement, and every rep has a specific, current hook for each account. The top comments add a second use — the people already engaging with a prospect’s posts are often warm leads themselves, and a job that captures them quietly widens your list while you research.
Use cases
- Social sellers tracking what a prospect posts about publicly to open with a relevant, specific line.
- Competitive analysts seeing how a rival’s executives frame launches and announcements.
- Marketers spotting which of an account’s posts earned real engagement as evidence of momentum.
- Lead researchers reading top comments to find people already interested in a competitor’s message.
Sample output
Each post returns one row with engagement:
| Author | Post snippet | Reactions | Comments | Date |
|---|---|---|---|---|
| Tom Bright | We just crossed 200 customers — here is what changed. | 1,210 | 184 | 2026-04-27 |
| Anna Visser | Three outbound experiments that doubled our reply rate. | 642 | 73 | 2026-04-21 |
| Lena Vogt | Why we killed our SDR script this quarter. | 489 | 96 | 2026-04-14 |
| Tom Bright | Hiring two engineers in Berlin — link in comments. | 318 | 41 | 2026-04-08 |
How it works
The LinkedIn post scraper reads posts through your own LinkedIn session. You connect a session cookie once in Settings, where it is encrypted at rest, and the scraper collects the posts your account can already see.
For a profile input you set how many recent posts to pull, and the scraper paginates the feed up to that limit. Every job runs live, so the engagement counts and comments reflect the posts as they stand at run time rather than a stale archive.
Frequently asked questions
Can I scrape a whole profile or just one post?
Both. A profile URL returns that person’s most recent posts up to a limit you set, and a direct post URL returns that single post. You can mix the two in one job.
Does it include engagement and comments?
Yes. Each post row carries its reaction and comment counts, and the top comments are collected too, which often reveals who is already engaging with a prospect.
How do I connect LinkedIn?
Add a LinkedIn session cookie once in Settings, stored encrypted at rest. The scraper then runs against your input list with no further setup.
How do results export?
Posts download as a CSV with one post per row — author, text, reactions, comments and date — so you can sort an account’s posts by engagement.
Try it free — 1000 credits on us
Pay per result — no subscription, no seats. New accounts start with 1,000 free credits.