This MCP server tracks LinkedIn posts from profiles and company pages and captures the commenters’ LinkedIn identities as publicly shown. It is described as a “LinkedIn Post Tracker and Comment Capture” server, with an associated MCP Registry presence.
🛠️ Key Features
Track LinkedIn posts from profiles
Track LinkedIn posts from company pages
Capture commenters’ LinkedIn information that is publicly visible
🚀 Use Cases
Observing or monitoring posts from specific LinkedIn accounts
Capturing publicly shown commenters for further analysis or processing
⚡ Developer Benefits
Enables programmatic collection tied to LinkedIn profiles and company pages
Focuses captured data on what LinkedIn shows publicly
⚠️ Limitations
Commenter information is limited to what LinkedIn displays publicly
Point it at LinkedIn person profiles or company pages. It returns the posts a search engine has indexed for each one, as flat rows: permalink, author, a text excerpt, and the publish date. No request is sent to LinkedIn, and no cookie, account, or credential is used.
Changed in 1.3.0. The actor stopped fetching linkedin.com on 2026-10-12. Commenter rows, reaction and comment counts, media, and the inputs collect_commenters, collect_reactors, max_engagers_per_post, and use_residential_proxy are gone. Posts now come from search results, so coverage is what the index holds: posts appear days or weeks after publishing, and many never appear. The tool keeps its name, capture_linkedin_posts_and_commenters, so existing clients keep working.
LinkedIn profiles and company pages in, the posts a search engine has indexed for them out.
Input
Type
Required
Meaning
profile_urls
array of strings
one of the two
Person profiles, for example https://www.linkedin.com/in/williamhgates.
company_urls
array of strings
one of the two
Company pages, for example https://www.linkedin.com/company/microsoft.
posted_since
string
no
ISO date. Posts published before this are skipped before anything is charged.
Reading the output
post is one row per indexed post: post_id, post_permalink, author_name, author_url, author_type, post_text (the search engine's excerpt), published_at (decoded from the post id).
notice is a run-level or source-level message. Filter these out before loading a table.
A post counts only when its permalink names the source, for example linkedin.com/posts/stripe_... for linkedin.com/company/stripe. A refused search comes back as a degraded notice, never as "no posts".
Billing
You are charged per post collected, plus a small actor start fee. Notice rows are free. posted_since filters before anything is charged.
Event
Price per event (USD)
Fires when
apify-actor-start
$0.00005
Charged when the Actor starts running, one event per GB of memory.
post-collected
$0.002 on the Free plan, down to $0.0017 on higher Apify plans
One LinkedIn post returned from search results, with its permalink, author, text excerpt and publish date.
It is a thin client for the Apify actor. It passes your input through and returns the actor's output unchanged. Every behavior described above lives in the actor, not here.
It reads only public search engine results. It sends no request to LinkedIn, holds no session cookie, and uses no LinkedIn account.
Post rows from a person profile name that person. When you run this you are the data controller for the personal data it returns and Apify is the processor. Your lawful basis is yours to establish; nothing here is legal advice.
This actor is unofficial and is not affiliated with, sponsored by or endorsed by LinkedIn or Microsoft.
Errors are surfaced, never swallowed. An invalid input, an invalid token, an exhausted balance, a timeout, or a run that returns anything other than a dataset all come back as an explicit tool error rather than as an empty result.
