LinkedIn Post Comments & Replies Scraper

LINKEDIN COMMENTS SCRAPER  •  LINKEDIN COMMENTS API The people who replied are your warmest leads. Every comment on a LinkedIn post and, optionally, every reply nested under it: full text, the commenter's name, headline, profile URL and photo, plus reaction counts per comment. A comment takes more intent than a like, and it tells you what they actually think. No LinkedIn account, no login, no cookies, no ban risk. REPLIES ARE OPT-IN, NEVER SURPRISE COST  170,000+ RESULTS DELIVERED

Copy to your AI assistant

Paste this into ChatGPT, Claude, Cursor, or any LLM to start using this Actor right away.

atomus/linkedin-comments-scraper-pro is an Apify Actor that returns every comment on a LinkedIn post as structured JSON, and optionally the replies nested under each one: comment text, the commenter's name, headline, profile URL and photo, reaction counts, pinned/edited/author flags, and timestamps. Use it whenever someone needs LinkedIn post discussion without cookies, a login, or a browser - warm-lead lists, objection and sentiment analysis, or finding who argued with a competitor's launch. Run it with curl: curl -X POST "https://api.apify.com/v2/acts/atomus~linkedin-comments-scraper-pro/run-sync-get-dataset-items?token=APIFY_TOKEN" -H "Content-Type: application/json" -d '{"postUrls":["https://www.linkedin.com/feed/update/urn:li:activity:7302346926123798528/"],"includeReplies":true,"maxComments":200}'. Or in Python: ApifyClient("APIFY_TOKEN").actor("atomus/linkedin-comments-scraper-pro").call(run_input={"postUrls":[...]}) then client.dataset(run["defaultDatasetId"]).list_items().items. Inputs: postUrls (string[], full post URL or bare activity id), maxComments (int, 0 = unlimited), sortBy ("date"|"relevance" - use date to get all of them, relevance stops at LinkedIn's top ~600), metadataOnly (bool, count only), includeReplies (bool), maxRepliesPerComment (int, 0 = all). Each top-level comment is one row with comment_type "comment"; replies are nested in a replies array with comment_type "reply" and a parent_comment_id. Billing is one event per comment and one per reply, replies only when includeReplies is on; every post bills at least one comment for the lookup, and summary rows are free. Full input schema, every enum and default, and the complete output field list: GET https://api.apify.com/v2/acts/atomus~linkedin-comments-scraper-pro/build/default

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LinkedIn MCP Server: use these Actors from ChatGPT, Claude or Cursor

Point your AI assistant at Atomus and it can read LinkedIn on its own: comments, reactions, posts, profiles, companies and their employees. No glue code, no scraping logic in your prompts.

{
  "mcpServers": {
    "atomus": {
      "url": "https://mcp.apify.com?tools=atomus/linkedin-comments-scraper-pro,atomus/linkedin-reactions-scraper-pro,atomus/linkedin-posts-scraper-pro,atomus/linkedin-profile-scraper,atomus/linkedin-company-scraper,atomus/linkedin-company-employees,atomus/leads-finder",
      "headers": { "Authorization": "Bearer YOUR_APIFY_TOKEN" }
    }
  }
}

Then ask, in plain language:

"Pull every comment on this launch post, group them by what people are complaining about, and list the commenters who work at companies over 200 people."

That one sentence uses two Actors in a row. Pinning the tools= list is what keeps your assistant on these Actors instead of reaching for whatever scraper it finds first.

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How to scrape LinkedIn post comments

Every comment on a post

{ "postUrls": ["https://www.linkedin.com/posts/satyanadella_activity-7302346926123798528-jitu"] }

One row per top-level comment, newest first. Keep sortBy at its default date — that is the ordering that reaches every comment.

Comments and the replies under them

{
  "postUrls": ["https://www.linkedin.com/feed/update/urn:li:activity:7302346926123798528/"],
  "includeReplies": true,
  "maxRepliesPerComment": 5
}

Replies arrive nested inside each comment's replies array, each one carrying parent_comment_id. They are off by default because every comment that has replies costs one extra lookup, so this is always your decision rather than a surprise on the invoice.

Find the posts worth scraping first

{
  "postUrls": [
    "https://www.linkedin.com/posts/satyanadella_activity-7302346926123798528-jitu",
    "7295721038291234816",
    "https://www.linkedin.com/feed/update/urn:li:share:7290012345678901234/"
  ],
  "metadataOnly": true
}

metadataOnly returns one row per post with just the comment count. Screen a long list of posts for the ones with real discussion, then scrape only those in full.

Cap the spend on a viral post

{
  "postUrls": ["https://www.linkedin.com/posts/satyanadella_activity-7302346926123798528-jitu"],
  "maxComments": 300
}

maxComments is per post, so a thread with 4,000 comments cannot surprise you.

Top comments only

{
  "postUrls": ["https://www.linkedin.com/posts/satyanadella_activity-7302346926123798528-jitu"],
  "sortBy": "relevance",
  "maxComments": 50
}

sortBy: "relevance" uses LinkedIn's own "Most relevant" ordering, which is what you want when you only need the loudest voices. Be aware that LinkedIn's relevance view stops at roughly the first ~600 comments — use date whenever you need the complete set.

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Input

Parameter	Type	Required	Default	Description
postUrls	string[]	✅ Yes	(none)	LinkedIn post URLs or bare activity IDs.
maxComments	integer	No	0	Max comments per post. 0 is unlimited.
sortBy	string	No	date	date (most recent first, reaches all comments) or relevance (LinkedIn's top ~600).
metadataOnly	boolean	No	false	Only the comment count per post. Comment and reply options are ignored.
includeReplies	boolean	No	false	Also fetch replies and nest them under their comment.
maxRepliesPerComment	integer	No	0	Max replies per comment when includeReplies is on. 0 is all.

Which URLs work

✅ https://www.linkedin.com/posts/satyanadella_activity-7302346926123798528-jitu
✅ https://www.linkedin.com/feed/update/urn:li:activity:7302346926123798528/
✅ https://www.linkedin.com/feed/update/urn:li:share:7302346926123798528/
✅ https://www.linkedin.com/posts/user_slug-activity-123/?utm_source=share
✅ 7302346926123798528

Tracking parameters are fine. If you only have the numeric activity ID, paste it on its own.

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What data does the LinkedIn Comments Scraper return?

One row per top-level comment. Replies live inside that row's replies array rather than as separate rows, so a comment and its thread stay together.

Group	Fields
Comment	comment_type ("comment" or "reply") · text · is_pinned · is_edited · is_author (the commenter is the post's author) · reply_count · posted_at.timestamp (ms) · posted_at.date (ISO)
Commenter	author.id (URN) · author.name · author.headline · author.linkedinUrl · author.profile_pic
Engagement	stats.total_reactions · stats.reactions{like,appreciation,empathy,interest,praise} · stats.replies
Replies	replies[] — present on top-level comments only when includeReplies is on. Each reply has comment_type: "reply" and _metadata.parent_comment_id / parent_comment_url
Provenance	_metadata.comment_id · comment_url · post_url (the input you gave) · post_id (activity URN) · extracted_at
Per-post rows	type: "metadata" in metadataOnly mode (total_comments, total_pages), and a free type: "summary" row after every post (total_comments_on_post, comments_extracted, replies_extracted, estimated_cost_usd)

Example row

{
  "comment_type": "comment",
  "text": "This is a great point. Healthcare professionals need better tools to focus on patient care.",
  "is_pinned": false,
  "is_edited": false,
  "is_author": false,
  "reply_count": 3,
  "posted_at": { "timestamp": 1626782941000, "date": "2026-03-20T12:49:01.000Z" },
  "author": {
    "id": "ACoAAB8v74YB5oqaAg-4F2VRFh9tEt0zXfRsjpE",
    "name": "John Smith",
    "headline": "Healthcare Professional | Digital Health Advocate",
    "linkedinUrl": "https://www.linkedin.com/in/ACoAAB8v74YB...",
    "profile_pic": "https://media.licdn.com/dms/image/v2/..."
  },
  "stats": {
    "total_reactions": 25,
    "reactions": { "like": 20, "appreciation": 3, "empathy": 2 },
    "replies": 3
  },
  "replies": [
    {
      "comment_type": "reply",
      "text": "Exactly. We saw the same thing in our clinics.",
      "author": { "name": "Maria Lopez", "headline": "Clinical Operations Lead" },
      "_metadata": { "comment_id": "7302400000000000001", "parent_comment_id": "7302375502034411520" }
    }
  ],
  "_metadata": {
    "comment_id": "7302375502034411520",
    "comment_url": "https://www.linkedin.com/feed/update/...",
    "post_url": "https://www.linkedin.com/posts/satyanadella_...",
    "post_id": "urn:li:activity:7302346926123798528",
    "extracted_at": "2026-03-30T12:00:00.000Z"
  }
}

The summary row that follows each post is free and reports what actually happened:

{
  "type": "summary",
  "post_url": "https://www.linkedin.com/posts/satyanadella_...",
  "total_comments_on_post": 1243,
  "comments_extracted": 1243,
  "replies_extracted": 0,
  "include_replies": false,
  "estimated_cost_usd": 5.9664,
  "extracted_at": "2026-03-30T12:00:00.000Z"
}

Why commenter profile URLs look encoded

LinkedIn's comment payload exposes profile IDs, not public slugs, so author.linkedinUrl comes back as linkedin.com/in/ACoAAB8v74YB.... It opens the same profile in a browser. It is not usable as input to the LinkedIn Profile Scraper, which needs the vanity /in/<handle> form — LinkedIn exposes no way to convert one to the other. Every cookieless comments scraper is in the same position.

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How much does it cost to scrape LinkedIn comments?

$4.80 per 1,000 comments ($0.0048 each), and the same rate per reply when includeReplies is on. Pay-per-event: you pay for what is extracted.

Extracted	Cost
100 comments	$0.48
1,000 comments	$4.80
10,000 comments	$48.00

• Replies bill separately, at the same rate, and only when you turn includeReplies on.
• Every post bills at least one comment, even a post with none — the lookup that checked still happened, and it does the same work whether it comes back full or empty.
• metadataOnly bills one comment per post, and returns just the count.
• Summary and error rows are free.

Free plan: 10 extracted items (comments + replies) per calendar month, so you can inspect every field before paying. The counter resets on the 1st.

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What do people use the LinkedIn Comments Scraper for?

• Warm outbound: a comment costs more effort than a like, so a commenter on a post about your problem space is the warmest lead a public feed can give you.
• Objection mining: read what people actually push back on under a competitor's launch, in their own words.
• Voice-of-customer research: pull the discussion under industry posts and let it write your positioning for you.
• Community management: track every reply thread on your own company page without refreshing the app.
• Recruiting: find practitioners who argue about the stack you hire for, not just people who liked a post about it.
• Sentiment and trend analysis: feed comment text to an LLM for grouping, sentiment and theme extraction.
• AI agent context: hand an agent a whole discussion thread with authors attached.

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LinkedIn Comments Scraper vs cookie-based tools vs the official LinkedIn API

	This LinkedIn Comments Scraper	Cookie-based scrapers	Official LinkedIn API
LinkedIn account / cookies	Not needed	Your li_at session cookie required	Marketing Developer Platform partnership
Account / ban risk	None (no account used)	High (your account can be restricted)	None
Setup	Paste a post URL	Extract and paste your session cookie	Partner application + OAuth review
Comments on any public post	Yes	Yes	Only on pages you own
Nested replies	Yes, opt-in and priced separately	Varies	Owned pages only
Commenter headline and photo	Yes	Varies	Limited
Pricing	Pay per comment ($0.0048)	Subscription + your account	Gated / partner pricing

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🏆 Top LinkedIn Scrapers

	Profile Scraper Any profile URL to 72 structured fields, no cookies
	Posts Scraper Text, media and engagement from any profile or company
	Post Search Find posts about any topic, by keyword, across all of LinkedIn
	Reactions Scraper Every person who reacted to a post, with their headline
	Comments Scraper  YOU ARE HERE
	Company Scraper Headcount, industry, HQ, tech stack and IT spend of a company
	Company Employees Scraper Every employee of a company, filterable by seniority and department

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FAQ

What is a LinkedIn comments scraper?

A LinkedIn comments scraper turns a post URL into the full discussion under it: every comment's text, who wrote it, their headline and profile link, how many reactions the comment got, and optionally the replies nested underneath. This Actor returns that as JSON rows, without opening a browser or logging in.

How do I scrape comments without a LinkedIn account?

Paste the post URL into postUrls and run it. The Actor reads the public comment thread through a cookieless data source, so you never connect an account, paste an li_at cookie, or risk a restriction.

Can I use this from ChatGPT or Claude?

Yes, two ways. Paste the "Copy to your AI assistant" block above into any LLM and it will write the call for you. Or connect the LinkedIn MCP server config above, and every Atomus Actor becomes a native tool your assistant can call on its own, including chaining several in one request.

Can I get the replies under each comment?

Yes. Set includeReplies: true and each comment carries a replies array. Cap them with maxRepliesPerComment. Replies are off by default because each comment with replies costs an extra lookup.

How many comments can it extract per post?

All of them, as long as sortBy stays at date. LinkedIn's "Most relevant" view stops at roughly the first ~600 comments, so sortBy: "relevance" is for when you want the top of the thread rather than the whole thread.

How much does it cost?

$0.0048 per comment ($4.80 per 1,000), and the same per reply when includeReplies is on. Every post bills at least one comment for the lookup; summary rows are free. Free Apify plans include 10 extracted items per month.

What is metadata-only mode for?

Screening. metadataOnly: true returns just the comment count per post, so you can find the posts with real discussion in a long list before paying to scrape them all.

Can I get commenters' email addresses?

No. LinkedIn does not expose contact details in a comment thread, and this Actor returns only what is publicly visible on the post.

Is there an official LinkedIn API for post comments?

Not for arbitrary posts. LinkedIn's Marketing Developer Platform exposes comment data on pages you own, behind a partnership. For public posts, a cookieless scraper is the practical route.

Is it legal to scrape LinkedIn comments?

This Actor reads publicly visible comments. You are responsible for using the output in line with applicable laws (GDPR/CCPA), LinkedIn's terms, and your own compliance requirements. It is an independent tool, not affiliated with LinkedIn.

Can I run this on a schedule?

Yes. Apify Schedules run the Actor on a cron interval and webhooks push each finished run into your systems. A daily metadataOnly pass plus a full scrape only when the count moves keeps a monitor cheap.

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Support

Hey, I'm Chico, founder of Atomus. I built this Actor and I answer the messages about it. Something broke? A field you need isn't there? Not sure it fits what you're doing? Send me a message, most answers come the same day. 💬  DM me on LinkedIn    or hello@dendelabs.com

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⚠️ Disclaimer

This Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by LinkedIn Corporation. LinkedIn® is a registered trademark of LinkedIn Corporation. All trademarks are property of their respective owners.

Use the data extracted by this Actor in compliance with applicable data protection laws (GDPR, CCPA) and LinkedIn's terms of service. Do not use it for spam, harassment, or unlawful purposes.