In short
- 1"A free finder reads a public post's comments with no setup at all, and is enough for most single-post jobs"
- 2"Cloud platforms (PhantomBuster, TexAu, Captain Data, Dripify) win on volume and scheduling, and cost the most to set up"
- 3"Browser extensions (Evaboot, Dux-Soup) sit in the middle: quick to install, and they stop when the tab closes"
- 4"The export is the easy half. What decides the outcome is filtering the list before you write to anyone"
Say you need the commenters off a viral post, a couple thousand of them, and you want them fast. You sign up for a cloud exporter, build the workflow, and a clean CSV lands in ten minutes. The export worked. Then the CSV sits there, because two thousand names with no indication of which forty are worth writing to is not a lead list. The export is the easy half, and it is the half every roundup measures.
That trade is the thing the roundups skip. Search for the best way to get comments off a LinkedIn post and you get the same dozen tools sorted by price, by export format, or by how many comments they claim to pull in one run, almost never by the one thing that decides whether you regret the choice: how much access to your own account the tool demands, and who is holding that access once the CSV lands.
That is the axis that separates a two-minute lookup from a restricted profile. So here is the roundup built around it: ten routes to export LinkedIn post commenters, ranked from the ones that touch your account least to the ones that take the most, with a neutral read on each and one honest concession where a dedicated tool wins.
The 10 tools at a glance
Two things about that table decide most of the difference, and neither is in the marketing copy.
A browser extension runs in the page you already have open. It reads the comment panel from the post in front of you and writes the result to a file. Install it once and it is a two-click job after that, but it only runs while the tab is open, so it does not suit anything scheduled.
A cloud tool runs on its own infrastructure, on a schedule. You configure it once in a dashboard and it keeps running whether your laptop is open or not. That is what you are paying for, and it is genuinely the right shape for a recurring motion. The cost is the setup: a workflow to build, and a dashboard to learn, before the first row arrives. The tool works. The configuration outlives the export.
The ranking below sorts by how much work each one takes to get going, and what you are holding when it finishes.
The tiers, tool by tool
No setup at all
Free comments finder. Paste a post URL and the comment list comes back. There is nothing to install and nothing to configure. The trade-off is scope: it reads what is public, so comments on posts shared to a restricted audience are out of reach. This is the route the rest of this article builds on. You can run it now with the LinkedIn comment extractor.
Apify comment actor. Apify is a marketplace of hosted scripts ("actors"), several of which target LinkedIn post comments. The important distinction is per actor: the popular comment actors read public post data on Apify's infrastructure, while the profile-detail and Sales Navigator actors want a connected account and more configuration. Read what the specific actor requires before you run it. For the fuller picture of what running on a marketplace actor costs and controls, see the BeReach vs Apify comparison.
Install once, then it is quick
Dedicated single-post exporter. A category of purpose-built tools does one job: paste a post URL, set a limit, get every commenter in a CSV, frequently with an email column appended. Most run in your browser through your logged-in session. This is the concession row, and it gets its own section below, because for one specific job these tools genuinely win.
Evaboot. Best known for cleaning Sales Navigator exports, Evaboot is a Chrome extension that also pulls post engagers using your live session, then dedupes and enriches the output. Clean data, real email-finding, and the exposure of any extension that acts through your account: bounded to your own browser and IP, but still your account doing the work.
Dux-Soup. One of the older LinkedIn browser extensions. It handles commenter and visitor export alongside its automation features, running entirely inside your browser. Mature and configurable, and like every extension it only works while the browser is open.
Bardeen. A general browser-automation extension with prebuilt LinkedIn "playbooks," including comment scraping, that can pipe results into Sheets, Notion, or Airtable. It straddles the line: the capture happens in your browser, but scheduled and cloud-run flows push it toward the higher-exposure end.
Most setup, most volume
TexAu. A growth-automation platform offering a comment exporter among many "recipes," available as a cloud service or a desktop app. The cloud version runs from its servers on a schedule; the desktop version runs locally and behaves more like an extension. Powerful and broad, and which version you pick decides whether it keeps working when your machine is off.
PhantomBuster. The most-cited name in this space, with a dedicated LinkedIn Post Commenters Export "phantom." You configure it once, then runs execute from PhantomBuster's cloud on a schedule. Reliable and well-documented, and it behaves exactly as the cloud model implies: it keeps going from infrastructure that is not yours, until you disconnect it.
Captain Data. An enterprise-grade automation platform with LinkedIn workflows including engagement export, run server side and wired into other systems by API. Built for teams and volume, which is also what raises the exposure: sustained, scheduled account activity from a hosted environment.
Dripify. Primarily a cloud sequencing tool, with engagement extraction alongside its campaigns. Same shape as the others in this tier: it is configured in the dashboard and runs from Dripify's servers, so it keeps working while your laptop is closed.
The one row where a dedicated tool wins
One job breaks the ranking, and it is worth naming. If your job is a single, one-time bulk dump of one very large post, say a viral thread with tens of thousands of comments, and you want every reactor's metadata and an appended email column in one flat CSV for research or list-building, a purpose-built single-post exporter does that in one click and does it better than a finder built for outreach. Raw volume, one export, emails attached, done.
A free finder is not optimized for that. It feeds a qualified outreach workflow, not a 40,000-row archive of a marketing post. When the deliverable really is the spreadsheet itself, the dedicated exporter is the right tool. The catch is the one this whole article is about: a 40,000-row spreadsheet is not a lead list, and somebody still has to work out which rows matter.
For most outreach, though, the deliverable is not the spreadsheet. It is a short list of people worth writing to, which is a different problem.
The fastest way to a usable list
The lowest-exposure route is also the fastest to start, because there is nothing to install and nothing to paste.
- Open the post on its own page. Use the full permalink from the address bar, not the shortened share link, so the tool resolves the right post.
- Paste the URL into the finder. The scrape a post's commenters reads the public comment list on a server and returns the people. No session is connected, so your account is never in the loop.
- Filter before you export, not after. Cut the list down while it is on screen. Cleaning a raw CSV of 400 rows later is slower than narrowing it now, and it is the step everyone skips.
The same pattern works for reactions through the sibling likes route, and there is a step-by-step walkthrough for commenters specifically in how to export LinkedIn post commenters.
What actually turns the list into pipeline
A list of 400 commenters is not 400 leads, and the export is the easy half. A comment is a stronger signal than a like because it costs visible effort, but it still does not tell you the person has a problem you solve. The qualification step is what converts an engagement list into a prospect list, and skipping it is why most exported CSVs die untouched.
Two filters do most of the work. Fit: does this person match who you actually sell to, judged more by company shape than by title alone. And relevance: someone who commented on a post about the exact problem you solve is worth far more than someone who commented on a viral post about hiring. The topic is part of the signal, not just the act of commenting.
The reason it matters is in the reply rates. In Belkins' 2026 LinkedIn outreach study, an already-warm prospect replied at 12.2% against 7.9% for a standard cold connection campaign, a lift of more than half from the relationship being warm rather than cold when the message landed (Belkins, LinkedIn outreach study, 2026). A commenter who engaged with a post about the exact problem you solve sits far closer to that warm end than a name pulled from a title search, and the relevance is what does the warming. That edge evaporates the moment a note meant to prove you did your homework collapses into pasting a first name. Qualification, doing enough homework to write a line that could only have been sent to that one commenter, is what makes the export worth the effort.
This is where the whole comparison resolves, specifically for comments. Pulling a post's comment list is the part every tool above does. Checking each commenter against your fit and relevance filters, and writing a note that answers what that person actually said, is the part none of them do. That is the half BeReach covers: it pulls the commenters, says which ones match who you sell to, and drafts a reply against each comment for you to approve. Sending is then paced across the day rather than fired as a burst, and roughly 100 invitations a week is the number worth planning against, industry consensus rather than published LinkedIn policy.
Every viral post is 100+ warm conversations waiting.
Tell your agent who you want to reach. It finds them, says which ones are worth your time, writes the first line, and follows up.
What is the best tool to export LinkedIn comments?
It depends on what you are doing with the list. For a one-off archive of a huge post, a dedicated single-post exporter wins on raw volume. For repeatable outreach, a free finder that reads public comments needs no setup and gets you to the useful part faster. Rank by what happens after the export, not by price.
Can you export LinkedIn post comments without connecting your account?
Yes, for public posts. A public post's comment list is publicly readable, so a finder can retrieve it without you signing in or installing anything. Comments on posts shared to a restricted audience are not publicly readable.
Chrome extension or cloud tool for exporting commenters?
An extension is quicker to get going and stops when you close the tab, which suits occasional one-off exports. A cloud tool costs more to set up but runs on a schedule and handles far more volume, which is what you want if this is a weekly motion rather than a one-time pull.
Are commenters or likers the better lead source?
Commenters, in almost every case. Commenting costs visible effort and usually reveals a viewpoint, which gives you both a stronger intent signal and a natural opening line. Liker lists are longer and weaker. Either way, the export is only worth it after you filter for fit and for how relevant the post is to what you sell.
Reading this in an AI assistant? Hand it the page and let it summarize, so you can ask follow-up questions against the whole argument rather than the part you have read so far.
