LinkedIn Post Engagers Email Finder

Turn a public LinkedIn post URL into outreach-ready commenter leads. Paste one or more post URLs and get one dataset row per visible commenter: name, profile URL, comment text, current company, and an MX-validated work email when one can be derived. Unmatched commenters still return as rows with an honest emailStatus so you can tell a completed empty lookup from a provider outage. No LinkedIn login or cookies.

Designed for B2B sales, recruiting, and ABM teams who already have a high-intent post and need emails for the people who actually commented. This is the email-finding companion to LinkedIn Post Engagers Scraper, which stops at names and comments. When you already have /in/ URLs instead of a post, start with LinkedIn Email Finder.

What you get

Output	What it answers
engagerName + engagerProfileUrl	Who commented on the post
commentText + postUrl	What they said and which post they engaged with
currentCompanyName + companyDomain	Where they work from the public profile
email + emailStatus + emailConfidence	How to reach them, or why no email was returned
OUTPUT / RUN_SUMMARY outcomes	Provenance — complete, empty, invalid input, or upstream outage

Who it is for (and why it matters)

• Sales development reps — turn comments on a competitor or industry post into a sequenced outreach list.
• Recruiters — contact people who already showed interest in a hiring or industry conversation.
• ABM / demand-gen teams — build a warm account list from a thought-leadership post instead of a cold directory.
• AI agents — one tool call with postUrls returns structured commenter rows plus optional emails, so the agent can enrich, skip, or route without guessing.

Best fit for this Actor

• Strongest starting condition: a public LinkedIn post URL with visible comments.
• Useful output: one row per commenter, billed $0.008 for the engager and $0.04 only when an email is returned.
• Use this Actor when the starting object is a LinkedIn post URL and the job is commenter emails.
• Liker and reactor identities are outside this Actor's contract on public no-login data. For names and comments only, start with LinkedIn Post Engagers Scraper. When you already have profile URLs, then use LinkedIn Email Finder.

Input

Field	Type	Default	Description
postUrls	array (required)	1 example post	Up to 50 LinkedIn post, feed-update, or pulse URLs
maxEngagersPerPost	integer	10	Cap on commenters saved and billed per post
includeUnverified	boolean	true	Return MX-valid pattern emails when SMTP cannot confirm
providerOrder	enum	scrapecreators-first	Public-data provider priority; fallback fires automatically
maxConcurrency	integer	2	Posts processed in parallel (1–5)

Quick start input

{
    "postUrls": ["https://www.linkedin.com/feed/update/urn:li:activity:7468770468041502720/"],
    "maxEngagersPerPost": 1,
    "includeUnverified": true
}

That input selects a single public post and one commenter so the run stays inside the five-minute quality window and still returns a real row.

Example input — a few posts, larger commenter cap

{
    "postUrls": [
        "https://www.linkedin.com/feed/update/urn:li:activity:7468770468041502720/",
        "https://www.linkedin.com/posts/microsoft_activity-7468770468041502720_"
    ],
    "maxEngagersPerPost": 10,
    "includeUnverified": true,
    "providerOrder": "scrapecreators-first",
    "maxConcurrency": 2
}

Duplicate post URLs are deduplicated automatically. Profile or company URLs are skipped as invalid input.

What data you receive

One dataset item is one commenter. Email-found rows carry a work address; commenter-only rows document that the lookup finished without a billable email.

{
    "engagerName": "Jane Doe",
    "engagerProfileUrl": "https://www.linkedin.com/in/example",
    "engagementType": "commenter",
    "commentText": "Great insights on AI adoption.",
    "postUrl": "https://www.linkedin.com/feed/update/urn:li:activity:7468770468041502720/",
    "currentCompanyName": "Acme",
    "companyDomain": "acme.com",
    "email": "jane.doe@acme.com",
    "emailStatus": "mx_valid_unverified",
    "emailConfidence": 54,
    "emailSource": "derived",
    "emailFound": true,
    "smtpVerified": false,
    "provider": "scrapecreators",
    "scrapedAt": "2026-08-21T00:00:00.000Z"
}

Commenter without an email:

{
    "engagerName": "Alex Rivera",
    "engagerProfileUrl": "https://www.linkedin.com/in/example-two",
    "engagementType": "commenter",
    "postUrl": "https://www.linkedin.com/feed/update/urn:li:activity:7468770468041502720/",
    "emailStatus": "company_domain_unresolved",
    "emailFound": false,
    "provider": "scrapecreators",
    "scrapedAt": "2026-08-21T00:00:00.000Z"
}

Every terminal run also writes OUTPUT and RUN_SUMMARY with a named outcome, per-post results, provider diagnostics, and billing counters.

Workflow story: from a viral post to a sequenced outreach list

An SDR sees a competitor CEO post that attracted a wave of comments from directors at target accounts. She pastes the post URL here with maxEngagersPerPost at 20. The Actor pulls the public commenters, resolves each profile's current company website domain, and derives an MX-validated work email. Fourteen rows come back with emailFound=true; six remain commenters with company_domain_unresolved or no_profile. She filters emailFound=true, drops the comment text into her first-touch snippet, and skips paying $0.04 on the six rows that had no email. Event cost is 20 × $0.008 plus 14 × $0.04.

Use through the API

curl -X POST "https://api.apify.com/v2/acts/khadinakbar~linkedin-post-engagers-email-finder/runs?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "postUrls": ["https://www.linkedin.com/feed/update/urn:li:activity:7468770468041502720/"],
    "maxEngagersPerPost": 1,
    "includeUnverified": true
  }'

Results land in the run's default dataset: https://api.apify.com/v2/datasets/{datasetId}/items?clean=true. Paginate large batches with offset/limit. The same Actor is exposed through Apify MCP as apify--linkedin-post-engagers-email-finder.

Use with AI agents through Apify MCP

Given this LinkedIn post URL, extract the people who commented and find a work email for each one. Return name, profile URL, comment, company, and email. Keep only dataset rows where emailFound is true. Cap the run at 10 commenters.

Inspect the terminal outcome, read the dataset, keep engagerProfileUrl as the source identifier, and treat emailStatus as provenance rather than a deliverability promise. Connect through Apify MCP.

{
    "postUrls": ["https://www.linkedin.com/feed/update/urn:li:activity:7468770468041502720/"],
    "maxEngagersPerPost": 10,
    "includeUnverified": true,
    "providerOrder": "scrapecreators-first",
    "maxConcurrency": 2
}

Then read results with get-actor-output, keep emailFound=true rows for outreach, and pass remaining profile URLs to LinkedIn Email Finder only if you want a second pass from the /in/ URL.

Pricing

This Actor uses Pay per event plus Apify platform usage. Open the live Pricing tab for current event details, and use Apify's run cost controls to keep the workflow aligned with your budget.

Event	Price	Charged when
Actor start	$0.00005	Once per run (scaled by memory)
engager-found	$0.008	One commenter row saved
email-found	$0.04	Additional, only when an email is returned

Invalid input and empty posts are not billed as engager-found. Commenters without an email are billed only for engager-found.

Run	Commenters	Emails found	Event cost (approx.)
1 post, 1 row with email found	1	1	~$0.048
1 post, 10 rows, 6 emails	10	6	~$0.32
3 posts, 20 rows, 12 emails	20	12	~$0.64

A bounded 1-row quality run costs about $0.048 in events. A 10-row list with 6 emails found costs about $0.32 in events.

Your run log prints the exact cost cap before any charge fires. Platform usage is billed on top at Apify's rates — the live Pricing tab is the current source of truth.

Best results

• Start with a post that already has public comments. Empty posts finish VALID_EMPTY with no engager charges.
• Keep maxEngagersPerPost at 10 unless you need a larger list; each commenter can trigger a profile and company lookup.
• Leave includeUnverified on. Apify blocks outbound SMTP port 25, so most real-world emails are mx_valid_unverified rather than mailbox-confirmed.
• Pair commenter-only rows with LinkedIn Email Finder when you later obtain a company domain by hand.
• Validate returned addresses with Email Address Validator before a large send.

Limits, reliability, and troubleshooting

• Public no-login data exposes commenters, not liker or reactor identities. Reaction counts still appear on the post.
• Emails are derived from name + company domain (or copied from a public about section). LinkedIn does not publish a private inbox through these providers.
• SMTP mailbox confirmation almost never fires on Apify. Treat mx_valid_unverified as MX-valid, not as a deliverability guarantee.
• Provider HTTP 429 or 5xx with zero rows maps to UPSTREAM_FAILED. Retry later rather than converting that into a hollow success.
• Provide a real post URL, not a profile or company page. Invalid shapes finish INVALID_INPUT with zero charges.

Builder's note

I built this after shipping LinkedIn Post Engagers Scraper and LinkedIn Email Finder as separate tools and watching users chain them by hand. In my testing of ScrapeCreators and SociaVault, commenter identities are public and liker identities are not. I learned that neither provider returns LinkedIn emails, so the working path is the same derive-and-MX-validate engine already proven on LinkedIn Email Finder, plus a public-about regex for the rare profile that already shows an address. That is why this Actor bills the commenter row separately from the email, and why emailStatus stays in the dataset even when email is empty.

Responsible use

Use this Actor on public LinkedIn posts you are authorized to process for legitimate sales, recruiting, research, or verification. It reads public post comments and public LinkedIn profile pages only. It does not log into LinkedIn, does not use your cookies, and is not a private people-graph or data-broker dump. Follow GDPR, CCPA, CAN-SPAM, LinkedIn's terms, and any local law that applies to your outreach. Honor opt-out and do-not-contact requests.

This tool is provided for lawful public-data collection. You are responsible for how you use the output.