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MCPToolsScrape X Post Commenters

X Post Commenters

Give it an X (Twitter) post URL, get back the accounts that commented on it.

Tool
x_post_commenters
Cost
0.3 credits per profile scraped
Category
Social Signals
Required input
post_url
Returns
Accounts that commented on the post

What it does

  • Returns the accounts that commented on an X post.
  • Useful for building warm lead lists from an engaged audience: people who replied to a post about your problem space already care about it.
  • Returns X accounts, not LinkedIn profiles. There is no email in the response.

This gives you handles. To reach a work inbox you need a LinkedIn profile first — match the person with find_people, then run find_work_email.


Use cases

  • Build a warm list from a relevant thread. People who replied to a post in your category have already engaged with the topic in public.
  • Mine a competitor’s replies. The accounts arguing under a rival’s post are users, evaluators and switchers.
  • Follow up on your own posts. Everyone who replied is a list you earned rather than sourced.
  • Find practitioners for research. Reply threads surface the people who actually do the work, not just the ones who market it.

How to use it

Connect the MCP server

Follow the setup guide for your client. Browser sign-in, no API key.

Find the post

Get the recent posts from @stripe and show me the ones about revenue operations with the most replies.

Pull the commenters

Get the commenters on that X post. 500 results.

Filter to real prospects

Drop accounts with no bio, no company and fewer than 50 followers. Keep the ones whose bio names a job title.

Cross over to LinkedIn

For the accounts that survived, search for a matching LinkedIn profile by name and company. Only keep confident matches.

Example prompts

Ask your clientWhat you get back
”Who commented on this X post?”Commenting accounts with their comment text
”Commenters on this post, 500 max”A larger single-call pull
”Commenters, keep only bios that mention a company”A filtered warm list
”Find posts from this profile first, then their commenters”Chains x_profile_posts — 0.3 credits per post

Best prompting practices

  • Set max_results deliberately. The default of 100 truncates a busy thread; 1000 on a quiet one just returns everything available. You pay per profile returned, so the ceiling is a budget, not a target.
  • Filter on the bio. X bios are the only firmographic signal in the response. No bio usually means no usable prospect.
  • Say the bio rule in the prompt. “Keep accounts whose bio names a founder, sales or RevOps role, drop the rest, tell me how many survived.” Filtering after the scrape is free; leaving it undefined means you read all 400 yourself.
  • Ask for the reply text. Handle, bio, follower count, profile URL and what they actually wrote — the reply is the reason to reach out.
  • Do not expect emails. This tool returns social accounts. Any email has to come from a separate enrichment step.
  • Deduplicate across threads. The same accounts reply to everything in a niche — collapse on handle and count appearances rather than treating each thread as a new list.
  • Pick topic posts over brand posts. A reply to “here is how we forecast” beats a reply to a product announcement.
  • Batch by post, not by account. One call covers a whole thread — there is no reason to run it per person.

Output

{ "commenters": [ { "username": "janedoe", "name": "Jane Doe", "bio": "VP RevOps", "comment": "We hit exactly this problem last quarter." } ] }

Credits and limits

0.3 credits per profile returned. max_results accepts 1–1000 and defaults to 100, so a default call costs up to 30 credits. Maximum 1000 commenters per call. Run check_credits (free) before working through a list of posts.

A high max_results does not create commenters that are not there. If a thread has 40 replies, asking for 1000 returns 40 and bills for 40 — 12 credits.


Parameters

ParameterTypeRequiredNotes
post_urlstringYesFull X post URL
max_resultsnumberNo1–1000, default 100

ToolUse it instead when
x_profile_reactionsYou want one profile’s posts with per-post reaction totals rather than the accounts that reacted — 0.3 credits per post
x_profile_postsYou need the post URLs first — 0.3 credits per post
linkedin_post_commentersYou want the same play on LinkedIn, where profiles carry job titles — 0.3 credits
tiktok_comments_from_postYou want the same play on TikTok — 0.3 credits per comment

Next steps


Keep learning

Two courses take these tools past the reference page — clustered by GTM job, then chained into workflows.