X (Twitter) Replies Scraper | $0.00015/Reply | Pay-Per-Result

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Xquik is the world's fastest & cheapest X (Twitter) scraper service with the most complete X data. Xquik's X (Twitter) Reply Scraper collects replies, comments & whole conversations. In public benchmarks, it reads replies 1.7x faster than 4 other Actors. It also costs the least per useful reply, as the benchmark below shows. Most other Apify Actors charge before filtering or deduplicating. Xquik charges only for delivered, unique, filter-matching results.

Scrape Twitter replies & comments for $0.00015 per delivered row on every Apify plan, & read them without an X account. Paste post URLs, Tweet IDs, profile URLs or usernames. Export replies, conversations, authors, engagement, entities & media URLs. Apify bills your platform usage separately. You need no X account. Filters run before dataset writes, so you pay only for delivered rows.

Xquik is an independent third-party service. Not affiliated with X Corp. "Twitter" and "X" are trademarks of X Corp.

What does X (Twitter) Reply Scraper do?

Xquik's X (Twitter) Reply Scraper collects public replies & comment conversations. It handles single posts, bulk URL lists, Tweet IDs & user reply timelines.

Use cases

• Measure sentiment & customer feedback under brand & product posts.
• Rank the most liked replies & comments under a viral post.
• Find leads who ask questions or name a need in public replies.
• Review replies for moderation, spam & abuse.
• Rebuild whole conversations for research & AI training datasets.
• Track how an account replies to its customers over time.

Why use X (Twitter) Reply Scraper?

• 1.7x faster reply exports. Its median run was 1.7x faster than the fastest of 4 other Actors. The benchmark ran on 2026-10-15.
• Lowest cost per useful reply. It cost the least per useful reply in the benchmark.
• 2x the fields per reply. Its median row had 100 fields in the benchmark. That is 2x the median of the other Actors.
• Pick the conversation shape. Keep direct replies, nested replies or both, down to the depth you set. collectionStrategy can also return the thread or only hidden replies.
• Rebuild every thread. Each reply carries its parent in inReplyToId, its root in rootTweetId & its depth.
• Many posts in 1 run. Paste post URLs, Tweet IDs, profiles & usernames together. A username returns that account's replies.
• Only the replies you want. Filter by words, hashtags, author, language, verification, engagement, media & date.
• Sort by likes or date. Rank replies by likes, or list the newest or oldest first. Rows come compact, full or rich, in camelCase or snake_case.
• Continue big threads later. A run that stops early saves each target's place in next-cursors. Pass 1 as startCursor to continue.

Complete results

• Complete mode adds replies the author hid & explains empty threads.
• Each answer holds the fullest data X has for it.

Accurate rows

• A post is called missing only when it's gone.
• Reposts carry the full original text.
• Every ID in a row stays exact.
• Mentions, links, hashtags & highlights line up with the text.
• A count that isn't known is listed in unknownCounts, never shown as 0.
• Verified badges match what x.com shows.
• Rows hold public data only.
• Runs count the replies they didn't reach.
• Ads & promoted entries never reach your rows.

Fresh data

• Reads keep working when X ships changes.

Speed

• One slow page doesn't hold up your run.
• Actors read many handles, posts & queries at once.
• Reads finish the moment their rows arrive.
• Stalled Actor calls recover on their own.

Fair billing

• Bad input costs nothing & tells you what to fix.
• Actors charge only for delivered, unique, matching rows.
• A restarted run never charges twice.
• Runs stay within your spend cap & still write their diagnostics.
• Tweet, reply & follower run reports estimate what the run cost.
• Small runs end with a tip that cuts cost.

Reliability

• A one-off error doesn't fail your run.
• A deadline returns the rows already found, with diagnostics.
• Actors ride out short Xquik outages.
• Actor runs survive restarts without repeats.
• One bad row doesn't sink a batch.
• Stopped runs keep their rows & their report.
• A run that can't start still explains itself.
• Support can see exactly what a request or run returned.

Built for agents

• Actors accept input written for other Actors.
• Output is ready for spreadsheets, with flat columns & engagement totals.
• Scraper datasets describe every field.
• Every run says why it ended & whether to retry.

Rich data

• Posts carry note text, edits, Community Notes, reach labels, reply controls & live events.
• Rows carry source apps, media counts & professional account data.
• Media comes with variants, alt text, sizes & availability reasons.

Quality checks

• Every field X shows is served, left out on purpose or proven absent.
• Xquik tests every read live against X.

What data can X (Twitter) Reply Scraper extract?

The dataset & run-report schemas describe every returned field. Text, number & boolean fields also carry examples for agents & generated integrations.

Every full reply row can include these core fields.

Field	Description
id	Reply ID
text	Reply text
fullText	Long-form reply text
createdAt	Reply timestamp
lang	X language code
url	Direct reply URL
conversationId	X conversation ID
inReplyToId	Immediate parent ID
inReplyToUserId	Parent author ID
inReplyToUsername	Parent username
likeCount	Likes
replyCount	Child replies
retweetCount	Reposts
quoteCount	Quotes
viewCount	Views
bookmarkCount	Bookmarks
author	Available public author metadata
media	Images, videos, GIFs, and variants
entities	Hashtags, cashtags, mentions, URLs & video timestamps
quoted_tweet	Quoted post when available
retweeted_tweet	Reposted post when available

Full rows also keep available source metadata.

• Post type fields are type, isReply, isQuoteStatus, isNoteTweet, isLimitedReply & isTranslatable.
• Text details are displayTextRange, noteTweet, article, card & cashtagAttachments.
• Labels & notices are contentDisclosure, communityNote, possiblySensitive, softIntervention, tombstone & exclusiveContent.
• Conversation details are conversationControl, limitedActions, subscriberBadge & unmentionedUserIds.
• Context fields are source, place, communityId, communityName, reactionContext, liveEventContext & postCta.
• Edit & availability fields are edit, previousCounts, viewState & authorUnavailable.

Flat rows keep conversation ancestry, source details, result type & schema version. See OpenAPI for the exact fields.

How do I use X (Twitter) Reply Scraper to scrape replies?

New to Apify? Create a free account first. The free plan needs no credit card & gives $5 to spend each month. At $0.00015 per row, $5 pays for up to 33,000 rows before platform usage. Then come back here & press Try for free.

1. Paste post URLs, Tweet IDs, profile URLs or usernames.
2. Set maxItems, scope & the filters your job needs.
3. Run Xquik's X (Twitter) Reply Scraper & open the dataset.

The form comes filled with a public conversation we tested. It returns up to 1,000 full, flat rows. Auto mode collects the full conversation by default. Deduplication & source attribution stay on.

Scrape replies from a post URL

{
  "startUrls": [{ "url": "https://x.com/OpenAI/status/2082577277246972300" }],
  "maxItems": 100
}

Scrape replies from tweet IDs

{
  "tweetIds": ["2082577277246972300", "2083148725367783580"],
  "maxItemsPerTarget": 100,
  "maxItems": 10000
}

Collect the full nested conversation

{
  "tweetIds": ["2082577277246972300"],
  "collectionStrategy": "conversationSearch",
  "scope": "all",
  "maxDepth": 5,
  "sort": "oldest",
  "maxItems": 500
}

Scrape a user's reply timeline

{ "usernames": ["OpenAI", "apify"], "maxItems": 10000 }

Filter replies before billing

{
  "tweetIds": ["2082577277246972300"],
  "anyWords": ["API", "agent", "developer"],
  "excludeWords": ["airdrop", "giveaway"],
  "lang": "en",
  "minLikes": 2,
  "minViews": 100,
  "verifiedOnly": true,
  "maxItems": 10000
}

Export flat CSV-friendly rows

{
  "tweetIds": ["2082577277246972300"],
  "outputMode": "full",
  "outputPreset": "flat",
  "fieldStyle": "camelCase",
  "maxItems": 100
}

Task examples

Choose from 50 public tasks. Each has a bounded input & a matching dataset view. Edit any task before you run it.

• Scrape X post replies & Twitter comments
• Scrape bulk Twitter replies
• Rebuild a Twitter reply conversation
• Rank Twitter replies by likes
• Scrape latest Tweet replies
• Remove spam from Twitter replies
• Scrape English Twitter replies
• Scrape verified Twitter replies
• Scrape Twitter replies with media
• Scrape a user's Twitter reply timeline
• Collect Twitter replies for AI agents
• Build an X reply RAG dataset
• Archive Twitter replies for LLMs
• Extract X reply leads for CRM

How much does it cost to scrape X replies?

Xquik's X (Twitter) Reply Scraper costs $0.00015 per delivered row on every Apify plan. Apify bills platform usage separately.

For more volume, pick an Apify plan with more prepaid usage.

Xquik applies one charge per delivered data row. Replies that your filters or deduplication remove cost nothing. Diagnostic records in diagnostics are free. No start, URL, query, pagination or filter fee applies.

Benchmark

Xquik's X (Twitter) Reply Scraper & 4 other Actors read 200 replies to 1 post. That post is public & has 2,800+ replies. Xquik's median run was 1.7x faster than the fastest other Actor. It also cost the least per useful reply. Its median row had 100 fields, 2x the median of the others. A useful reply is unique & sits in that post's thread.

• xquik/x-reply-scraper delivered 200 useful replies at $0.000156 per useful reply, 19.7 per second & 100 fields per row. View run
• xquik/x-reply-scraper delivered 200 useful replies at $0.000156 per useful reply, 16.5 per second & 101 fields per row. View run
• xquik/x-reply-scraper delivered 200 useful replies at $0.000157 per useful reply, 14.4 per second & 101 fields per row. View run
• xquik/x-reply-scraper delivered 200 useful replies at $0.000157 per useful reply, 13.6 per second & 101 fields per row. View run
• xquik/x-reply-scraper delivered 200 useful replies at $0.000156 per useful reply, 16.5 per second & 100 fields per row. View run
• xquik/x-reply-scraper delivered 200 useful replies at $0.000157 per useful reply, 11.3 per second & 100 fields per row. View run
• xquik/x-reply-scraper delivered 200 useful replies at $0.000156 per useful reply, 20.1 per second & 100 fields per row. View run
• xquik/x-reply-scraper delivered 200 useful replies at $0.000156 per useful reply, 20.6 per second & 100 fields per row. View run
• kaitoeasyapi/twitter-x-data-tweet-scraper-pay-per-result-cheapest delivered 200 useful replies at $0.000220 per useful reply, 9.6 per second & 50 fields per row. View run
• kaitoeasyapi/twitter-x-data-tweet-scraper-pay-per-result-cheapest delivered 200 useful replies at $0.000220 per useful reply, 8.1 per second & 50 fields per row. View run
• scraper_one/x-post-replies-scraper delivered 200 useful replies at $0.000263 per useful reply, 6.6 per second & 15 fields per row. View run
• api-ninja/x-twitter-replies-retweets-scraper delivered 200 useful replies at $0.000400 per useful reply, 5.0 per second & 33 fields per row. View run
• apidojo/tweet-scraper delivered 199 useful replies at $0.000402 per useful reply, 6.7 per second & 51 fields per row. View run

All runs took place on 2026-10-15 on the Bronze tier. Cost is the customer's total spend per useful result. Ours includes the Apify usage our customers pay. Fields per row is the median count of non-empty fields. That count includes nested fields, & a list counts as 1. Open a run for its input, log & dataset.

Empty, partial & stopped runs

Xquik's X (Twitter) Reply Scraper explains empty, partial & stopped runs for free. The run status says why the run stopped. It also counts charged results & targets read. A run that reads every target & finds no reply writes no record. Its status says why & what to change.

Incomplete extraction

An interrupted run writes a free partial diagnostic. Available results stay intact. Read availableResults, failedTargets, retryable & nextAction before you retry. A successful Actor exit confirms delivery, not complete extraction.

The status names every cause of an early stop. stopCauses lists each cause with its own message, retryable & nextAction. The causes are target_not_found, target_failed, reply_reach & deadline_reached. reply_reach means X served only part of a thread.

A missing post or account does not count as a failure. The status names it, such as "X has no match for 1 target." It joins stopCauses only when another cause stopped the run. The run is retryable when any cause is.

Diagnostics

Successful data rows use resultType: "reply". A run that needs attention writes exactly 1 free record to diagnostics. Examples are an invalid input, a skipped target or an early stop. The record says how to fix the problem. A run that reads every target & finds no reply writes none. Its status says why.

The run status says why the run stopped. It also counts charged results & targets read. Runs with a problem always write run-report, including no-input and invalid-input exits. A large run writes it too. A small run that goes well skips it & saves Apify usage. Turn on alwaysSaveRunRecords to write it on every run.

The report schema documents completion, billing, failures & saved cursors. Its version field reports the exact published Actor source version.

The status field uses these values.

• no-input
• invalid-input
• replies-incomplete
• zero-output
• aborted
• unexpected-error

Input

The Input tab lists every option. Give at least 1 post URL, Tweet ID, profile URL or username. Every other field is optional.

Reply targets & input aliases

Use these primary fields.

Input	Purpose
startUrls	Mixed X post and profile URLs
tweetIds	Numeric post IDs
usernames	Profile reply timelines
startCursor	Resume one target from a saved cursor

The input form shows canonical controls only. Compatibility aliases still work in JSON, API, SDK, automation & saved task inputs. When you combine canonical & alias fields, their existing resolution order applies.

These aliases accept common field names from other scrapers.

• URL aliases are urls, tweetUrls, postUrls, profileUrls, & twitterUrl as one string.
• ID aliases are conversationIds, postIds, ids, tweetId, id.
• Username aliases are twitterHandles, screenname.
• Global limit aliases are maxResults, max_results, resultsLimit, maxReplies.
• Per-target aliases are maxRepliesPerTweet, maxCommentsPerPost, resultsPerCategory.
• The search alias is useSearch.
• Nested reply aliases are includeNestedReplies, includeRepliesOfReplies.
• The depth alias is depth as 1, 2 or 3 for maxDepth. full sets no limit.
• The scope alias is onlyDirectReplies for scope: "direct".
• Original post aliases are includeOriginalTweet, includeSourceTweet. With includeSourceTweet, resultsPerCategory caps the replies & the post is 1 more row.
• The author alias is excludeOpSelfReplies for excludeOriginalAuthor.
• Sort aliases are sortBy & queryType for sort. top, newest & mostLiked read as relevance, latest & likes.
• Output aliases are outputVariant, includeRaw.

category set to replies changes nothing. A category that is another Actor's job, such as retweets or info, stops the run. It reads & charges nothing. The message names the Actor to use. When you set one of these aliases & its canonical field, the canonical value wins. The run log names the alias that lost.

Malformed or unsupported targets do not fail the Actor. When no valid target remains, the run writes a diagnostic with the fix.

Coverage strategies

Pick how the Actor collects replies. Auto fits most jobs.

Auto complete

Use collectionStrategy: "auto" for most jobs. It collects every reply it can reach for your scope. Scope, depth, sort & author controls apply before your limits. It includes replies below non-root targets. When X hides part of a thread, the status says how many replies X hides. A thread run continues with auto when X's thread view ends before your limits. The other collectionStrategy values never switch modes.

A coverage figure in diagnostics does not prove X has no more replies. Limits, missing data or errors can leave a run incomplete.

Direct replies

Use collectionStrategy: "replies" for direct replies in X's own order. It supports saved cursors.

Conversation search

Use collectionStrategy: "conversationSearch" for broad conversation coverage.

Full thread context

Use collectionStrategy: "thread" to read the source conversation context. Set includeOriginalPost: true to keep the root post as depth 0. When X's thread view ends before maxItems, the run continues with auto.

Hidden replies

The default auto strategy adds the replies the post's author hid. Each one is a row with resultType: "hiddenReply", at the usual row price, & counts toward maxItems. A post without hidden replies costs nothing extra. Set includeHiddenReplies: false to leave them out.

Use collectionStrategy: "hiddenReplies" for the hidden replies alone. X lists them oldest first, with the replies to them. A post without hidden replies returns no rows.

Direct & nested reply controls

Use scope to choose the result shape.

Value	Result
direct	Keep depth 1 replies
nested	Keep replies to replies at depth 2+
all	Keep every available direct and nested reply

Use maxDepth to limit nesting. When X omits a conversation ancestor, the parent link can be missing. The Actor preserves the best available depth.

Sorting

Use sort with these values.

• relevance keeps X source order
• latest sorts newest first
• oldest sorts oldest first
• likes sorts highest like count first

likes runs can miss some replies.

Profile targets collect your requested count of unique, filtered results, then sort them. Tweet targets keep global sorting.

The sortBy & queryType compatibility aliases still work.

Reply filters

All supported filters run before dataset writes.

Text & entity filters

Input	Behavior
exactPhrase	Require one exact phrase
anyWords	Require at least 1 word or phrase
excludeWords	Remove matching words or phrases
keywordInclude	Alias merged with anyWords
keywordExclude	Alias merged with excludeWords
hashtags	Require at least 1 hashtag
cashtags	Require at least 1 cashtag
mentioning	Require an @mention

Author & language filters

Input	Behavior
fromUser	Keep one reply author
toUser	Keep replies addressed to one username
lang	Keep one X language code
verifiedOnly	Require any public verification signal
blueVerifiedOnly	Require X Premium verification
excludeOriginalAuthor	Remove source-author self-replies

Engagement filters

Use minLikes, minReplies, minRetweets, minQuotes, minViews & minBookmarks. The minFaves alias maps to minLikes.

Media & time filters

• Set hasMediaOnly: true for replies with public media.
• Set mediaType to any, image, video, gif or link.
• Set mediaType to none for text replies without media or links.
• Set since for an inclusive start timestamp.
• Set until for an exclusive end timestamp.
• Use sinceTime & untilTime as compatibility aliases.

Output

Each reply row is a JSON object. The dataset & run-report schemas describe every field, so AI agents can read rows without guessing. Export the dataset as JSON, CSV, Excel or HTML.

Author metadata

Nested authors follow the public profile contract. It covers identity, counts, verification, availability, professional data & profile biographies.

Flat output adds authorId, authorUsername, authorName, authorFollowers, authorFollowing & authorVerified.

Media metadata

Media covers availability, geometry, tags & video variants. It also has the watchNowUrl & visitSiteUrl actions.

Flat output adds mediaUrls.

Output example

A trimmed reply row looks like this.

{
  "resultType": "reply",
  "id": "1881423000000000000",
  "url": "https://x.com/example/status/1881423000000000000",
  "text": "Thanks for sharing this update.",
  "createdAt": "2026-08-09T12:00:00.000Z",
  "lang": "en",
  "conversationId": "1881422000000000000",
  "rootTweetId": "1881422000000000000",
  "parentReplyId": "1881422000000000000",
  "depth": 1,
  "isDirectReply": true,
  "likeCount": 42,
  "replyCount": 3,
  "retweetCount": 5,
  "quoteCount": 2,
  "viewCount": 1000,
  "bookmarkCount": 7,
  "authorUsername": "example",
  "authorName": "Example User",
  "authorFollowers": 1000,
  "authorVerified": false,
  "mediaUrls": ["https://pbs.twimg.com/media/example.jpg"],
  "sourceTweetId": "1881422000000000000",
  "sourceTarget": "1881422000000000000"
}

Sample values are illustrative. Real runs return live data.

Output modes

Pick how wide each dataset row is.

Compact

Set outputMode: "compact" for a narrower dataset. It keeps text, conversation, author, engagement & media fields.

Full

Set outputMode: "full" to keep every supported public field.

Rich

Set outputMode: "rich" for the most data per row. Rich rows keep every full column & add hasCommunityNotes, quotedTweetPermalink, unavailableAuthorId & media sourceUser at the end.

Raw

Set outputMode: "raw" to add a sanitized source snapshot under raw.

Nested or flat

The default flat layout keeps nested objects & adds author fields for tables. Set outputPreset: "nested" to omit the added flat fields.

Field naming

Set fieldStyle to source, camelCase or snake_case. The Actor avoids overwriting colliding source keys.

Output columns

8 inputs shape each row after the run reads it. They run no code & change no price.

Field	What it does
fields	Keep only these fields, in the order & spelling you write
omitFields	Drop these fields & keep the rest
renameFields	Move a field to a column with a new name
flatten	Turn each nested object into top-level columns
fillMissingFields	Fill a kept field a row lacks with null. On by default
joinFields	Turn each of these lists into 1 text value
joinSeparator	Text between joined items. The default is a comma & a space
constantFields	Add a column with the same text on every row

• Use a dot for a field inside an object, such as author.id. Case & underscores do not matter.
• Every row keeps its id.
• With fields, a field a row lacks arrives as null. Every row then has the same columns.
• A wrong field name stops the run before it reads & charges nothing.
• If names cannot be checked, the run reads on & lists unseen names last.
• The run ignores a map function or jq filter written for another Actor.

Name a computed column in fields or renameFields to add it.

Column	Formula
totalEngagement	likeCount + replyCount + retweetCount + quoteCount. A missing count adds 0
engagementRate	totalEngagement × 100 ÷ the author's followers, to 4 decimals
engagementPerView	totalEngagement × 100 ÷ viewCount, to 4 decimals

totalEngagement is null for a row without those counts. A rate is null when its divisor is missing or 0.

Run options

Limits, billing & continuation

maxItems limits delivered rows across the run. maxItemsPerTarget limits each post or profile.

One run can read many targets. Caps, deduplication, attribution & billing stay exact across them.

The Actor removes duplicate rows before output & billing. Set dedupeAcrossTargets: false to keep duplicate rows from different targets.

After a run stops at its time limit, read next-cursors from the default key-value store. Pass one cursor through startCursor to continue that target.

Apify timeout

The default Apify timeout is 0, so runs have no time limit. The Actor continues until it reaches the cap or runs out of eligible data. You can still set a finite Apify timeout. Then completionReason: "deadline_reached" means that limit is near. The Actor saves replies & the report, then exits cleanly before the limit. Delivered replies bill once. Unfinished targets stay resumable.

API examples

Each example runs Xquik's X (Twitter) Reply Scraper & returns the dataset items. Replace <APIFY_API_TOKEN> with your Apify API token.

JavaScript

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<APIFY_API_TOKEN>' });
const run = await client
  .actor('xquik/x-reply-scraper')
  .call({
    tweetIds: ['2082577277246972300'],
    collectionStrategy: 'auto',
    scope: 'all',
    maxItems: 100,
  });

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Python

from apify_client import ApifyClient

client = ApifyClient("<APIFY_API_TOKEN>")
run = client.actor("xquik/x-reply-scraper").call(run_input={
    "tweetIds": ["2082577277246972300"],
    "collectionStrategy": "auto",
    "scope": "all",
    "maxItems": 100,
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

cURL

actor=xquik~x-reply-scraper
curl "https://api.apify.com/v2/acts/$actor/run-sync-get-dataset-items" \
  -X POST \
  -H "Authorization: Bearer <APIFY_API_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"tweetIds":["2082577277246972300"],"maxItems":100}'

Automation & integrations

Run Xquik's X (Twitter) Reply Scraper through Apify schedules, webhooks or API clients. Connect it to Make, Zapier, n8n, Google Sheets or cloud storage. Agents can call it through the Apify MCP server.

Eligible agent workflows can also use x402 or Skyfire.

Xquik also offers 86 dashboard tools, a REST API, signed webhooks & an MCP server.

AI agent & MCP readiness

Run Xquik's X (Twitter) Reply Scraper through Apify MCP, API clients, x402 or Skyfire.

• Limited permissions protect unrelated Apify account data.
• Pay-per-event billing ties cost to delivered results.
• Standby mode stays off for compatibility with agentic payments.
• Typed schemas describe replies, run reports & continuation cursors.
• Bounded defaults prevent accidental unbounded agent runs.
• Stable camelCase & snake_case modes simplify tool chaining.
• Diagnostic rows include a status, a message & a recovery action.
• Run reports include exact outcomes, stop reasons & charge estimates.

Always use the latest build

Select latest for every run to get all published fixes.

If you specify no build, Apify uses this Actor's latest default. Console runs & standard API examples inherit that default.

Saved tasks may override the Actor default. Schedules & task integrations reuse that choice. Keep every override set to latest.

Apify does not redirect exact build numbers to latest. Replace pinned numbers with latest. Use exact builds only for temporary rollbacks.

Related Xquik Actors

Every Xquik Actor shares the same extraction engine, filter-first billing & diagnostics. Pick the one that matches the data you need.

• X (Twitter) Tweet Scraper scrapes tweets from searches, profile timelines, Lists & tweet IDs with 50+ filters & flat exports. Use it when you need tweet data without analysis. From $0.00015 per row.
• X (Twitter) Profile Scraper scrapes profiles plus their posts, replies, media & followers from handles, IDs or URLs. Use it when you start from accounts rather than searches. From $0.00015 per row.
• X (Twitter) Engagement Scraper scrapes replies, quotes, retweeters & threads for post URLs or IDs in bulk. Use it when you measure who engaged with posts. From $0.00015 per row.
• X (Twitter) Quote Tweets Scraper scrapes the quote tweets of posts with text, media, counts, authors & 11 filters. Use it when you study who quoted posts & what they said. From $0.00015 per tweet.
• X (Twitter) Follower Scraper scrapes followers, following, List members, subscribers & Community members as profile rows. Use it when you need audience or member lists. From $0.00015 per profile.
• X (Twitter) User Search Scraper searches users by handle, bio & location with follower, verification, age & location filters. Use it when you build account lists from search. From $0.00015 per profile.
• X (Twitter) Account Location Scraper checks where accounts are based with X's "Account based in" label, "connected via" & username changes. Use it when you vet where accounts are based. From $0.00015 per account.
• X (Twitter) Email Scraper gets the emails, phones & links accounts publish on their profiles, from handles, followers or user searches. Use it when you need the emails profiles publish. From $0.00015 per profile.
• X (Twitter) List Scraper scrapes List posts, members & followers from List URLs or IDs. Use it when a curated List defines your sources. From $0.00015 per row.
• X (Twitter) Community Scraper scrapes Community info, posts, searches, members & moderators. Use it when your sources are X Communities. From $0.00015 per row.
• X (Twitter) Space Scraper finds Spaces by keyword & reads their titles, states, times, listener counts, hosts & speakers. It also reads broadcasts by URL or ID. Use it when you track live audio & video on X. From $0.00015 per Space or broadcast.
• X (Twitter) Trends Scraper scrapes real-time trends by location with rank, volume, query & WOEID. Use it when you track what is trending where. From $0.00015 per trend.
• X (Twitter) Jobs Scraper scrapes X job listings by keyword, place, workplace, seniority & company, with salaries & apply links. Use it when you collect job openings posted on X. From $0.00015 per job.
• X (Twitter) Article Scraper scrapes long-form X Articles as Markdown & text with covers, authors, dates & metrics. Use it when you need article bodies, not tweets. From $0.00015 per article.
• X (Twitter) Media Downloader extracts or stores photos, videos & GIFs from posts or profiles with MP4 & metadata options. Use it when you need the media files themselves. From $0.00015 per media row.
• X (Twitter) Brand Monitoring with AI Analysis tracks brand mentions with AI relevance, sentiment & customer-experience answers & compares runs. Use it when you watch a brand over time. From $0.0003 per analyzed tweet.
• X (Twitter) Tweet Sentiment Analysis with AI labels attitude, intensity & sarcasm probability for every tweet with AI. Use it when you need general sentiment on any topic. From $0.0003 per analyzed tweet.
• X (Twitter) Stock & Crypto AI Trading Signals labels bullish, bearish, neutral or mixed stance, content type, conviction & asset relevance with AI. Use it when you follow stocks, crypto or trading talk. From $0.0003 per analyzed tweet.
• X (Twitter) News Monitor with AI Analysis labels news posts by format, source attribution & topic relevance with AI. Use it when you separate reporting from commentary. From $0.0003 per analyzed tweet.
• X (Twitter) Tweet Classifier with AI Analysis answers your own category, score & yes/no questions for every tweet with AI. Use it when the preset analyses do not fit your labels. From $0.0003 per analyzed tweet.
• X (Twitter) Tweet Viral Score Analyzer with AI estimates a Viral Score from 0 to 100 & a verdict for every tweet from 8 AI trait answers. Use it when you study why tweets spread or flop. From $0.0003 per analyzed tweet.
• X (Twitter) Monitor catches every new tweet, reply, quote, repost & profile change of accounts, usually in under a second after X shows it, plus keyword tweets & follows. Use it when you need alerts as soon as X shows a tweet. From $0.0045 per monitor-hour.
• X (Twitter) to Discord Bot sends every new tweet, reply, quote & repost of accounts to a Discord channel through its webhook, with no bot to host. Use it when you want an account's tweets in a Discord channel. From $0.0045 per monitor-hour.
• X (Twitter) Crypto Tracker tracks the tweets, deleted tweets, profile changes & follows of crypto accounts & KOLs, plus cashtag tweets. Use it when you act on what crypto accounts post or follow. From $0.0045 per monitor-hour.
• X (Twitter) Follower Tracker tracks the new & lost followers of an account, & whom it follows or unfollows, with each account's full profile. Use it when you read an account's followers or follows as a signal. From $0.0045 per monitor-hour.
• X (Twitter) Post Tracker records the views, likes, reposts, replies, quotes & bookmarks of chosen posts on each run, with the change since the last run. Use it when you track how posts perform over time. From $0.00015 per snapshot.

FAQ

Answers to common questions, then where to get help.

How do I scrape the comments on a tweet?

Paste the post URL into startUrls & click Start. X calls comments replies, so each comment is 1 reply row.

Can I scrape replies from many tweets at once?

Yes. Paste many post URLs or Tweet IDs in 1 run. Each reply keeps the source post in sourceTarget.

Does it include nested replies?

Yes. The default scope collects direct & nested replies. Set scope to direct for replies to the post only. maxDepth limits how deep a run goes.

Does it get replies the author hid?

Yes. The default auto strategy adds them as hiddenReply rows. Set includeHiddenReplies: false to skip them.

Can I sort replies by likes or date?

Yes. Set sort to rank replies by likes, or to list the latest or oldest first.

Can I export replies to CSV or Excel?

Yes. Export the dataset as CSV, Excel, JSON or HTML. Flat output keeps 1 reply per row with author fields beside it.

Can I scrape a user's replies instead of a post's?

Yes. Paste a profile URL or a username. The run reads that user's reply timeline.

Do I need an X account or an X API key?

No. You need no X account or X API key. Paste a post link & the run reads its public replies.

Is it legal to scrape X replies?

Xquik's X (Twitter) Reply Scraper collects public replies & does not bypass protected accounts. Collect only public data. Follow applicable laws & platform rules.

Reply datasets can contain personal data. Choose a lawful purpose. Minimize retention. Protect exports. Honor deletion & access requests where required. Ask qualified counsel when uncertain.

Why did my run return fewer replies than the post shows?

When X hides part of a thread, the status says how many replies X hides. If a run stops early, its status says how many replies it didn't reach. X's reply count for the post sets the total. When a date sort may skip replies between rows, the status says so. reply_reach in stopCauses means X served only part of a thread. Filters, deduplication, scope, maxDepth & your limits also lower the count.

Can I use the API, schedules & integrations?

Yes. The API tab shows Python, JavaScript & cURL examples. Use Apify schedules to run Xquik's X (Twitter) Reply Scraper on a cron. It also connects to Make, Zapier, n8n & Google Sheets.

Where do I get help?

Open an issue in the Issues tab with the run ID.

Can I get a custom solution?

Yes. Describe what you need in the Issues tab. Xquik also offers a dashboard, a REST API, an MCP server & webhooks. Find Xquik's website on its Apify profile.