Threads Scraper — Posts, Profiles, Replies & Hashtags

Scrape Threads (threads.com) without a browser and without logging in.

Give it a keyword, a #hashtag, an @username, or any Threads URL. Get back flat rows ready for a spreadsheet, a dashboard, or an LLM pipeline.

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Why this one

Threads scrapers break in two boring ways: they don't recognise the URL you gave them, and they die the moment Meta reshuffles the page. This one is built against both.

	This actor	Typical Threads scraper
How it finds data	Walks the page's own JSON for any thread_items node	Hard-coded path into a Relay wrapper Meta reshuffles at will
URL shapes understood	profile, /replies, /media, /@user/post/CODE, /t/CODE, threads.net, ?si= tracking links	Often just the plain profile URL
Stable numeric author ID	✅ authorId on every row	Usually username only — which breaks when someone renames
One bad target	Skipped, with the reason; the rest still run	Whole run fails
What you pay for	Only rows actually delivered	Often a start fee regardless of output

If a run returns nothing, it costs you nothing. There is no actor-start charge.

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What you get

Real, unedited rows from this input:

{ "queries": ["@zuck", "#buildinpublic"], "profileTabs": ["posts", "replies", "media"], "maxItems": 25 }

→ 25 rows in one run: 1 profile + 24 unique posts, zero duplicates across the three tabs.

A post

{
  "recordType": "post",
  "code": "DVrwsE5EdSz",
  "url": "https://www.threads.com/@zuck/post/DVrwsE5EdSz",
  "text": "Meanwhile at Meta HQ",
  "authorUsername": "zuck",
  "authorId": "63055343223",
  "authorFullName": "Mark Zuckerberg",
  "authorIsVerified": true,
  "publishedAt": "2026-03-10T00:26:46.000Z",
  "likeCount": 7581,
  "replyCount": 1192,
  "repostCount": 232,
  "quoteCount": 56,
  "isReply": false,
  "mediaType": "image",
  "mediaCount": 1,
  "media": [{ "type": "image", "url": "https://instagram.fcdg4-1.fna.fbcdn.net/v/t51.82787-15/...", "width": 1080, "height": 1350 }],
  "hashtags": [],
  "sourceType": "profile",
  "sourceUrl": "https://www.threads.com/@zuck"
}

authorId is the account's stable numeric ID. Usernames get changed; this doesn't. Use it as your join key.

A profile row

{
  "recordType": "profile",
  "authorUsername": "zuck",
  "authorId": "63055343223",
  "authorFullName": "Mark Zuckerberg",
  "authorIsVerified": true,
  "followerCount": 5721349,
  "biography": "Mostly superintelligence and MMA takes",
  "bioLinks": [],
  "url": "https://www.threads.com/@zuck"
}

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Input

Field	Type	Notes
queries	array	Required. Keywords, #hashtags, @usernames, or Threads URLs — mixed freely.
profileTabs	array	Which profile tabs to pull: posts, replies, media. More tabs = more posts.
expandThreads	boolean	Also open every post that has replies and scrape the conversation. Highest yield, highest cost.
maxItems	integer	Hard cap on delivered rows — your spend ceiling. 0 = no limit.
minLikes / minReplies	integer	Drop low-engagement posts. Filtered posts are not billed.
onlyVerified	boolean	Verified authors only.
excludeReplies	boolean	Top-level posts only.
mustHaveMedia	boolean	Only posts carrying an image or video.
postedAfter / postedBefore	string	YYYY-MM-DD date window.
includeProfileInfo	boolean	Emit the extra profile row shown above.
proxyConfiguration	object	Residential strongly recommended.

Every URL shape works

@zuck                                          https://www.threads.net/@zuck
https://www.threads.com/@zuck                  https://www.threads.com/@zuck/replies
https://www.threads.com/@zuck/media            https://www.threads.com/@zuck/post/CODE
https://www.threads.com/t/CODE                 https://www.threads.com/@zuck/post/CODE?si=xyz
#buildinpublic                                 ai agents

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How much data you actually get — read this

Threads shows a limited number of posts to logged-out visitors, and this actor does not log in. Measured yield per page fetch:

Input	Posts per fetch
A post URL (post + its reply thread)	~31
Keyword search	~20
Hashtag	~18
Profile /replies tab	~8
Profile /media tab	~6
Profile main tab	~4

So a profile returns its most recent posts, not its full history. Scraping all three profile tabs is the way to widen that — measured ~18 unique posts for @zuck across three tabs versus 4 from the main tab alone — and expandThreads multiplies it further by pulling each post's replies.

If you need a complete profile archive going back months, this actor will not give you that, and no amount of retrying will change it. That is a Threads limit, not a bug, and it is stated here rather than discovered after you have paid.

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Cost

You are billed per delivered row, so the row count is the price. Rows removed by your filters, duplicates, and failed pages are all free.

Job	Rows	Cost
One profile, all three tabs	~18	~$0.05
One keyword search	~20	~$0.06
One post + full reply thread	~31	~$0.09
10 hashtags	~180	~$0.54

Set maxItems to cap any run. It is a hard ceiling.

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Honest limitations

• No full profile history. See the table above. Deeper paging sits behind Threads' internal API and is deliberately not attempted.
• language is almost always empty. Threads does not populate detected_language for logged-out requests, so there is deliberately no language filter in the input — a filter that silently keeps everything is worse than no filter at all.
• Private and non-existent accounts return nothing. You get an explicit does not exist or has no public content message, and you are not charged.
• Threads rate-limits. Each retry rotates to a fresh proxy session and re-establishes cookies, which is what actually clears a block — a fresh IP alone gets challenged again. If everything is blocked the run fails and bills nothing.
• A post with no replies yields one row. expandThreads only helps where conversation exists.

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Use it for

• Brand & competitor monitoring — watch a hashtag or keyword on a schedule.
• Creator research — recent posts, engagement counts, and verified status per account.
• Conversation mining — pull a viral post's full reply thread for sentiment or support signals.
• LLM pipelines — flat rows, no HTML, stable numeric IDs to join on.

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Scheduling

Point the Apify Scheduler at this actor with a handful of keywords and postedAfter set to yesterday to build your own Threads history over time. Because you only pay per delivered row and duplicates are removed within each run, a daily watch stays cheap.