Threads Search API
Scrape Threads Search data with one API call. Searches Threads for posts matching a keyword query. Returns a list of matching posts with text content, like counts, author info, and creation timestamps. Posts filed under a Threads topic tag also carry that tag name at `post.ext.topic_tag` (e.g. `bali`, `dokter gigi`) with its stable id at `post.ext.topic_tag_id`, so you can group or filter results by topic client-side; both are absent on untagged posts, which are the majority. Threads exposes no tags-only search mode upstream, so this stays a keyword query. Search rows carry the same media shape as the other post lanes: carousel posts return every slide as an array in `content.media_urls`, video posts return a playable video URL there with the cover frame in `content.thumbnail_url`, and a quote post's attached content is recoverable at `post.ext.quoted_post`. `post.ext.quote_count` and `post.ext.reshare_count` complete the reshare picture that `engagement.shares` only starts. `engagement.views` and `post.flags.pinned` are null on a plain call, because Threads publishes them only on `/v1/threads/post`; send `include=engagement` and the first 20 posts are looked up there by permalink in the same call, and only those two leaves (plus a missing display name) are copied onto each row. You are billed 1 credit for each post whose view count or display name was filled. Threads publishes a view count only once it has one, so a post that is minutes old usually comes back without one: that row still gets its pinned flag, and it is free. The join adds 3 to 12 seconds (never more than 12), and a `data.hydration` block reports the rows looked up, filled and served from cache and the credits held and kept; a post the lookup could not read at all is refunded and named by `data._warnings: ["engagement_partial"]`. It is refused beside a `limit` above 20: page with the cursor instead, 20 posts a call. Each response is one result window (typically 15-20 posts); page deeper by sending back pagination.next_cursor as cursor, or set limit (1-100) to have the API walk multiple windows server-side until it has collected at least that many unique posts, billed per window consumed (1 credit each, unused window budget refunded). limit is a collection target rather than a page size, so a response usually carries somewhat more than you asked for; nothing you were billed for is trimmed away. Those windows run sequentially at roughly 3.4 seconds each, so limit buys posts with wall clock as well as credits: measured 07/09/2026 cache-cold, a single window is 3.5s while limit=50 is 10.2s and limit=100 is 19.5s. Set your client timeout above the limit you ask for, or page with the cursor instead. start_date and end_date bound the search to a period; the cursor walk stays inside those bounds. Multi-word queries are handled for you: Threads matches a search against the topic tags it already knows rather than scoring individual terms, so a longer phrase it does not recognise returns nothing at all rather than fewer results. When that happens the query is automatically relaxed into its adjacent word pairs (for example `cari vendor mesin kopi jakarta` becomes `cari vendor`, `vendor mesin`, `mesin kopi` and `kopi jakarta`), those searches run in parallel, and the results come back merged, de-duplicated and ordered by how many of your terms each post contains. You are billed 1 credit for each relaxed search that returned posts and nothing for the ones that did not, so a query that already worked costs exactly what it always did. An expanded response is a single page and carries no pagination cursor, and `data._warnings` names every sub-query that ran. Relaxation respects start_date and end_date: posts outside your window are dropped from every sub-query, and a sub-query left with nothing inside the window is not billed. It also never fires on a request that carried a cursor, so the last hop of a pagination loop is the honest end of the walk rather than a surprise page of loosely related posts. Send expand=false to search the exact phrase only.
Last updated October 2026Maintained by the SocialCrawl team
Returns Threads posts matching a keyword, each with its text, like count, author, creation time, and the topic tag it was filed under at post.ext.topic_tag, plus a cursor for the next window.
Use it to find posts by topic across Threads. Follow pagination.next_cursor to page deeper, or set limit (up to 100) to collect several windows in one call; start_date and end_date bound the period.
Searching 68 platforms in parallel
TikTok·
Instagram·
YouTube·
Facebook·
X·
LinkedIn·
Reddit·Threads·
Pinterest·
Twitch·
Truth Social·
Snapchat·
Kick·
Bluesky·
Kwai·
Rumble·
Spotify·
Apple Music·TikTok Shop·
Amazon Shop·
Google Shopping·
Trustpilot·
TripAdvisor·
Yelp·
Linktree·
Komi·
Pillar·
lnk.bio·Facebook Ads·Google Ads·LinkedIn Ads·Google Search·Google News·
Finance·
Polymarket·
Tavily·
Hacker News·
GitHub·
Perplexity·
Naver·
Utility·
Universal SearchTikTok·Instagram·YouTube·Facebook·X·LinkedIn·Reddit·Threads·Pinterest·Twitch·Truth Social·Snapchat·Kick·Bluesky·Kwai·Rumble·Spotify·Apple Music·TikTok Shop·Amazon Shop·Google Shopping·Trustpilot·TripAdvisor·Yelp·Linktree·Komi·Pillar·lnk.bio·Facebook Ads·Google Ads·LinkedIn Ads·Google Search·Google News·Finance·Polymarket·Tavily·Hacker News·GitHub·Perplexity·Naver·Utility·Universal SearchTikTok·Instagram·YouTube·Facebook·X·LinkedIn·Reddit·Threads·Pinterest·Twitch·Truth Social·Snapchat·Kick·Bluesky·Kwai·Rumble·Spotify·Apple Music·TikTok Shop·Amazon Shop·Google Shopping·Trustpilot·TripAdvisor·Yelp·Linktree·Komi·Pillar·lnk.bio·Facebook Ads·Google Ads·LinkedIn Ads·Google Search·Google News·Finance·Polymarket·Tavily·Hacker News·GitHub·Perplexity·Naver·Utility·Universal SearchTikTok·Instagram·YouTube·Facebook·X·LinkedIn·Reddit·Threads·Pinterest·Twitch·Truth Social·Snapchat·Kick·Bluesky·Kwai·Rumble·Spotify·Apple Music·TikTok Shop·Amazon Shop·Google Shopping·Trustpilot·TripAdvisor·Yelp·Linktree·Komi·Pillar·lnk.bio·Facebook Ads·Google Ads·LinkedIn Ads·Google Search·Google News·Finance·Polymarket·Tavily·Hacker News·GitHub·Perplexity·Naver·Utility·Universal SearchWhat can you do with the Search API?
The Search endpoint gives you structured Threads data with computed fields in a single request. No scraping infrastructure to build or maintain.
Example Request
curl -H "x-api-key: YOUR_API_KEY" \
"https://www.socialcrawl.dev/v1/threads/search?query=artificial+intelligence&label=sponsored&relevance=filter&trim=true"import requests
response = requests.get(
"https://www.socialcrawl.dev/v1/threads/search",
params={
'query': 'artificial intelligence',
'label': 'sponsored',
'relevance': 'filter',
'trim': 'true',
},
headers={"x-api-key": "YOUR_API_KEY"},
)
data = response.json()const response = await fetch(
"https://www.socialcrawl.dev/v1/threads/search?query=artificial+intelligence&label=sponsored&relevance=filter&trim=true",
{
headers: { "x-api-key": "YOUR_API_KEY" },
},
);
const data = await response.json();Parameters worth sending
label=sponsoredMarks each post that is paid or sponsored, at no extra credits; intent and niche are free too.relevance=filterDrops rows that are not about your query, at no extra credits; relevance=score keeps them and adds a score.trim=trueSame price, lighter payload: drops the bulky raw fields.
Parameters
| Parameter | Required | Description |
|---|---|---|
| query | Yes | Search keyword or phrase to find Threads posts |
| start_date | No | Inclusive start of the search period (YYYY-MM-DD). Pagination never walks past it, and a relaxed query drops any post older than it. Threads treats the date pair as a ranking hint rather than a filter, so the window is enforced on our side: a post we cannot date is treated as outside it. |
| end_date | No | Inclusive end of the search period (YYYY-MM-DD). Pagination starts here and walks back in time, and a relaxed query drops any post newer than it. |
| trim | No | Ask the upstream for a stripped record. This is a real shape change, not just less whitespace: a trimmed row carries only the id, text, shortcode, like count, timestamp and author, so media, reply count, share count, view count, topic tag, pinned flag and quoted post all come back null. Same 1 credit either way, so send it only when the text and the like count are all you need. |
| cursor | No | Opaque cursor from a prior response's pagination.next_cursor, passed back verbatim, to fetch the next (older) result window. It carries your date bounds, so paging cannot escape the period you asked for. A request that sends a cursor is never query-relaxed. |
| limit | No | Collect AT LEAST this many unique posts in one call (1-100). This is a collection target, not a page size: the API walks whole result windows server-side until it has collected this many (or the query runs dry), so the response usually carries somewhat more than you asked for and never fewer unless the query ran out. Nothing you paid for is trimmed away. Billed 1 credit per window consumed (about 15-20 posts each), with the unused window budget refunded. Omit for a single window. BUDGET FOR THE WALL CLOCK: the windows run one after another, at roughly 3.4 seconds each, so a high limit is a long request. Measured on production 07/09/2026, cache-cold: no limit 3.5s for 20 posts, limit=30 7.3s for 37, limit=50 10.2s for 55, limit=100 19.5s for 111. If your HTTP client defaults to a 10-second timeout, limit=50 and above will not fit inside it. Either raise the client timeout, or ask for a smaller limit and page with pagination.next_cursor, which costs the same credits for the same posts. |
| expand | No | Set to false to search the exact phrase only. Defaults to true, which relaxes a query Threads does not recognise into its adjacent word pairs and merges the results, billing 1 credit per relaxed search that returned posts inside your date window. Ignored on a request that carries a cursor. |
| include | No | Send `engagement` to fill `engagement.views` and `post.flags.pinned` on the first 20 posts by looking each one up on `/v1/threads/post` in the same call. 1 credit per post whose view count or display name was filled from a fresh lookup (20 at most); posts served from that lookup's cache (10 minutes) are free, and so is a post Threads has published no view count for yet, which still gets its pinned flag. Adds 3 to 12 seconds, never more than 12. One token only: `engagement`. Not accepted with a `limit` above 20; page with the cursor for more. (engagement) |
| relevance | No | Optional. Without this param every row already carries computed.relevance against your query, free ({ p, sense, depth, spam }: is this row about what your query means, or a different thing that shares its words?), and nothing is dropped or reordered. score asks for it explicitly and waits for every row; filter also drops the rows that are not about your query, and lists their ids in data.relevance.dropped_ids. Your query is the topic; nothing to configure. A row that could not be judged is never dropped and carries relevance: null. Pagination is unchanged, so a filtered page can hold fewer rows. Free with your query as the topic; with relevant_to it adds 1 credit per started 25 newly judged rows (rows already judged for the same topic are free, and so is a cached page). (score | filter) |
| relevance_threshold | No | Optional, only with relevance. The probability (0 to 1) a row must reach to be kept by relevance=filter. Default 0.5. Lower keeps more rows, higher keeps fewer. |
| relevant_to | No | Optional, only with relevance. Up to 200 characters describing what you mean, used as the topic instead of the query. Use it when the query is ambiguous, for example query=cleopatra with relevant_to=Cleopatra, the IGT slot game. |
| judgments | No | Optional, on (the default) or off. By default every row gains free SocialCrawl judgments (computed.labels, and computed.relevance on search endpoints), reported in data.labels (mode default) and data.relevance (origin default), each with a status (complete, partial or skipped) and pending: the rows still being judged when the page was sent, which carry null now and are filled on your next call or cached read. Default judgments never add credits, never change an existing field, and never drop or reorder a row. off returns the page exactly as before, with none of those keys. label=none does the same. (on | off) |
| dry_run | No | Optional. When 1, return a cost preview for this labelled or relevance-filtered request without fetching the page or judging any row. data.estimate reports rows_expected, rows_cached, label_credits_min, label_credits_max and base_credits. 0 credits charged. (1) |
| fit | No | Optional. When goal, keep the rows and fields needed for the goal you pass in goal= (plus any that are uncertain, and the first and last), and replace the rest with a stub. data.held_back lists the held ids and a recall id that re-reads the full page from cache at no extra charge. Without this param the page is unchanged. (goal) |
| goal | No | Required by fit=goal. What you are trying to do, in your own words, up to 300 characters. |
| fit_tokens | No | Optional, only with fit=goal. Soft cap on how much of the page to keep, in tokens. Uncertain blocks and the first and last block are kept even if they exceed it. |
| label | No | Optional CSV of SocialCrawl labels to add to every post. Without this param every page already carries sponsored, intent and niche, free; label= adds the labels you name to them (the defaults keep running). sponsored, intent and niche are free when asked for too; mention, quality, intent with offer=, and injection add 1 credit per started 25 newly judged posts. judgments=off (or label=none) turns the default labels off. sponsored: is the post a paid or gifted promotion (p, 0 to 1), did it carry a disclosure marker such as #ad or 광고 (disclosed), is it likely paid with no marker (undisclosed), and which of the accounts it mentions does it promote (brand, or null). These are signals to review, never a finding. mention (needs brand=): is the post about that brand rather than something that shares its name (about_brand, 0 to 1), how it feels about the brand on five levels (sentiment_level 0 to 4 and sentiment_score 0 to 1, null when the post is not about the brand), is it sarcastic, which aspect it talks about (taste_or_quality, price_or_value, availability_or_delivery, health_or_safety, advertising_or_campaign, customer_service, none), and did the author buy or use it (first_hand). intent: what the author is mainly doing (label: asking_for_recommendation, comparing_options, switching_away, complaining, promoting, news_or_discussion, other, or null when unsure, with confidence), whether they read as a potential buyer rather than a seller (buyer, seller), how pressing the need is (urgency, 0 to 3), and, when you pass offer=, whether your offer would plausibly help them (fits_offer). niche: which of the 33 niches of the published taxonomy sc-niche-v1 the caption belongs to, or personal_no_niche, or other (label, confidence, taxonomy), with label null when the caption is too thin to tell or the pick is unsure. It reads the caption only, not the video. quality: how much checkable detail the caption carries (fact_density 0 to 3), whether it mainly asks for likes, replies, shares, follows or tags (engagement_bait, 0 to 1), whether it is written to provoke anger as a way to get engagement (rage_bait, 0 to 1; about the writing, never the side taken), whether it only repeats someone else's news or view (secondhand, 0 to 1), and what the post is mainly doing (post_aim: inform, opinion, sell, entertain, provoke, other). exclude=engagement_bait drops posts whose engagement_bait is 0.8 or higher. injection flags text that addresses an AI system and tries to direct it (flagged, p); it never drops or rewrites a row. A post that could not be judged carries labels: null. Posts already labelled for anyone are free, and so is a cached page. data.labels reports what was judged and billed. |
| exclude | No | Optional CSV (engagement_bait), only with label=quality. Drops posts whose engagement_bait probability is 0.8 or higher and lists their ids in data.labels.dropped_ids. A post that could not be judged is never dropped. |
| brand | No | Required by label=mention, ignored otherwise. The brand or product the posts are judged against, up to 300 characters, for example brand=Buldak. Without it label=mention is skipped with the warning label_mention_needs_brand and is not billed. |
| brand_description | No | Optional, with label=mention. One plain sentence saying what the brand is, for example brand_description=Samyang's spicy instant noodle brand. Use it when the name is also an ordinary word or another company's name. |
| offer | No | Optional, with label=intent. One or two plain sentences saying what you sell, up to 300 characters, for example offer=A web design agency that builds websites for small businesses. Adds fits_offer to every post; without it fits_offer is null. |
| label_evidence | No | Optional, only with label=. When 1, every labelled row also carries computed.labels_evidence.<preset> = { quote, sentence_index }: the sentence in the row that most clearly shows the label, copied verbatim. Absent or null when no single sentence shows it. (1) |
| since | No | Only rows published on or after this date: YYYY-MM-DD (midnight UTC) or an ISO 8601 timestamp. Rows older than it are left off each page. This list is not in date order, so the walk does not stop at the date: keep following `next_cursor`, and each page costs what a page costs even when every row on it is filtered out. A row with no date is kept. `published_after`, `start_date`, `from_date`, `publish_time` (`yesterday`, `this-week`, `this-month`, `last-3-months`, `last-6-months`) and `max_age_days` are accepted and applied as `since`. |
| until | No | Only rows published on or before this date: YYYY-MM-DD (that whole UTC day is included) or an ISO 8601 timestamp. Newer rows are left off each page and the walk does not stop, so older pages follow. A row with no date is kept. `published_before`, `end_date` and `to_date` are accepted and applied as `until`. |
| max_pages | No | 1 to 5 (default 1). Walk up to this many pages in one call and return the rows from all of them (after any filter). Each page walked is billed exactly as one call to this endpoint (a cached page is free) and counts against your rate limit. The walk stops early at the last page, or when the request's time budget runs low; `data.walk.stopped` says why (`end`, `max_pages`, `time_budget`, `page_error`) and `data.next_cursor` continues from where it stopped. |
| seen | No | An id you choose (1 to 64 letters, digits, `.`, `_` or `-`). Rows your account already received under the same `seen` id are removed from the page, and the page price falls with the share of repeats: page credits x new rows / rows on the page, rounded up, so a page of nothing but repeats is free. Only the page's own price is discounted: credits for joined data (`include=`) are charged only for rows you have not received, and are never discounted. The memory lasts 24 hours from the last call that used the id, holds row ids only, and is private to your account. Use one id across a set of related searches; `data.walk.repeats` counts what was removed. |
What does the Threads Search API return?
Every response follows one unified schema. Here is a real, unmodified response body, so you can see the exact fields you get back before spending a credit.
Example response
{
"success": true,
"platform": "threads",
"endpoint": "/v1/threads/search",
"data": {
"items": [
{
"post": {
"id": "3998890680578542448",
"url": "https://www.threads.com/@user_4317b4/post/Dd-6eMPgQtw",
"content": {
"text": "Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted).",
"media_urls": null,
"thumbnail_url": null,
"duration_seconds": null
},
"author": {
"username": "user_4317b4",
"display_name": "user_74c21a",
"avatar_url": "https://example.com/avatars/user_bab3c1.png",
"verified": false
},
"engagement": {
"views": null,
"likes": 5,
"comments": 1,
"shares": 0,
"saves": null
},
"flags": {
"nsfw": null,
"spoiler": null,
"pinned": null,
"deleted": false
},
"published_at": "2026-10-02T07:08:58.000Z",
"ext": {
"published_at_epoch": 1790924938,
"quote_count": 0,
"topic_tag": null,
"reshare_count": null,
"topic_tag_id": null
}
},
"computed": {
"engagement_rate": null,
"language": "en",
"content_category": "other",
"estimated_reach": null,
"relevance": {
"p": 0.46,
"sense": "target",
"depth": 1.03,
"spam": 0.05
},
"labels": null
}
},
{
"post": {
"id": "3998600807021823393",
"url": "https://www.threads.com/@user_5cca78/post/Dd94j-dIEWh",
"content": {
"text": "Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted).",
"media_urls": null,
"thumbnail_url": null,
"duration_seconds": null
},
"author": {
"username": "user_5cca78",
"display_name": "user_c565e9",
"avatar_url": "https://example.com/avatars/user_de4ca5.png",
"verified": false
},
"engagement": {
"views": null,
"likes": 1,
"comments": 1,
"shares": 1,
"saves": null
},
"flags": {
"nsfw": null,
"spoiler": null,
"pinned": null,
"deleted": false
},
"published_at": "2026-10-01T21:33:03.000Z",
"ext": {
"published_at_epoch": 1790890383,
"quote_count": 0,
"topic_tag": "tinfoilhat",
"reshare_count": null,
"topic_tag_id": "18415724197038380"
}
},
"computed": {
"engagement_rate": null,
"language": "en",
"content_category": "other",
"estimated_reach": null,
"relevance": {
"p": 0.83,
"sense": "target",
"depth": 1.48,
"spam": 0.18
},
"labels": null
}
}
],
"next_cursor": "dw1.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",
"total": null,
"relevance": {
"mode": "score",
"topic_source": "query",
"rows": 20,
"scored": 19,
"cached": 1,
"kept": 20,
"dropped": 0,
"dropped_ids": [],
"unjudged": 0,
"too_short": 1,
"threshold": 0.5,
"extra_credits": 0,
"methodology_version": "relevance/2",
"origin": "default",
"pending": 0,
"pending_ids": [],
"status": "complete"
},
"labels": {
"presets": [
"sponsored",
"intent"
],
"rows": 20,
"labelled": 7,
"cached": 0,
"skipped": 1,
"unjudged": 0,
"dropped": 0,
"dropped_ids": [],
"extra_credits": 0,
"methodology_version": "labels/1",
"mode": "default",
"status": "partial",
"pending": 12,
"pending_ids": [
"3998890680578542448",
"3998600807021823393"
]
},
"dropped": 0
},
"credits_used": 1,
"request_id": "req_example000000",
"cached": false,
"pagination": {
"next_cursor": "sc.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",
"has_more": true,
"page_size": 20
},
"credits_remaining": 9999,
"source": "captured",
"captured_at": "2026-10-02T07:26:34.862Z",
"redacted": true
}Live sample illustrating the unified response shape. Field values reflect the record you query.
How does the Threads Search API work?
Send a GET request with your API key and get back clean, structured JSON in our unified schema. Supported computed fields are populated when the source provides the required inputs.
Method
GET
Response
JSON
How do you scrape social media data in seconds?
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Computed fields, not just scraped
When an endpoint supports these metrics and the source provides the required inputs, the normalized record includes engagement_rate, estimated_reach, content_category, and language. Ready to use.
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import requests
response = requests.get(
'https://www.socialcrawl.dev/v1/tiktok/profile',
params={'handle': 'charlidamelio'},
headers={'x-api-key': 'sc_YOUR_API_KEY'}
)
data = response.json(){
"success": true,
"platform": "tiktok",
"data": {
"author": {
"username": "charlidamelio",
"followers": 152400000
},
"engagement": {
"likes": 12400000000,
"engagement_rate": 0.087
},
"metadata": {
"language": "en",
"content_category": "lifestyle"
}
}
}Have a question? We got answers
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