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Reddit Search API
Returns posts matching a keyword from across Reddit, each with title, score, comment count, subreddit, permalink, and the body at ext.selftext. A page holds up to 25 posts and varies.
GET /v1/reddit/searchLast updated November 2026Maintained by the SocialCrawl team
When to use the Reddit Search API
Use it to search all of Reddit at once. Bodies arrive free here, so include_body=true is rarely needed and refunds what it does not spend. subreddit/search searches inside one community.
From the API reference
Searches Reddit for posts matching a keyword query. Returns a list of matching posts with titles, scores, comment counts, subreddit names, and permalinks. One result page is assembled from more than one index, so a few leaves are reported for only part of a page and are null on the rest: post.flags.spoiler, post.engagement.shares and post.engagement.saves. A null there means the index that returned that row does not report the field, never that the value is false or zero — treat those three as opportunistic and do not aggregate over them. The post body is at ext.selftext (content.text is the title and body joined, matching /v1/reddit/post); this surface sends it on self-posts without any extra flag. A page holds up to 25 posts and the exact count varies between calls, so do not assume a fixed page size: pages of about 7 are common and a sparse query can return fewer. Rows beyond the first few, and the newest rows on a sort=new page, may carry fewer fields than the rest: flags.spoiler in particular is present on some rows and null on others within one response. Where a row carries them you also get the author's avatar at author.avatar_url, images or video at content.media_urls, and the upvote ratio, post flair and Reddit's own content language at ext.upvote_ratio, ext.flair and ext.content_language. include_body=true is still accepted and rarely needed now: bodies arrive on the rows themselves, so on most pages the flag finds nothing to fetch and its extra credits are refunded in full. It still hydrates a row that does arrive without a body, at 1 extra credit per row hydrated, up to 25 per page. Link posts have no body, so ext.selftext is null. Ranking is a voice-of-customer sweep rather than precision retrieval: expect some off-topic matches on short or ambiguous queries, and use quoted phrases to tighten them. To get more than one page in a single call, set limit (26 to 1,000): the call then reads Reddit's own search index once and returns up to that many posts for the query, sort and timeframe, newest first with sort=new, at 1 credit per 25 posts returned. Reddit stops one query at about 1,000 posts, so that answer has no next page; to collect more than that on a busy keyword, repeat the call through the day with sort=new and since set to your last run (or seen), and you pay only for the new posts. Those rows carry the same fields as the rest of the page, with post.flags.spoiler, post.engagement.shares and post.engagement.saves null, and the default relevance score and labels cover the first 100 of them.
Searching 69 platforms in parallel
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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 Search
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 Search·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 Search
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 Search·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 Search
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 Search·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 Search
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 SearchReddit API
What can you do with the Search API?
The Search endpoint gives you structured Reddit data with computed fields in a single request. No scraping infrastructure to build or maintain.
Example Request
# GET /v1/reddit/search: Metered: holds 1 credit per page up front and refunds what the call does not use. Cache hits are free and failed calls are refunded.
# Check the price first for 0 credits: add dry_run=1 to the query. Nothing is fetched or charged.
# --max-time 22: this endpoint's measured p99 latency x 1.5.
# --retry 3: retries timeouts, 429 and 5xx, honoring Retry-After.
# -o response.json keeps only the final attempt's body.
# One Idempotency-Key per request, reused on every retry, so a retried call is never charged twice.
# Next page: send pagination.next_cursor back as cursor until pagination.has_more is false.
IDEMPOTENCY_KEY=$(od -An -N16 -tx1 /dev/urandom | tr -d ' \n')
curl -sS --max-time 22 --retry 3 -o response.json \
-H "x-api-key: YOUR_API_KEY" \
-H "Idempotency-Key: $IDEMPOTENCY_KEY" \
"https://www.socialcrawl.dev/v1/reddit/search?query=%22claude+code%22&label=sponsored&relevance=filter&trim=true" && cat response.json# GET /v1/reddit/search: Metered: holds 1 credit per page up front and refunds what the call does not use. Cache hits are free and failed calls are refunded.
# Check the price first for 0 credits: add dry_run=1 to the query. Nothing is fetched or charged.
import os
import random
import time
import uuid
import requests
API_KEY = os.environ.get("SOCIALCRAWL_API_KEY", "YOUR_API_KEY")
TIMEOUT_S = 22 # this endpoint's measured p99 latency x 1.5.
MAX_RETRIES = 3
URL = "https://www.socialcrawl.dev/v1/reddit/search"
def backoff(attempt):
# Exponential backoff with jitter: about 1 s, 2 s, then 4 s.
return 2 ** attempt * (0.5 + random.random() / 2)
def socialcrawl(params):
# One Idempotency-Key per request, reused on every retry, so a retried call is never charged twice.
idempotency_key = str(uuid.uuid4())
for attempt in range(MAX_RETRIES + 1):
try:
res = requests.get(
URL,
params=params,
headers={"x-api-key": API_KEY, "Idempotency-Key": idempotency_key},
timeout=TIMEOUT_S,
)
body = res.json()
except (requests.RequestException, ValueError):
# A timeout, a dropped connection or a non-JSON gateway page: retry with the same key.
if attempt == MAX_RETRIES:
raise
time.sleep(backoff(attempt))
continue
if body["success"]:
return body
error = body["error"]
# Branch on error["type"], never on the message text.
if error["type"] == "RESOURCE_NOT_FOUND":
return None # refunded: nothing to read
retry_after = res.headers.get("Retry-After")
# SERVICE_UNAVAILABLE without Retry-After is a withdrawn endpoint: permanent.
permanent = error["type"] == "SERVICE_UNAVAILABLE" and retry_after is None
if not error.get("retryable") or permanent or attempt == MAX_RETRIES:
raise RuntimeError(f"{error['type']}: {error['message']} (request_id {body['request_id']})")
# Retry-After (seconds) wins; otherwise back off.
time.sleep(float(retry_after) if retry_after else backoff(attempt))
params = {
"query": "\"claude code\"",
"label": "sponsored",
"relevance": "filter",
"trim": "true",
}
# Walk the list: send pagination.next_cursor back as cursor until has_more is false.
MAX_PAGES = 10 # each page is one call
items = []
for _ in range(MAX_PAGES):
body = socialcrawl(params)
if body is None:
break
items.extend(body["data"]["items"])
page = body.get("pagination") or {}
if not page.get("has_more") or not page.get("next_cursor"):
break
params["cursor"] = page["next_cursor"]
print(f"{len(items)} items")// GET /v1/reddit/search: Metered: holds 1 credit per page up front and refunds what the call does not use. Cache hits are free and failed calls are refunded.
// Check the price first for 0 credits: add dry_run=1 to the query. Nothing is fetched or charged.
const API_KEY = process.env.SOCIALCRAWL_API_KEY ?? "YOUR_API_KEY";
const TIMEOUT_MS = 22_000; // this endpoint's measured p99 latency x 1.5.
const MAX_RETRIES = 3;
type Page = { next_cursor: string | null; has_more: boolean };
type SocialCrawlResponse =
| { success: true; data: any; pagination?: Page; credits_used: number; request_id: string }
| { success: false; error: { type: string; message: string; retryable: boolean }; request_id: string };
const sleep = (ms: number) => new Promise((resolve) => setTimeout(resolve, ms));
// Exponential backoff with jitter: about 1 s, 2 s, then 4 s.
const backoffMs = (attempt: number) => 2 ** attempt * 1000 * (0.5 + Math.random() / 2);
async function socialcrawl(url: URL) {
// One Idempotency-Key per request, reused on every retry, so a retried call is never charged twice.
const idempotencyKey = crypto.randomUUID();
for (let attempt = 0; ; attempt++) {
let res: Response;
let body: SocialCrawlResponse;
try {
res = await fetch(url, {
headers: {
"x-api-key": API_KEY,
"Idempotency-Key": idempotencyKey,
},
signal: AbortSignal.timeout(TIMEOUT_MS),
});
body = (await res.json()) as SocialCrawlResponse;
} catch (error) {
// A timeout, a dropped connection or a non-JSON gateway page: retry with the same key.
if (attempt >= MAX_RETRIES) throw error;
await sleep(backoffMs(attempt));
continue;
}
if (body.success) return body;
// Branch on error.type, never on the message text.
if (body.error.type === "RESOURCE_NOT_FOUND") return null; // refunded: nothing to read
const retryAfter = res.headers.get("Retry-After");
// SERVICE_UNAVAILABLE without Retry-After is a withdrawn endpoint: permanent.
const permanent = body.error.type === "SERVICE_UNAVAILABLE" && retryAfter === null;
if (!body.error.retryable || permanent || attempt >= MAX_RETRIES) {
throw new Error(`${body.error.type}: ${body.error.message} (request_id ${body.request_id})`);
}
// Retry-After (seconds) wins; otherwise back off.
await sleep(retryAfter ? Number(retryAfter) * 1000 : backoffMs(attempt));
}
}
const url = new URL("https://www.socialcrawl.dev/v1/reddit/search");
url.searchParams.set("query", "\"claude code\"");
url.searchParams.set("label", "sponsored");
url.searchParams.set("relevance", "filter");
url.searchParams.set("trim", "true");
// Walk the list: send pagination.next_cursor back as cursor until has_more is false.
const MAX_PAGES = 10; // each page is one call
const items: unknown[] = [];
for (let page = 0; page < MAX_PAGES; page++) {
const body = await socialcrawl(url);
if (!body) break;
items.push(...body.data.items);
const next = body.pagination?.next_cursor;
if (!body.pagination?.has_more || !next) break;
url.searchParams.set("cursor", next);
}
console.log(`${items.length} items`);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 words or a phrase. Words match any, not all: vision pro also returns posts that mention only one of them. Wrap a phrase in double quotes to match it exactly (query="vision pro"). Reddit operators such as subreddit:name work too. When fewer than half the rows contain every word of an unquoted query, the response says so in _warnings. |
| sort | No | Sort by (relevance | new | top | comment_count) |
| timeframe | No | Only return posts from this window. Applied on sort=relevance, sort=top and sort=comment_count. It has no effect with sort=new, which is already ordered newest-first and returns recent posts regardless. (all | day | week | month | year) |
| after | No | Used to paginate to next page |
| trim | No | Set to true for a trimmed down version of the response. On this endpoint it also skips the second source that widens the page, so a trimmed page is both thinner and usually shorter. Measured 09/09/2026: default 29 rows, `trim=true` 25 rows. It does not drop `author.avatar_url` or `ext.*` — those leaves stay when the first source already carried them. Use it to skip the widening pass, not to strip fields. |
| include_body | No | Set to true to include each post's body (selftext) on the search page. Rarely needed now: bodies arrive on the rows themselves. 1 extra credit per row that actually comes back with a body, unused credits refunded. Link posts have no body, so they are looked up and not charged for. |
| limit | No | How many posts to return in one call, 26 to 1,000. Above 25 the call reads Reddit's own search index once instead of returning one page: up to this many posts for the query, sort and timeframe, newest first with sort=new, at 1 credit per 25 posts returned (limit / 25 is held up front and the rest refunded). Reddit stops one query at about 1,000 posts, so this answer has no next page. At 25 or below the ordinary page is returned exactly as without it, and a request that carries after is a next page, so limit does not apply to it. |
| 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, ai_style, 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. ai_style: writing patterns common in AI-generated text, judged on the text alone. It does not say who wrote the post, and a person who writes in this style is flagged too. Six patterns are judged, each a probability (0 to 1): binary_contrast ("This is not X. It's Y."), faux_insight ("Here's what nobody tells you" and throat-clearing openers), colon_reveal ("The best part: it learns."), profound_kicker (ends on an aphorism or mic-drop line), puffery ("marks a pivotal moment", "highlighting the importance of") and rhetorical_setup ("What if I told you", a question the post answers itself, "Not a X. Not a Y. A Z."). Four are counted in the text: slop_words (words and phrases such as delve, leverage, robust, game changer, at the end of the day), em_dashes, emoji_bullets (lines that start with an emoji or a symbol bullet) and one_line_paragraphs (paragraphs that are one short line). pattern_count is how many patterns are present (a judged pattern at 0.8 or higher, slop_words 1 or more, em_dashes 2 or more, emoji_bullets 2 or more, one_line_paragraphs 5 or more) and markers lists their names, comma-separated. A post with less than about eight words of text is only counted, with every judged pattern 0. The judged patterns read the first 400 and the last 150 characters of a long post, and the counts read the whole post. exclude=ai_style drops posts with 2 or more patterns. ai_written: how likely the post was written by an AI model, from SocialCrawl's own text classifier, reading the opening of the post (about 1,000 characters): p (0 to 1, calibrated), level (likely (p 0.95 or higher), possible (p 0.71 or higher) or unlikely) and model (the model name; a new name means a new scale). A post under 8 words is too short to read: p null, level too_short. It is a probability, not proof: a person can be flagged and an AI-written post can pass, and the shorter the post the less certain it is. exclude=ai_written drops likely posts. 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, ai_style, ai_written). engagement_bait, only with label=quality, drops posts whose engagement_bait probability is 0.8 or higher. ai_style, only with label=ai_style, drops posts that show 2 or more of its writing patterns (pattern_count 2 or higher). ai_written, only with label=ai_written, drops posts whose level is likely (p 0.95 or higher), or whose p reaches your ai_written_threshold; a post too short to read is never dropped. Dropped posts are listed in data.labels.dropped_ids. A post that could not be judged is never dropped. |
| ai_written_threshold | No | Optional, only with label=ai_written and exclude=ai_written. The p (0 to 1) at which exclude=ai_written drops a post. Default 0.95 (level likely). 0.71 also drops possible posts: more AI posts go, and more posts by people with them. |
| 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 the page, and the page that reaches one ends the walk: `next_cursor` is not returned and `pagination.stopped_at` is `since`. Sending it sets the newest-first sort shown in this endpoint's sort parameter (any other sort value is a free 400). The page still costs what a page costs, so you pay for the pages you walk and no more. 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_age_days | No | Keep only rows published within this many days (`post.published_at`), 1 to 3650. A row with no date is discarded. Filtering runs on our side after each page is fetched, so every page walked is billed as usual; `data.walk.discarded` counts what was removed and why. Each page is its own entry in `GET /v1/credits/transactions`, under the page's request id listed in `data.walk.request_ids`. |
| max_pages | No | 1 to 50 (default 1, or 50 when `max_items` or `max_credits` is sent). 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; its charge and any refund are recorded under the page's own request id, listed in `data.walk.request_ids`. 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`, `max_items`, `max_credits`, `time_budget`, `page_error`) and `pagination.next_cursor` continues from where it stopped. |
| max_items | No | 1 to 5000. Get more in one call: keep walking pages until the response holds at least this many rows (after any filter), then stop with `data.walk.stopped: "max_items"`. The last page is returned whole (it was billed), so `data.items` can hold up to one page more than this, and `pagination.next_cursor` resumes right after it without skipping a row. Walks up to 50 pages unless `max_pages` says fewer; each page is billed as one call (a cached page is free). Add `max_credits` to cap the spend. A long walk can stop on the time budget first (`"time_budget"`): send the returned cursor with the same params to continue. |
| max_credits | No | 1 to 100000. The most this call may spend, across every page it walks. A page starts only while the credits already spent plus that page's price (or, when higher, the most any page of this walk has cost) still fit, so the call never goes past it; the walk then stops with `data.walk.stopped: "max_credits"` and the cursor to resume. Sent alone, it walks as far as the budget goes (up to 50 pages). A value below the price of one page is a free 400 whose `error.details.page_credits` names that price. Credits a row join (`include=`) adds are known only once a page has run, so page 1 is checked against its own price. |
| 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. |
Example Response
What does the Reddit 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": "reddit",
"endpoint": "/v1/reddit/search",
"data": {
"items": [
{
"post": {
"id": "1wrckhp",
"url": "https://www.reddit.com/r/ClaudeAI/comments/1wrckhp/what_tool_have_you_built_for_yourself_with_claude/",
"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_1c226d",
"display_name": "user_37da46",
"avatar_url": "https://example.com/avatars/user_246eb3.png",
"verified": null
},
"engagement": {
"views": null,
"likes": 1183,
"comments": 581,
"shares": null,
"saves": null
},
"flags": {
"nsfw": false,
"spoiler": false,
"pinned": null,
"deleted": false
},
"published_at": "2026-09-27T06:12:55.000Z",
"ext": {
"subreddit": "ClaudeAI",
"title": "Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted).",
"selftext": "I built a tool that reads emails from my kid’s school and other activities (swimming, music classes, scouts) etc and then: - Adds them to our shared calendar- Sends us a WhatsApp message to remind us the day before of what to pack in his school bag- Tells us what is on his lunch menu (helps us to avoid making the same dinner for him as he would have had for lunch) This all saves so much headache and head space in our daily routine. No more flapping around in the morning!!! I’ve also build tools that help with invoicing and proposals for example. Those have single-handedly removed a lot of daily frustration and friction. For example sometimes I wouldn’t bid on a job because I knew it would take a few hours of my day to write the proposal. And that would leave money on the table. Not it takes 5 mins and more work is coming in as a result simply because more proposals are going through the door. I’d I love to hear what you guys are making and things that really help you out. My main aim is to get my evenings and weekends back and be able to spend more time with my family whilst still scaling my business. Maybe they are lofty goals!!",
"upvote_ratio": 0.9750402576489532,
"flair": "Claude Code Workflow",
"content_language": "en",
"published_at_epoch": 1790489575
}
},
"computed": {
"engagement_rate": null,
"language": "en",
"content_category": "food",
"estimated_reach": null,
"relevance": {
"p": 0.95,
"sense": "target",
"depth": 1.52,
"spam": 0.18
},
"labels": {
"sponsored": {
"p": 0.04,
"disclosed": false,
"undisclosed": false,
"brand": null
},
"intent": {
"label": "other",
"confidence": 0.55,
"buyer": false,
"seller": 0.06,
"fits_offer": null,
"urgency": 0.4
},
"niche": {
"label": "technology",
"confidence": 0.89,
"taxonomy": "sc-niche-v1"
}
}
}
},
{
"post": {
"id": "1wqnn5x",
"url": "https://www.reddit.com/r/ClaudeAI/comments/1wqnn5x/claude_code_users_are_getting_up_to_250_in_free/",
"content": {
"text": "Sample comment text (redacted).",
"media_urls": "https://madrobot.blog/2026/09/24/claude-code-cloud-sessions-free-credit-how-to-claim/",
"thumbnail_url": "https://external-preview.redd.it/a5YzxKLxe6DjLWqf21T52VT5R2_j8clQxEGkWpNkADY.jpeg?auto=webp&s=c739062d30747aaa35f78bfb4348eff896509a17",
"duration_seconds": null
},
"author": {
"username": "user_15284e",
"display_name": "user_72b766",
"avatar_url": "https://example.com/avatars/user_d9b374.png",
"verified": null
},
"engagement": {
"views": null,
"likes": 110,
"comments": 53,
"shares": null,
"saves": null
},
"flags": {
"nsfw": false,
"spoiler": false,
"pinned": null,
"deleted": false
},
"published_at": "2026-09-26T10:58:20.000Z",
"ext": {
"subreddit": "ClaudeAI",
"title": "Sample comment text (redacted).",
"selftext": "Don't forget to claim it guys!",
"upvote_ratio": 0.8089887640449438,
"flair": "Promotion",
"content_language": "en",
"published_at_epoch": 1790420300
}
},
"computed": {
"engagement_rate": null,
"language": "en",
"content_category": "other",
"estimated_reach": null,
"relevance": {
"p": 0.89,
"sense": "target",
"depth": 0.96,
"spam": 0.85
},
"labels": null
}
}
],
"next_cursor": "sc2.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",
"total": null,
"relevance": {
"mode": "score",
"topic_source": "query",
"rows": 25,
"scored": 25,
"cached": 0,
"kept": 25,
"dropped": 0,
"dropped_ids": [],
"unjudged": 0,
"too_short": 0,
"threshold": 0.5,
"extra_credits": 0,
"methodology_version": "relevance/2",
"origin": "default",
"pending": 0,
"pending_ids": [],
"status": "complete"
},
"labels": {
"presets": [
"sponsored",
"intent"
],
"rows": 25,
"labelled": 3,
"cached": 3,
"skipped": 0,
"unjudged": 0,
"dropped": 0,
"dropped_ids": [],
"extra_credits": 0,
"methodology_version": "labels/1",
"mode": "default",
"status": "partial",
"pending": 22,
"pending_ids": [
"1wqnn5x",
"1wrcmjn"
]
},
"dropped": 0
},
"credits_used": 1,
"request_id": "req_example000000",
"cached": false,
"pagination": {
"next_cursor": "sc.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",
"has_more": true,
"page_size": 25
},
"credits_remaining": 9999,
"source": "captured",
"captured_at": "2026-10-02T07:26:20.953Z",
"redacted": true
}Live sample illustrating the unified response shape. Field values reflect the record you query.
API Details
How does the Reddit 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
Developer First
How do you scrape social media data in seconds?
The fastest social media scraping API for developers. Scrape profiles, posts, comments, and analytics from 69 platforms covering 10B+ monthly active users.
One schema, every platform
Query 69 platforms with identical response structures. Write your integration once.
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.
See your data before you code
Visual Data Explorer. Paste any URL, get rich result cards, sortable tables, CSV export.
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()[ .JSON ]
{
"success": true,
"platform": "tiktok",
"data": {
"author": {
"username": "charlidamelio",
"followers": 152400000
},
"engagement": {
"likes": 12400000000,
"engagement_rate": 0.087
},
"metadata": {
"language": "en",
"content_category": "lifestyle"
}
}
}FAQ
Have a question? We got answers
Find answers to frequently asked questions about SocialCrawl's API, pricing, and capabilities.
Contact usHow do I search Reddit posts with an API?
Send a GET request to /v1/reddit/search with your query in the query parameter. SocialCrawl searches across all of Reddit and returns matching posts with title, score, comment count, subreddit, author, permalink, and timestamp.
What sort options does Reddit search support?
Four sort modes: relevance (default), new, top, and comment_count. Pair sort=top with a timeframe (day, week, month, year, all) to pull the highest-scoring posts from a specific period. Useful for trend analysis and brand tracking.
Can I monitor brand mentions across Reddit?
Yes. Run the search endpoint on a cron with your brand name or product keywords as the query, sort by new, and ingest the result into your monitoring pipeline. No Pushshift downtime and no Reddit app registration required.
How do I paginate through search results?
The response includes an after token. Pass that value as the after parameter on the next request to fetch the next page. Repeat until after is empty to walk through the full result set beyond the default page size.
How much does the Reddit Search API cost?
Each search request costs 1 credit on the standard tier, regardless of how many results come back. New accounts get 100 free credits with no credit card required. Pass trim=true to receive a slimmer response when you only need core fields.
Ask AI about SocialCrawl
Guides that use this endpoint
Each guide walks through one job from start to finish, with the calls in order and what one run costs.
Ready to scrape Reddit Search data?
Get your API key and start pulling Reddit data in under 60 seconds.