100 free credits. No credit card required.Start building
Logo
Reddit logo
100 free credits. No credit card required

Reddit Search API

Scrape Reddit Search data with one API call. 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.

Last updated October 2026Maintained by the SocialCrawl team

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.

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.

Searching 68 platforms in parallel

·TikTok logoTikTok·Instagram logoInstagram·YouTube logoYouTube·Facebook logoFacebook·X logoX·LinkedIn logoLinkedIn·Reddit logoReddit·Threads logoThreads·Pinterest logoPinterest·Twitch logoTwitch·Truth Social logoTruth Social·Snapchat logoSnapchat·Kick logoKick·Bluesky logoBluesky·Kwai logoKwai·Rumble logoRumble·Spotify logoSpotify·Apple Music logoApple Music·TikTok Shop logoTikTok Shop·Amazon Shop logoAmazon Shop·Google Shopping logoGoogle Shopping·Trustpilot logoTrustpilot·TripAdvisor logoTripAdvisor·Yelp logoYelp·Linktree logoLinktree·Komi logoKomi·Pillar logoPillar·lnk.bio logolnk.bio·Facebook Ads logoFacebook Ads·Google Ads logoGoogle Ads·LinkedIn Ads logoLinkedIn Ads·Google Search logoGoogle Search·Google News logoGoogle News·Finance logoFinance·Polymarket logoPolymarket·Tavily logoTavily·Hacker News logoHacker News·GitHub logoGitHub·Perplexity logoPerplexity·Naver logoNaver·Utility logoUtility·Universal Search logoUniversal Search
·TikTok logoTikTok·Instagram logoInstagram·YouTube logoYouTube·Facebook logoFacebook·X logoX·LinkedIn logoLinkedIn·Reddit logoReddit·Threads logoThreads·Pinterest logoPinterest·Twitch logoTwitch·Truth Social logoTruth Social·Snapchat logoSnapchat·Kick logoKick·Bluesky logoBluesky·Kwai logoKwai·Rumble logoRumble·Spotify logoSpotify·Apple Music logoApple Music·TikTok Shop logoTikTok Shop·Amazon Shop logoAmazon Shop·Google Shopping logoGoogle Shopping·Trustpilot logoTrustpilot·TripAdvisor logoTripAdvisor·Yelp logoYelp·Linktree logoLinktree·Komi logoKomi·Pillar logoPillar·lnk.bio logolnk.bio·Facebook Ads logoFacebook Ads·Google Ads logoGoogle Ads·LinkedIn Ads logoLinkedIn Ads·Google Search logoGoogle Search·Google News logoGoogle News·Finance logoFinance·Polymarket logoPolymarket·Tavily logoTavily·Hacker News logoHacker News·GitHub logoGitHub·Perplexity logoPerplexity·Naver logoNaver·Utility logoUtility·Universal Search logoUniversal Search
·TikTok logoTikTok·Instagram logoInstagram·YouTube logoYouTube·Facebook logoFacebook·X logoX·LinkedIn logoLinkedIn·Reddit logoReddit·Threads logoThreads·Pinterest logoPinterest·Twitch logoTwitch·Truth Social logoTruth Social·Snapchat logoSnapchat·Kick logoKick·Bluesky logoBluesky·Kwai logoKwai·Rumble logoRumble·Spotify logoSpotify·Apple Music logoApple Music·TikTok Shop logoTikTok Shop·Amazon Shop logoAmazon Shop·Google Shopping logoGoogle Shopping·Trustpilot logoTrustpilot·TripAdvisor logoTripAdvisor·Yelp logoYelp·Linktree logoLinktree·Komi logoKomi·Pillar logoPillar·lnk.bio logolnk.bio·Facebook Ads logoFacebook Ads·Google Ads logoGoogle Ads·LinkedIn Ads logoLinkedIn Ads·Google Search logoGoogle Search·Google News logoGoogle News·Finance logoFinance·Polymarket logoPolymarket·Tavily logoTavily·Hacker News logoHacker News·GitHub logoGitHub·Perplexity logoPerplexity·Naver logoNaver·Utility logoUtility·Universal Search logoUniversal Search
·TikTok logoTikTok·Instagram logoInstagram·YouTube logoYouTube·Facebook logoFacebook·X logoX·LinkedIn logoLinkedIn·Reddit logoReddit·Threads logoThreads·Pinterest logoPinterest·Twitch logoTwitch·Truth Social logoTruth Social·Snapchat logoSnapchat·Kick logoKick·Bluesky logoBluesky·Kwai logoKwai·Rumble logoRumble·Spotify logoSpotify·Apple Music logoApple Music·TikTok Shop logoTikTok Shop·Amazon Shop logoAmazon Shop·Google Shopping logoGoogle Shopping·Trustpilot logoTrustpilot·TripAdvisor logoTripAdvisor·Yelp logoYelp·Linktree logoLinktree·Komi logoKomi·Pillar logoPillar·lnk.bio logolnk.bio·Facebook Ads logoFacebook Ads·Google Ads logoGoogle Ads·LinkedIn Ads logoLinkedIn Ads·Google Search logoGoogle Search·Google News logoGoogle News·Finance logoFinance·Polymarket logoPolymarket·Tavily logoTavily·Hacker News logoHacker News·GitHub logoGitHub·Perplexity logoPerplexity·Naver logoNaver·Utility logoUtility·Universal Search logoUniversal Search
Reddit 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

curl -H "x-api-key: YOUR_API_KEY" \
  "https://www.socialcrawl.dev/v1/reddit/search?query=%22claude+code%22&label=sponsored&relevance=filter&trim=true"
import requests

response = requests.get(
    "https://www.socialcrawl.dev/v1/reddit/search",
    params={
    'query': '"claude code"',
    '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/reddit/search?query=%22claude+code%22&label=sponsored&relevance=filter&trim=true",
  {
    headers: { "x-api-key": "YOUR_API_KEY" },
  },
);

const data = await response.json();

Parameters worth sending

  • label=sponsored Marks each post that is paid or sponsored, at no extra credits; intent and niche are free too.
  • relevance=filter Drops rows that are not about your query, at no extra credits; relevance=score keeps them and adds a score.
  • trim=true Same price, lighter payload: drops the bulky raw fields.

Parameters

ParameterRequiredDescription
queryYesSearch 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.
sortNoSort by (relevance | new | top | comment_count)
timeframeNoOnly 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)
afterNoUsed to paginate to next page
trimNoSet 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_bodyNoSet 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.
relevanceNoOptional. 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_thresholdNoOptional, 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_toNoOptional, 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.
judgmentsNoOptional, 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_runNoOptional. 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)
fitNoOptional. 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)
goalNoRequired by fit=goal. What you are trying to do, in your own words, up to 300 characters.
fit_tokensNoOptional, 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.
labelNoOptional 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.
excludeNoOptional 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.
brandNoRequired 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_descriptionNoOptional, 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.
offerNoOptional, 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_evidenceNoOptional, 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)
sinceNoOnly 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`.
untilNoOnly 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_daysNoKeep 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.
max_pagesNo1 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.
seenNoAn 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

Why SocialCrawl

Why use SocialCrawl for Reddit Search data?

We handle the complexity of Reddit data extraction so you can focus on building. Unified schema, AI enrichment, and zero platform logic in your code.

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 68 platforms covering 10B+ monthly active users.

One schema, every platform

Query 68 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"
    }
  }
}
+ 68 platforms
FAQ

Have a question? We got answers

Find answers to frequently asked questions about SocialCrawl's API, pricing, and capabilities.

Contact us
How 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

Ready to scrape Reddit Search data?

Get your API key and start pulling Reddit data in under 60 seconds.

Start for free

🤖 AI agent or LLM? Read this page as markdown