Reddit Omni Search API
Scrape Reddit Omni Search data with one API call. Runs reddit/search, expands the top N threads' comments in parallel (capped 15/thread), and rolls up which subreddits are talking. Each thread carries its comments at `threads[].top_comments` (the `include` parameter names this block `comments`; the field on the response is `top_comments`). Each rollup row is `{ name, subscribers, weekly_active_users, thread_count, tone }`. `subscribers` is how many accounts have joined the community and `weekly_active_users` is how many took part in the last week. The second is NOT a subset of the first, because Reddit does not require joining to post or comment: measured on r/keyboards the weekly figure (188,869) is HIGHER than the subscriber count (147,416), while on r/technology it is far lower. Read them as two independent signals, size against liveliness, and never as a ratio. Both are filled from the same source as `/v1/reddit/subreddit/details` and inherit its behaviour, so on a small share of rows one or both can be null while the rest of the row is unchanged. `tone` is one LLM label per community and degrades to null with a `_warnings` line rather than a silent blank. Returns sync JSON or a typed SSE stream that emits each thread as its comments land. Metered at 1 credit per search page + 1 credit per successfully-expanded thread (minimum 5); a failed thread isn't billed and the unused thread ceiling is refunded. `subreddit=` scopes the sweep to one community. The `next_cursor` resumes the search. Honest note: Reddit search is the slowest social search on the API (a 10 to 12s median, with a tail past 30s, so allow a 60s client timeout) and relevance is loose: a VoC sweep, not precision ranking.
Last updated September 2026Maintained by the SocialCrawl team
Returns threads from across Reddit for one keyword with their top comments inline at top_comments, plus a roll-up of which subreddits are talking, their weekly active users and tone.
Use it for a customer-listening sweep in one call rather than running search then post/comments per thread; it is slow and relevance is loose.
Searching 65 platforms in parallel
What can you do with the Omni Search API?
The Omni 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/omni-search?query=best+mechanical+keyboard&threads=5"import requests
response = requests.get(
"https://www.socialcrawl.dev/v1/reddit/omni-search",
params={
'query': 'best mechanical keyboard',
'threads': '5',
},
headers={"x-api-key": "YOUR_API_KEY"},
)
data = response.json()const response = await fetch(
"https://www.socialcrawl.dev/v1/reddit/omni-search?query=best+mechanical+keyboard&threads=5",
{
headers: { "x-api-key": "YOUR_API_KEY" },
},
);
const data = await response.json();Parameters
| Parameter | Required | Description |
|---|---|---|
| query | Yes | Keyword or phrase to sweep across Reddit. |
| threads | No | How many top threads to expand comments for (1-8, default 8). |
| sort | No | Search sort order (relevance | new | top | comment_count). (relevance | new | top | comment_count) |
| timeframe | No | Time window for the search (all | day | week | month | year). (all | day | week | month | year) |
| subreddit | No | Scope the sweep to one subreddit (bare name, no r/ prefix). |
| cursor | No | Opaque cursor from a prior response's next_cursor to page deeper. |
| include | No | CSV subset of subreddits,comments (default both). The comments block is returned as `threads[].top_comments`. |
What does the Reddit Omni 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": "instagram",
"endpoint": "/v1/instagram/engagement",
"data": {
"engagement_rate_percentages": 38.33,
"recent_posts": 12,
"followers": 87608035,
"comments": 528912,
"likes": 33049046,
"recent_posts_explanation": "Statistics based on the last 12 posts",
"id_user": "2278169415",
"username": "mrbeast",
"is_private": false,
"posts_details": [
{
"likes": 5636982,
"comments": 69484,
"taken_at": 1781457954,
"datetime": "2026-06-14 20:25:54",
"hours_since_post": 461,
"time_ago": "19 days ago",
"likes_per_hour": 12228,
"comments_per_hour": 151
},
{
"likes": 20000768,
"comments": 223510,
"taken_at": 1732824650,
"datetime": "2024-11-28 23:10:50",
"hours_since_post": 13971,
"time_ago": "2 years ago",
"likes_per_hour": 1432,
"comments_per_hour": 16
},
{
"likes": 929226,
"comments": 30633,
"taken_at": 1782232475,
"datetime": "2026-06-23 19:34:35",
"hours_since_post": 246,
"time_ago": "10 days ago",
"likes_per_hour": 3777,
"comments_per_hour": 125
},
{
"likes": 487761,
"comments": 22482,
"taken_at": 1781799425,
"datetime": "2026-06-18 19:17:05",
"hours_since_post": 366,
"time_ago": "15 days ago",
"likes_per_hour": 1333,
"comments_per_hour": 61
},
{
"likes": 712265,
"comments": 15716,
"taken_at": 1781366405,
"datetime": "2026-06-13 19:00:05",
"hours_since_post": 487,
"time_ago": "20 days ago",
"likes_per_hour": 1463,
"comments_per_hour": 32
},
{
"likes": 1475116,
"comments": 35386,
"taken_at": 1781277094,
"datetime": "2026-06-12 18:11:34",
"hours_since_post": 512,
"time_ago": "21 days ago",
"likes_per_hour": 2881,
"comments_per_hour": 69
},
{
"likes": 1108220,
"comments": 26632,
"taken_at": 1780160249,
"datetime": "2026-05-30 19:57:29",
"hours_since_post": 822,
"time_ago": "1 months ago",
"likes_per_hour": 1348,
"comments_per_hour": 32
},
{
"likes": 542948,
"comments": 28476,
"taken_at": 1779375582,
"datetime": "2026-05-21 17:59:42",
"hours_since_post": 1040,
"time_ago": "1 months ago",
"likes_per_hour": 522,
"comments_per_hour": 27
},
{
"likes": 698514,
"comments": 24401,
"taken_at": 1779120014,
"datetime": "2026-05-18 19:00:14",
"hours_since_post": 1111,
"time_ago": "2 months ago",
"likes_per_hour": 629,
"comments_per_hour": 22
},
{
"likes": 468000,
"comments": 13548,
"taken_at": 1778947209,
"datetime": "2026-05-16 19:00:09",
"hours_since_post": 1159,
"time_ago": "2 months ago",
"likes_per_hour": 404,
"comments_per_hour": 12
},
{
"likes": 526594,
"comments": 24411,
"taken_at": 1777737719,
"datetime": "2026-05-02 19:01:59",
"hours_since_post": 1495,
"time_ago": "2 months ago",
"likes_per_hour": 352,
"comments_per_hour": 16
},
{
"likes": 462652,
"comments": 14233,
"taken_at": 1777580305,
"datetime": "2026-04-30 23:18:25",
"hours_since_post": 1538,
"time_ago": "2 months ago",
"likes_per_hour": 301,
"comments_per_hour": 9
}
]
},
"credits_used": 5,
"credits_remaining": 9999,
"request_id": "req-8Kq2ZmR4vT9xLb3P",
"cached": false
}Example captured from the Instagram API. Every SocialCrawl endpoint returns this same unified schema, so your Reddit Omni Search response has the same fields.
How does the Reddit Omni 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?
The fastest social media scraping API for developers. Scrape profiles, posts, comments, and analytics from 65 platforms covering 10B+ monthly active users.
One schema, every platform
Query 65 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(){
"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
Find answers to frequently asked questions about SocialCrawl's API, pricing, and capabilities.
Contact usHow do I search all of Reddit with one API call?
Does the Reddit search API include comments?
Can I scope the sweep to one subreddit?
How much does a Reddit search sweep cost?
Why is the Reddit sweep slower than other searches?
Ask AI about SocialCrawl
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