Prism Mentions API
Scrape Prism Mentions data with one API call. Pass handle (the @ is optional), or url (a link or a link prefix), or name on its own. platforms defaults to twitter, reddit, facebook. Opt in to instagram for posts that tag the handle, or web (url only) for a web page that contains the link. since is YYYY-MM-DD. include_self defaults to false and drops the account's own rows. Each kept row has match_kind reply, retweet, mention or tag. Unverified rows are dropped and counted in dropped_unverified. Url mode adds first_seen for the link. name is judged; a handle or a url is checked in code and is not judged. If that judgment is unavailable the rows are kept and warnings says why. Instagram comments on unknown posts cannot be searched, and Instagram caption mentions cannot. TikTok comments on unknown posts cannot be searched. Threads search is weak: measured 23/09/2026 it returned no row containing the handle, so Threads is not searched. Facebook post search returned no row containing the handle or the link on the same day, so Facebook is not searched. TikTok search for @handle returned no row containing that @, so TikTok is not searched. Bluesky has no search lane. LinkedIn is not covered. Private or deleted content is not covered. This is a first page of each search, not an index.
Last updated September 2026Maintained by the SocialCrawl team
Returns public posts and comments that mention a handle or contain a link, from the first page of each search that can find them.
Use it to find public mentions of an account or a link when you do not already know the post. It is a first page, not an index.
Searching 67 platforms in parallel
What can you do with the Mentions API?
The Mentions endpoint gives you structured Prism 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/prism/mentions?handle=nasa"import requests
response = requests.get(
"https://www.socialcrawl.dev/v1/prism/mentions",
params={
'handle': 'nasa',
},
headers={"x-api-key": "YOUR_API_KEY"},
)
data = response.json()const response = await fetch(
"https://www.socialcrawl.dev/v1/prism/mentions?handle=nasa",
{
headers: { "x-api-key": "YOUR_API_KEY" },
},
);
const data = await response.json();Parameters
| Parameter | Required | Description |
|---|---|---|
| handle | No | Account handle, with or without @. Checked in code. Not combined with name. |
| url | No | A link or a link prefix, such as example.com/news. Checked in code. Not combined with name. |
| name | No | A display name, 2 to 120 characters, passed on its own. Each row is judged. A failed judgment keeps the rows. |
| platforms | No | Comma-separated subset of twitter, reddit, facebook, threads, instagram, tiktok, web. Default twitter, reddit, facebook. Instagram needs a handle. Web needs a url. Facebook, Threads and TikTok are accepted and not searched. |
| since | No | Only keep rows published on or after this date, YYYY-MM-DD. On X it is also part of the search. |
| include_self | No | When true, keep rows whose author is the handle. Default false. |
What does the Prism Mentions 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 Prism Mentions response has the same fields.
How does the Prism Mentions 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 67 platforms covering 10B+ monthly active users.
One schema, every platform
Query 67 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"
}
}
}Ready to scrape Prism Mentions data?
Get your API key and start pulling Prism data in under 60 seconds.
