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

Pinterest Search API

Scrape Pinterest Search data with one API call. Searches Pinterest for pins matching a keyword. Each pin includes its permalink, the original image (`post.content.media_urls`) and a thumbnail, the pinner's username, name and avatar, and the date it was pinned. `post.content.text` is the pin's title, or its description when the title is empty; many pins carry neither, so it is null on those rows. The search results themselves carry no engagement, so on a plain call `post.engagement.saves`, `.likes` (reactions), `.comments` and `.shares` are null. Send `include=engagement` and every row is joined, in the same call, to the per-pin lookup that carries them: the save count, the reaction count, the comment count and the share count land on each row. Cost: 1 credit for the page plus 1 credit per row filled from a fresh lookup (25 rows max, so 26 credits at most); rows already in cache are filled for free, rows that could not be filled are refunded, and a repeat of the same call within the cache window is 0 credits. Time: a plain call is about 2 seconds; `include=engagement` adds 4 to 10 seconds on a fresh page (the lookups run in parallel and the call waits for the slowest, never more than 12 seconds) and nothing when the rows are already cached. `limit=N` caps the rows and the credits together. The response carries a `hydration` block itemising rows, lookups, cache hits, credits and milliseconds. `post.engagement.views` is not published for search results and stays null either way. Page with cursor.

Last updated October 2026Maintained by the SocialCrawl team

Start for freeView Documentation

Returns Pinterest pins matching a keyword, each with its text, original image, pinner and pin date; include=engagement adds save, reaction, comment and share counts.

Use it to discover pins on a topic; add include=engagement for each pin's saves at 1 credit a row, or call pin when you already have one pin URL.

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
Pinterest API

What can you do with the Search API?

The Search endpoint gives you structured Pinterest 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/pinterest/search?query=home+decor+ideas&trim=true"
import requests

response = requests.get(
    "https://www.socialcrawl.dev/v1/pinterest/search",
    params={
    'query': 'home decor ideas',
    'trim': 'true',
    },
    headers={"x-api-key": "YOUR_API_KEY"},
)

data = response.json()
const response = await fetch(
  "https://www.socialcrawl.dev/v1/pinterest/search?query=home+decor+ideas&trim=true",
  {
    headers: { "x-api-key": "YOUR_API_KEY" },
  },
);

const data = await response.json();

Parameters worth sending

  • trim=true Same price, lighter payload: drops the bulky raw fields.

Parameters

ParameterRequiredDescription
queryYesKeyword or phrase to search Pinterest pins for.
cursorNoCursor to get the next page. Take it from `pagination.next_cursor` on the previous response.
trimNoSet to true for a trimmed down version of the response
includeNoSet to `engagement` (one token only) to fill `post.engagement.saves`, `.likes` (reactions), `.comments` and `.shares` on every row in this one call. Holds 1 credit per row (at most 25, or `limit`) and keeps only the rows filled from a fresh lookup; rows already in cache and rows that could not be filled are refunded, so the most a call can cost is 1 + rows and the usual bill is lower. Adds 4 to 10 seconds on a fresh page (never more than 12) and nothing when the rows are already cached; read `data.hydration` for the rows, the credits held and kept, and the time. (engagement)
limitNoTake the top N rows of the page (1 to 25) after the search has run. With `include=engagement` it also caps the extra credits at N: `limit=5&include=engagement` costs at most 6. It is not a page size: `next_cursor` still advances past the full page, so rows beyond N on this page are not returned by the next page.
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 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`.
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`.
Example Response

What does the Pinterest 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": "pinterest",
  "endpoint": "/v1/pinterest/search",
  "data": {
    "items": [
      {
        "post": {
          "id": "__EMPTY__",
          "url": "https://www.pinterest.com/pin/1095292987353812",
          "content": {
            "text": null,
            "media_urls": null,
            "thumbnail_url": null,
            "duration_seconds": null
          },
          "author": {
            "username": null,
            "display_name": null,
            "avatar_url": null,
            "verified": null
          },
          "engagement": {
            "views": null,
            "likes": null,
            "comments": null,
            "shares": null,
            "saves": null
          },
          "flags": {
            "nsfw": null,
            "spoiler": null,
            "pinned": null,
            "deleted": false
          },
          "published_at": null
        },
        "computed": {
          "engagement_rate": null,
          "language": null,
          "content_category": null,
          "estimated_reach": null
        }
      },
      {
        "post": {
          "id": "UGluOjIyNTAzOTMxMjYyNzg4MTg5Mg==",
          "url": "https://www.pinterest.com/pin/225039312627881892",
          "content": {
            "text": "Sample comment text (redacted).",
            "media_urls": "https://i.pinimg.com/originals/2c/24/91/2c24917f5d44c73a48b10de4692f3467.jpg",
            "thumbnail_url": "https://i.pinimg.com/236x/2c/24/91/2c24917f5d44c73a48b10de4692f3467.jpg",
            "duration_seconds": null
          },
          "author": {
            "username": "user_734df9",
            "display_name": "user_d051ef",
            "avatar_url": "https://example.com/avatars/user_0ea4f2.png",
            "verified": null
          },
          "engagement": {
            "views": null,
            "likes": null,
            "comments": null,
            "shares": null,
            "saves": null
          },
          "flags": {
            "nsfw": null,
            "spoiler": null,
            "pinned": null,
            "deleted": false
          },
          "published_at": "2022-11-05T14:37:02.000Z"
        },
        "computed": {
          "engagement_rate": null,
          "language": null,
          "content_category": "other",
          "estimated_reach": null
        }
      }
    ],
    "next_cursor": "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",
    "total": null,
    "dropped": 0
  },
  "credits_used": 1,
  "request_id": "req_example000000",
  "cached": false,
  "pagination": {
    "next_cursor": "sc.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",
    "has_more": true,
    "page_size": 2
  },
  "credits_remaining": 9999,
  "source": "captured",
  "captured_at": "2026-10-02T07:26:41.042Z",
  "redacted": true
}

Live sample illustrating the unified response shape. Field values reflect the record you query.

API Details

How does the Pinterest 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 Pinterest Search data?

We handle the complexity of Pinterest 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 Pinterest pins by keyword with an API?
Send a GET request to /v1/pinterest/search with a query parameter. SocialCrawl returns matching pins with their text, full-size image URLs, author info, and the pin date, ranked by Pinterest relevance. Add include=engagement and every row also carries its save, reaction, comment, and share counts.
What data does each Pinterest search result include?
Each result returns pin id, permalink, text (the pin's title, or its description when the title is empty), image URLs at multiple resolutions, author info, and the pin date. The counts arrive with include=engagement, at 1 extra credit per row filled. All normalised into the unified SocialCrawl post schema.
Can I paginate through Pinterest search results?
Yes. Pass the cursor parameter returned in the previous response to fetch the next page. Combined with trim=true, this makes it easy to stream thousands of pins for trend analysis without blowing up bandwidth.
How is this different from the official Pinterest API?
The official Pinterest API requires OAuth, a business account, and app review, and does not expose keyword pin search at the depth SocialCrawl does. Our search endpoint works with any x-api-key, no Pinterest login.
How much does the Pinterest Search API cost?
Each search costs 1 credit on the standard tier. New accounts get 100 free credits with no credit card required, enough to run 100 Pinterest keyword searches before you pay anything.

Ask AI about SocialCrawl

Ask ChatGPTAsk PerplexityAsk GeminiAsk ClaudeAsk Grok

Ready to scrape Pinterest Search data?

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

Start for free

🤖 AI agent or LLM? Read this page as markdown