Pinterest Pins Videos Search Scraper By Keyword

Pinterest Video Scraper — Pins, Videos & Keyword Suggestions

Pinterest Video Scraper — Pins, Videos & Keyword Suggestions turns seed keywords, search URLs, or usernames into structured Pinterest search results: pin and video cards plus Pinterest's own related-keyword autocomplete suggestions. Every pin carries hashtags parsed from its own title and description, plus locally-derived SEO metrics like title length and alt-text presence — no fabricated volume or trend numbers. Every response is structured JSON, ready to pass to an LLM, index into a vector store, or feed a content-planning pipeline. Point it at a niche and start mining results.

What is Pinterest Video Scraper — Pins, Videos & Keyword Suggestions?

Pinterest Video Scraper By Keyword queries Pinterest's public search-by-keyword surface for one or more seed terms and returns every matching pin or video card as a structured JSON row, alongside Pinterest's own related-keyword autocomplete suggestions for the same seed. No Pinterest account or login is required — the Actor runs logged-out against Pinterest's public search and typeahead endpoints. Each pin row is enriched with hashtags parsed from its own title/description text and locally-computed SEO metrics, so a single run returns both raw pin data and lightweight content-SEO signals.

• Bulk seed-keyword input — keywords, full search URLs, or usernames, mixed in one seedKeywords array
• Video-only or all-format filtering via pinFormatFilter (defaults to Videos)
• Related-keyword expansion — pulls Pinterest's own autocomplete suggestions per seed (expandKeywords, capped by seedKeywordCount)
• Hashtag extraction straight from each pin's own title/description text (extractHashtags)
• Locally-derived SEO metrics per pin — title/description length, alt-text presence (includeSeoMetrics)
• Automatic proxy escalation (no proxy → datacenter → residential, 3 retries) when Pinterest blocks a request

What data can you get with Pinterest Video Scraper — Pins, Videos & Keyword Suggestions?

The Actor returns two row types in the same dataset: scraped pins/videos, and related-keyword suggestion rows.

Result Type	Extracted Fields	Primary Use Case
Pin / video (type: "pin")	node_id, pinUrl, created_at, scrapedAt, title, description, hashtags, hashtagCount, titleLength, descriptionLength, hasAltText, url, link, link_to_video, is_video, pinner, domain, dominant_color, width, height, image_size, reaction_counts, search_term	Visual/content trend research, video sourcing, pin-level SEO auditing
Related keyword suggestion (type: "keyword_suggestion")	isChild, parentId, seedKeyword, suggestion, search_term, scrapedAt	Keyword and content planning, board/pin-title ideation

Related keyword suggestion rows

When expandKeywords is on, each seed keyword also gets its own set of suggestion rows pulled live from Pinterest's AdvancedTypeaheadResource autocomplete endpoint — the same one that powers Pinterest's own search box. Each suggestion is plain text (suggestion), tied back to its seed via seedKeyword/parentId, capped per seed by seedKeywordCount. No volume, rank, or trend number is attached, because Pinterest's autocomplete endpoint doesn't expose one — only the suggestion text itself.

{
  "type": "keyword_suggestion",
  "seedKeyword": "home decor",
  "suggestion": "home decor ideas on a budget",
  "parentId": "home decor"
}

Why not build this yourself?

Pinterest's own API (v5) is built for managing a business account's own boards and pins, not for searching what's publicly visible across all of Pinterest for an arbitrary keyword. Its "Search user's Pins" endpoint only searches the authenticated account's own pins, and partner-level pin search requires marketing-partner approval — neither gives an ordinary developer a public keyword-search endpoint over all of Pinterest.

Building an equivalent search-by-keyword pipeline yourself means maintaining a headless browser against Pinterest's search results pages and the AdvancedTypeaheadResource autocomplete endpoint, tracking response-shape changes as Pinterest updates its site, and running a proxy-escalation chain for when Pinterest blocks a request — all before writing a line of hashtag or SEO-metric logic. Pinterest Video Scraper — Pins, Videos & Keyword Suggestions already does this: response-interception search scraping with bookmark-cursor pagination, plus the same no-proxy → datacenter → residential fallback chain, so you send a keyword and get structured rows back.

How to scrape Pinterest with Pinterest Video Scraper — Pins, Videos & Keyword Suggestions?

No input field is required to start a run, but seedKeywords needs at least one entry to return any results.

1. Open the Actor on its Apify Store listing and go to the Input tab.
2. Add one or more keywords, Pinterest search URLs, or usernames to seedKeywords.
3. Set pinFormatFilter (All or Videos) and maxPinsPerKeyword for how much to pull per seed.
4. Turn expandKeywords, extractHashtags, and includeSeoMetrics on or off as needed.
5. Start the run, then read results from the Dataset tab or export as JSON/CSV.

{
  "seedKeywords": ["home decor", "cat"],
  "maxPinsPerKeyword": 50,
  "pinFormatFilter": "Videos",
  "expandKeywords": true,
  "seedKeywordCount": 20
}

How to run multiple keyword searches in one job

seedKeywords accepts an array — each keyword, search URL, or username is scraped one after another within the same run, with each seed's pins and (if enabled) related-keyword suggestions saved to the dataset before the next seed starts. There is no documented concurrency setting for running seeds in parallel; seeds are processed sequentially in the order supplied.

⬇️ Input

All 8 input fields are optional; seedKeywords (or its fallback key searchTerms) needs at least one entry for a run to return data.

Parameter	Required	Type	Description	Example Value
seedKeywords	No	array	Pinterest search keywords, profile URLs, or usernames to mine. Bulk input supported. Fallback key: searchTerms.	["home decor", "cat"]
maxPinsPerKeyword	No	integer	Max pins to scrape per seed keyword (1–1000). Fallback key: maxItems.	50
pinFormatFilter	No	string	All (pins + videos) or Videos only. Fallback key: filtre.	Videos
expandKeywords	No	boolean	Fetch related search-suggestion keywords per seed from Pinterest's own autocomplete. Default true.	true
seedKeywordCount	No	integer	Max related-suggestion rows kept per seed keyword when expandKeywords is on (1–50). Default 20.	20
extractHashtags	No	boolean	Parse #hashtags out of each pin's own title/description. Default true.	true
includeSeoMetrics	No	boolean	Add titleLength, descriptionLength, hasAltText to every pin row. Default true.	true
proxyConfiguration	No	object	Proxy behavior. Default: no proxy, with automatic datacenter → residential fallback if Pinterest blocks a request.	{"useApifyProxy": false}

Example JSON input

{
  "seedKeywords": ["home decor", "cat"],
  "maxPinsPerKeyword": 50,
  "pinFormatFilter": "Videos",
  "expandKeywords": true,
  "seedKeywordCount": 20,
  "extractHashtags": true,
  "includeSeoMetrics": true,
  "proxyConfiguration": { "useApifyProxy": false }
}

Common pitfall: expandKeywords is on by default, and every related-keyword suggestion row is billed through the same pin_result charged event as pin rows. A run with several seed keywords and seedKeywordCount set high adds that many extra billed rows per seed on top of the pins themselves — turn expandKeywords off if you only want pin/video data.

⬆️ Output

Results are typed, normalized JSON with a consistent schema across both row types, exportable as JSON, CSV, or Excel from the Dataset tab.

Scraped results

[
  {
    "node_id": "4362930884162196",
    "type": "pin",
    "isChild": false,
    "parentId": null,
    "pinUrl": "https://www.pinterest.com/pin/4362930884162196/",
    "created_at": "Wed, 17 Sep 2025 21:05:25 +0000",
    "scrapedAt": "2026-07-25T10:12:03Z",
    "title": "Boho Home Decor Ideas #bohodecor #HomeDecor",
    "description": "Cozy living room styling #interiordesign",
    "hashtags": ["bohodecor", "homedecor", "interiordesign"],
    "hashtagCount": 3,
    "titleLength": 43,
    "descriptionLength": 40,
    "hasAltText": true,
    "seedKeyword": null,
    "suggestion": null,
    "url": "https://i.pinimg.com/236x/46/f4/88/46f4885495c1ed7ca2dbfd4787b06bb6.jpg",
    "link": null,
    "link_to_video": null,
    "is_video": false,
    "pinner": { "full_name": "Sofia Ortiz", "username": "sofiacamposflor", "follower_count": 4, "image_url": "https://s.pinimg.com/images/user/default_140.png" },
    "domain": "Uploaded by user",
    "dominant_color": "#88a549",
    "width": 236,
    "height": 236,
    "image_size": "236x",
    "reaction_counts": { "1": 1877 },
    "search_term": "home decor"
  },
  {
    "node_id": "8821457930012648",
    "type": "pin",
    "isChild": false,
    "parentId": null,
    "pinUrl": "https://www.pinterest.com/pin/8821457930012648/",
    "created_at": "Fri, 04 Jul 2025 14:22:10 +0000",
    "scrapedAt": "2026-07-25T10:12:05Z",
    "title": "5-Minute Cat Grooming Routine #cattips",
    "description": "Quick brushing tutorial for short-haired cats #cats #pettips",
    "hashtags": ["cattips", "cats", "pettips"],
    "hashtagCount": 3,
    "titleLength": 39,
    "descriptionLength": 62,
    "hasAltText": false,
    "seedKeyword": null,
    "suggestion": null,
    "url": "https://i.pinimg.com/736x/12/aa/cc/12aacc00e1a2b3c4d5e6f7089abcde12.jpg",
    "link": "https://example-pet-blog.com/cat-grooming",
    "link_to_video": "https://v1.pinimg.com/videos/mc/hls/12/aa/cc/12aaccvideo.m3u8",
    "is_video": true,
    "pinner": { "full_name": "Pet Care Daily", "username": "petcaredaily", "follower_count": 15230, "image_url": "https://s.pinimg.com/images/user/petcare_140.png" },
    "domain": "example-pet-blog.com",
    "dominant_color": "#c9a876",
    "width": 736,
    "height": 736,
    "image_size": "736x",
    "reaction_counts": { "1": 542, "2": 87 },
    "search_term": "cat"
  },
  {
    "node_id": null,
    "type": "keyword_suggestion",
    "isChild": true,
    "parentId": "home decor",
    "pinUrl": null,
    "created_at": null,
    "scrapedAt": "2026-07-25T10:12:06Z",
    "title": null,
    "description": null,
    "hashtags": null,
    "hashtagCount": null,
    "titleLength": null,
    "descriptionLength": null,
    "hasAltText": null,
    "seedKeyword": "home decor",
    "suggestion": "home decor ideas on a budget",
    "url": null,
    "link": null,
    "link_to_video": null,
    "is_video": null,
    "pinner": null,
    "domain": null,
    "dominant_color": null,
    "width": null,
    "height": null,
    "image_size": null,
    "reaction_counts": null,
    "search_term": "home decor"
  }
]

How can I use the data extracted with Pinterest Video Scraper — Pins, Videos & Keyword Suggestions?

• Pinterest marketers and content strategists: mine hashtags, titleLength, descriptionLength, and hasAltText from top-ranking pins in a niche to plan a new pin's title/description/hashtag set.
• E-commerce and product discovery teams: filter pin rows by domain and link to find which shoppable sites and product pages are already ranking for a keyword, without needing an affiliate or ads account.
• AI engineers and LLM developers: an agent issues a keyword query, receives this Actor's structured JSON back, and grounds a content or trend answer in live pin, video, and suggestion data instead of stale training data.
• Creative and video content researchers: filter to pinFormatFilter: "Videos" and read link_to_video to source real video-pin examples and their captions for an Idea Pin or Reel concept.

How do you monitor Pinterest keyword and hashtag trends over time?

Keyword and hashtag monitoring means re-running the same seed keywords on a schedule and comparing the new rows to the previous run, rather than treating one run as a permanent snapshot of what's trending. Because every pin row is deduplicated by node_id and every suggestion row is tied to its seedKeyword, repeated runs let you diff which node_ids are new since the last run (fresh content ranking for that keyword), which hashtags are appearing more often across new pins, and which suggestion values are new or have dropped out of Pinterest's own autocomplete for a seed term.

A basic workflow: schedule this Actor against a fixed seedKeywords list (one entry per niche or competitor term you track), store each run's rows keyed by node_id/suggestion and scrapedAt in your own database, then compare the newest run against the previous one. Alert on the changes that matter to you — a burst of new node_ids carrying a hashtag you don't currently use, a competitor's domain suddenly appearing across multiple pins for the same keyword, or a new autocomplete suggestion worth targeting before it gets competitive. Apify's platform-level Schedule feature can trigger the Actor on a fixed interval without any code of your own, and the Apify API's dataset endpoints or run-finished webhooks can deliver each run's results into your own pipeline for the diffing step.

Integrate Pinterest Video Scraper — Pins, Videos & Keyword Suggestions and automate your workflow

Pinterest Video Scraper — Pins, Videos & Keyword Suggestions works with any language or tool that can send an HTTP request.

REST API with Python

import requests

TOKEN = "<YOUR_APIFY_TOKEN>"
url = "https://api.apify.com/v2/acts/scrapier~pinterest-pins-videos-search-scraper-by-keyword/run-sync-get-dataset-items"

payload = {
    "seedKeywords": ["home decor"],
    "pinFormatFilter": "Videos",
    "maxPinsPerKeyword": 50,
}

resp = requests.post(url, params={"token": TOKEN}, json=payload, timeout=180)
rows = resp.json()  # pin and keyword_suggestion rows, as shown above

for row in rows:
    if row["type"] == "pin":
        print(row["node_id"], row["is_video"], row["hashtags"])

MCP for query-grounded AI agents

The Actor is reachable through Apify's Actors MCP Server: run npx @apify/actors-mcp-server --tools scrapier/pinterest-pins-videos-search-scraper-by-keyword locally with an APIFY_TOKEN set, or connect the hosted server at https://mcp.apify.com. Register it with an MCP-compatible client — Claude Desktop, Claude Code, or Cursor — and an agent can call it as a tool: a user asks about a trend, the agent runs the keyword search, and grounds its answer in the returned pin and suggestion fields instead of guessing.

Scheduled monitoring and delivery

There is no actor-specific webhook built into this Actor. Attach it to Apify's platform-level Schedule to trigger runs on an interval, and use the Apify API's run-finished webhooks or dataset export endpoints to deliver each run's rows into your own storage or pipeline.

Is it legal to scrape Pinterest pins?

Scraping publicly accessible Pinterest search results is generally lawful — courts have held that accessing data a site makes available to any visitor, without bypassing an access barrier, does not violate the Computer Fraud and Abuse Act (hiQ Labs, Inc. v. LinkedIn Corp., 9th Cir., 2019). Pinterest Video Scraper — Pins, Videos & Keyword Suggestions returns only what a logged-out visitor to a public search page already sees. That said, pinner rows carry a public username, display name, and follower count, which counts as personal data in some jurisdictions (GDPR/CCPA) even when publicly posted, and Pinterest's own Terms of Service restrict automated collection — review both before storing this data at scale. Scraping for periodic trend monitoring carries a different risk profile than scraping to train a model. Consult your legal team for commercial use cases involving bulk data storage or resale.

Frequently asked questions

Can I search by username or profile URL instead of a keyword?

Yes. seedKeywords accepts Pinterest profile URLs and plain usernames alongside plain keywords — the Actor extracts a search term from whatever form you provide.

Can I get all pin formats, or only videos?

Both. pinFormatFilter defaults to Videos (video pins only) but can be set to All to include image pins too; either way, is_video and link_to_video on each row tell you which is which.

How does this Actor handle Pinterest's anti-bot measures?

It escalates proxies automatically when Pinterest blocks a request: no proxy first, then Apify datacenter proxy, then residential proxy with up to 3 retries. It also warms up each browser session by loading pinterest.com before issuing the search request.

How many results does this Actor return per query?

maxPinsPerKeyword caps pins at up to 1000 per seed keyword (default 50), and — separately — seedKeywordCount caps related-keyword suggestions at up to 50 per seed (default 20) when expandKeywords is on.

How do I monitor a keyword's hashtags and suggestions over time?

Schedule this Actor against the same seedKeywords list, store each run's rows keyed by node_id/suggestion, and diff hashtags, new node_ids, and suggestion values between runs to catch fresh content and rising search terms.

Does it work with Claude, ChatGPT, and AI agent frameworks?

Yes — it's callable as a plain HTTP endpoint by any agent framework that can send a request, and it's also reachable through Apify's Actors MCP Server (npx @apify/actors-mcp-server --tools scrapier/pinterest-pins-videos-search-scraper-by-keyword, or the hosted https://mcp.apify.com) for MCP-native clients like Claude Desktop and Claude Code.

How does this Actor compare to other Pinterest scrapers?

Pinterest Search Scraper (SEO Keyword Discovery), a related Actor in the same catalog, takes a single required seed keyword and computes an aggregate SEO summary row (top hashtags, top terms, keyword-coverage stats) on top of its pins. This Actor instead accepts a bulk array of seed keywords per run, defaults to video-first filtering, and returns per-pin hashtag/SEO fields plus raw autocomplete suggestion rows without an aggregate summary layer — better suited to scanning many seeds for raw pin and video data rather than deep single-keyword SEO analysis.

Can I use this Actor without managing proxies or a Pinterest account?

Yes. No Pinterest account or login is required — search pages and the autocomplete endpoint are scraped logged-out. Proxy handling is automatic: the default run uses no proxy, and if Pinterest blocks a request, the Actor escalates to datacenter and then residential proxy on its own.

Your feedback

Found a bug or a field that doesn't match what's documented here? Let us know through the Actor's Issues tab on Apify or Scrapier's support contact — reports like this go straight into fixing the extractor.