TikTok Search Scraper - [Videos, Hashtags & Users]

What is TikTok Search Scraper - Videos, Hashtags & Users?

TikTok Search Scraper is an Apify Actor for keyword, top, hashtag, and user search across TikTok. It accepts search queries, hashtags, and creator-name or brand-name user queries, then stores one normalized dataset record per returned search result. Those records can represent videos, top search items, hashtags, or user profiles, with useful fields such as video IDs and URLs, captions, creator usernames, profile URLs, follower counts, and engagement metrics when returned. The actor requires no cookies or TikTok login and is usable through Apify MCP for natural-language workflows.

Best fit and connected workflows

This actor fits workflows that start with TikTok discovery and end with targeted enrichment or downstream analysis. Common routing patterns include:

• Search by keyword to collect TikTok videos for content research, social listening, or trend triage.
• Search by hashtag to gather topical video rows around a subject or campaign term.
• Search by user query to identify creator profiles and public profile metrics.
• Use searchType: all when you want keyword videos, top results, and user profiles from the same search query.
• Send discovered public profile URLs or IDs into TikTok Profile Posts Scraper - Creator Feed Data when you want creator feed enrichment for selected profiles.
• Send discovered public profile URLs or IDs into TikTok Profile Videos Scraper when you want profile video enrichment for selected creators.

Practical scenario

Maya is preparing a creator shortlist for a running-shoe campaign. She starts with searchQueries: ["nike running"], searchType: "keyword", and userQueries: ["nike"]. The actor returns a first page of video rows and profile rows. Maya reviews videoUrl, caption, authorUsername, playCount, likeCount, and profileUrl to separate creator-led videos from brand-owned profiles. Her next action is to open the strongest profile records in a downstream profile scraper for deeper creator review.

Inputs

Field	Type	Purpose
searchQueries	array of strings	Keywords or phrases to search on TikTok. Used with searchType.
searchType	string	Search surface for searchQueries: keyword, top, users, or all.
keywordQueries	array of strings	Always runs keyword video search for these queries.
topQueries	array of strings	Always runs top search for these queries. Top search can include videos and photo carousels.
hashtags	array of strings	Hashtags to search, with or without #.
userQueries	array of strings	Creator profile searches by keyword, brand name, or person name.
maxResultsPerQuery	integer	Maximum normalized rows saved per query or hashtag.
maxPagesPerQuery	integer	Safety cap for result pages fetched per search target.
region	string	Alpha-2 country code for search localization when supported.
datePosted	string	Time filter for keyword search.
publishTime	string	Time filter for top search. Defaults to datePosted when omitted.
sortBy	string	Sort order for keyword and top search where supported.
includeRawData	boolean	Adds the raw source payload to each row for debugging and custom parsing.

Focused input example

{
  "searchQueries": ["nike running"],
  "searchType": "keyword",
  "hashtags": ["running"],
  "userQueries": ["nike"],
  "region": "US",
  "datePosted": "all-time",
  "sortBy": "relevance",
  "maxResultsPerQuery": 25,
  "maxPagesPerQuery": 3,
  "includeRawData": false
}

Output fields

The default dataset stores normalized rows with a shared shape across videos, top results, hashtag results, and user profiles.

Field	Meaning
recordType	video, top_result, or user.
searchType	keyword, top, hashtag, or users.
query	Search query or hashtag.
hashtag	Hashtag for hashtag search rows.
resultPosition	Position in the normalized result list.
page	Result page used to fetch the row.
cursor	Pagination cursor for that result page.
contentType	TikTok content type when returned.
videoId, videoUrl	Video identifiers and URLs.
caption, createdAt	Video text and creation timestamp.
authorUsername, authorNickname, authorVerified	Creator metadata for video rows.
username, profileUrl, nickname, bio, verified	Profile metadata for user rows.
playCount, likeCount, commentCount, shareCount, collectCount	Video engagement metrics when returned.
followerCount, followingCount, heartCount, videoCount, privateAccount	Public profile metrics when returned.
hashtags, musicId, musicTitle, musicAuthor	Tag and sound metadata when returned.
scrapedAt	Timestamp when the row was saved.

Illustrative dataset record

{
  "recordType": "video",
  "searchType": "keyword",
  "query": "nike running",
  "resultPosition": 1,
  "page": 1,
  "cursor": 10,
  "contentType": "video",
  "videoId": "7452069943757114646",
  "videoUrl": "https://www.tiktok.com/@creator/video/7452069943757114646",
  "caption": "New running shoes today",
  "createdAt": "2026-01-01T00:00:00.000Z",
  "authorUsername": "creator",
  "authorNickname": "Creator Name",
  "authorVerified": true,
  "playCount": 2932976,
  "likeCount": 197747,
  "commentCount": 347,
  "shareCount": 26467,
  "collectCount": 10436,
  "scrapedAt": "2026-06-11T00:00:00.000Z"
}

How it works

The actor fetches TikTok search results through a managed data provider with an automatic fallback provider, so no cookies or TikTok account are needed. Results are normalized into the default dataset, while OUTPUT and RUN_SUMMARY records in the default key-value store provide terminal run details for automation and agent workflows: COMPLETE, PARTIAL, VALID_EMPTY (no matching results), INVALID_INPUT, and an unsuccessful run status when every search target fails upstream. includeRawData stores the raw source payload alongside normalized rows.

Pricing

This actor uses Pay per event pricing with Apify platform usage included. The charged events are:

• apify-actor-start: charged once when the actor starts after input validation.
• search-result-scraped: charged for each TikTok search result row successfully saved to the dataset.

For example, if a run saves twenty-five result rows, the start event is charged once and the per-row event is charged twenty-five times. See the Pricing tab for current event prices.

Use with AI agents (MCP)

This Actor is available through Apify MCP as a tool for TikTok search discovery. The exact Actor identity is khadinakbar/tiktok-search-scraper.

Tool description: use it to search TikTok by keyword, top search, hashtag, or user query and return normalized dataset rows with videos, profiles, metrics, and metadata for downstream agent steps.

Search TikTok for "nike running" and return keyword videos plus creator profiles from the first page. Keep the result set focused, then surface the top candidate profiles for follow-up enrichment.

Output interpretation:

• Read dataset rows from the default dataset to inspect videos, top results, hashtags, or user profiles.
• Use runSummary for counts, routes used, and terminal status in agent pipelines.
• Use runOutput for machine-readable terminal outcome details, including useful result counts and PPE charge counts.

Provenance and scope:

• Rows are normalized into one dataset shape across videos, top results and profiles.
• Search scope follows the selected inputs: keyword, top, hashtag, user, or combined search routing.
• includeRawData can carry the raw source payload for debugging and custom parsing.

Pagination and cost guidance:

• maxResultsPerQuery controls how many normalized rows are saved per query or hashtag.
• maxPagesPerQuery limits result pages per target.
• Larger result targets increase per-row event counts and therefore total PPE usage.

Apify API example

import { ApifyClient } from "apify-client";

const client = new ApifyClient({
  token: process.env.APIFY_TOKEN,
});

const run = await client.actor("khadinakbar/tiktok-search-scraper").call({
  searchQueries: ["nike running"],
  searchType: "keyword",
  hashtags: ["running"],
  userQueries: ["nike"],
  region: "US",
  maxResultsPerQuery: 25,
  maxPagesPerQuery: 3,
  includeRawData: false,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Best results and outcome guidance

Choose the narrowest search input that matches the task. Use searchQueries for topic exploration, hashtags for tag-based discovery, and userQueries for creator lookup. When you need a broader sweep from one term, searchType: "all" combines keyword, top, and user search for each query. Use region when localization matters, and use sortBy, datePosted, and publishTime to shape the returned order where TikTok supports it. For larger workflows, start with a lower maxResultsPerQuery, review the returned profiles or videos, and then enrich the selected records.

Pick the right TikTok search Actor

This Actor is the mixed-discovery option: keyword videos, Top results, hashtag videos and creator profiles under one schema in one run. For a single surface, a focused Actor from the same developer is usually the better fit:

When you need	Use
Keyword or hashtag videos with minimum views, likes or duration filters	TikTok Video Search Scraper
Creator profiles only, for a keyword or brand search	TikTok User Search Scraper
A deep feed and analytics for one hashtag	TikTok Hashtag Scraper
Keyword videos, Top results and creators mixed in one dataset	This Actor

Builder's note

I designed one normalized record shape for video and user rows, with recordType distinguishing them and scrapedAt on every saved row, so mixed-surface runs stay easy to route in downstream automation.

FAQ

How should I route a keyword search versus a user search?

Use searchQueries with searchType: "keyword" when you want video results around a topic. Use userQueries when you want creator profiles returned as user rows.

When should I use searchType: "all"?

Use searchType: "all" when you want the same query to produce keyword videos, top results, and user profile matches in one run.

How do I move from discovery to enrichment?

After this Actor returns public profile URLs or IDs, send those records into TikTok Profile Posts Scraper - Creator Feed Data or TikTok Profile Videos Scraper for profile-focused follow-up.

How do I keep pagination focused?

Set maxPagesPerQuery to a small value for discovery runs, then increase it only for broader collection tasks. Pair it with maxResultsPerQuery to shape the final dataset size.

How do I inspect run details in automation?

Read the default dataset for result rows, then read RUN_SUMMARY and OUTPUT from the default key-value store for counts, routes used, and terminal outcome data.

Responsible use

Use the actor for lawful research, monitoring, and enrichment workflows that respect TikTok access rules and the rights of others. Review the returned public data in the context of your own compliance, privacy, and platform obligations before storing or acting on it.