Likee Scraper — Public Videos & Creator Profiles

Collect public Likee videos and creator profiles for creator research and social listening. This Likee scraper exports attributed metrics, captions and timestamps, with filters, bounded history and summaries of the videos actually scanned.

Quick start

1. Enter one or more public creator handles or profile URLs.
2. Choose videos, creator profiles or both. Set the scan depth and maximum saved rows.
3. Run the Actor, then open its dataset and the SUMMARY record.

{
  "profiles": ["Likee_Russia", "baby.miaa"],
  "resultType": "both",
  "maxVideosPerProfile": 50,
  "maxResults": 102
}

This recipe requests up to 50 videos per creator and allows space for two profile records. It is an input recipe, not a public saved-task link.

Prefer a video guide? This short Apify walkthrough shows you how to set up and run an Actor. It uses a different Actor, but the setup steps are the same.

What you get

• Attributed public video data: stable video and author IDs, captions, hashtags, mentions, publication dates and available view, like, comment and share counts.
• Creator profiles: public biography, avatar, follower/following counts and total likes where supplied by Likee.
• Comparable cohorts: sample sizes, medians, averages and optional creator-relative engagement scores over scanned videos, before filters.
• Repeatable watch lists: optional only-new output with history separated by normalized targets, output mode and filters.
• Explicit coverage: per-input outcomes, scan limits and unavailable reasons outside the dataset. Unknown values remain null.

Who is it for?

Creator research teams can compare public creator profiles and recent-video cohorts before building a shortlist. Social listening teams can refresh a known watch list and use the returned captions and metrics in their own reporting workflow.

Input settings

Settings	What they control
profiles, userIds	Public handles/profile URLs, or internal numeric author IDs supplied as strings. Internal-ID resolution needs a listing entry with a public author handle.
videos	Public share URLs, author/video URLs, or author/videoId references. A bare numeric video ID is insufficient.
resultType	videos, profiles or both. Individual video inputs require videos or both.
maxResults, maxVideosPerProfile	Maximum saved rows across the run, including profiles, and maximum scanned source entries per creator.
sorting	latest retains source recent-video order. popular ranks by views within the scanned cohort, not the creator's whole history.
minViews, minLikes, minComments, minShares, minEngagementRate	Video thresholds applied before saving and result charging. Engagement rate is (likes + comments + shares) / views × 100.
publishedAfter, publishedBefore	Inclusive UTC publication boundaries. A date alone means midnight, not the end of that day.
engagementScore	Adds video ratios against the same creator's scanned median reach and engagement. Standalone videos have no comparison cohort.
onlyNew	Returns matching videos not remembered in this watch-list scope. Requires video output. The first run establishes the baseline.

Individual video recipe: use {"videos":["https://likee.video/v/sepkYQ"],"resultType":"videos","maxResults":1}. An author/video reference is found by scanning that author's history up to maxVideosPerProfile. A requested ID not found before the limit remains an incomplete extraction, not proof of deletion.

Monitoring recipe: add "onlyNew": true to your creator watch-list input. Keep its normalized targets, filters and output mode unchanged to reuse the same history. No schedules are created by the Actor.

Invalid individual targets are skipped with field/index warnings while valid targets continue. An invalid overall mode or date range produces a correction warning without extraction. Check SUMMARY for a working input recipe.

Output data

Video and creator records share a dataset. Use recordType to distinguish them.

Record	Useful fields
Video identity	videoId, authorId, authorUsername, authorNickname, authorProfileUrl
Content	caption, hashtags, mentions, postedAt, scrapedAt
Metrics	playCount, likeCount, commentCount, shareCount, engagementRate
Available media	coverImageUrl, videoFileUrl, postUrl, shareUrl, music metadata and video dimensions
Creator profile	Public profile details and analytics describing the actual scanned video cohort
Provenance	sourceInput, explicit cohort sizes and completeness, optional metric precision and creator-relative ratios

Public listing responses often lack video file URLs and share links. Those fields remain null rather than being reconstructed from internal IDs. Share-page counters can be rounded and are labeled with metricPrecision. Time-window post counts remain null when scanned history does not cover the interval.

The SUMMARY key-value record reports per-input outcomes, saved row counts, filters, previously seen videos, skipped private entries and limits. Status and error messages are not dataset rows.

Download your results

Open your run's dataset, choose Export and select JSON, CSV or Excel. JSON keeps nested fields together. CSV and Excel are useful when you want to review the records in a spreadsheet.

See Apify's download and export guide for the available formats and field options.

Pricing

The Actor Start charge applies when a run starts, including empty runs and runs that return input warnings.

The result charge applies to each completed saved video or creator profile row. Profile rows count toward maxResults, including profiles with no matching videos. Excluded videos, previously seen videos and unavailable targets do not create paid result rows. Useful completed rows can still be charged when another input fails.

See the live Pricing tab for current rates and discounts.

Tips for best results

• Start with a small cohort. Confirm the creator identity and populated metrics before increasing scan depth.
• Leave room for profiles. In both mode, allow extra saved rows for creator summaries.
• Compare like-for-like samples. Use similar depths and date boundaries across creators. Popular ranking cannot see older videos outside that sample.
• Keep monitoring scope stable. Changes to targets, filters or output mode create a separate baseline. History retains the latest 10,000 emitted video IDs per scope, so evicted IDs can reappear.

Limits and caveats

• Anonymous public content only. No login, private content, contact enrichment, media downloads, full comment text or platform-wide search/hashtag discovery.
• Scan limits are not whole-account coverage. Creator analytics describe scanned public videos before filters, not every post on the account.
• Some share links redirect to an app or homepage without usable public video data. These remain extraction failures rather than invented empty results.
• Unavailable targets succeed with truthful reasons. Blocking, malformed source responses, incomplete required lookups and essential storage/billing failures remain failures. Useful completed rows are preserved.
• Null metrics do not satisfy numeric filters, even when the minimum is zero. Public-source changes can affect availability and field population.
• Only-new history is not a transactional exactly-once delivery guarantee. A failed run can leave accessible rows and incomplete history. Start a new run rather than resurrecting an interrupted run.

Automation and integrations

Save your settings for next time

Once you have an input that works for you, save it as an Apify task. This keeps your settings together so you can use them again without filling in the form from scratch.

Run on a schedule

Need fresh results regularly? You can schedule the Actor or a saved task in your own account. The Actor itself does not create or enable schedules.

Use only-new mode to retrieve newly observed matching videos. Comparing metrics across runs or sending alerts belongs to your own workflow.

Send results to your other tools

Use n8n, Make or Zapier to connect this scraper to the rest of your workflow. For example, you could pass its results to an AI assistant or add records to a spreadsheet. Follow the Apify integration guides for your chosen tool.

For a custom connection, an Apify webhook can notify your app when a run finishes or fails. Your app can then fetch the results or handle the failure.

API usage

Collect a bounded creator cohort from your app, then retrieve the dataset for analysis. The Node.js and Python clients wait for the run to finish. cURL starts a run and returns its details. Follow that run to completion, then fetch its defaultDatasetId.

See the official JavaScript client guide, Python client guide and Actor runs API reference.

cURL

curl -X POST 'https://api.apify.com/v2/acts/fetch_cat~likee-public-content-scraper/runs' \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H 'Content-Type: application/json' \
  -d '{"profiles":["Likee_Russia"],"maxVideosPerProfile":10,"maxResults":11}'

Node.js

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('fetch_cat/likee-public-content-scraper').call({
  profiles: ['Likee_Russia'], maxVideosPerProfile: 10, maxResults: 11,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Python

import os
from apify_client import ApifyClient
client = ApifyClient(os.environ['APIFY_TOKEN'])
run = client.actor('fetch_cat/likee-public-content-scraper').call(run_input={
    'profiles': ['Likee_Russia'], 'maxVideosPerProfile': 10, 'maxResults': 11,
})
print(client.dataset(run['defaultDatasetId']).list_items().items)

MCP and AI agents

You can ask your assistant to collect Likee data and help you work with it. The scraper retrieves public records. Your assistant can summarize them, compare creators or prepare a file afterward.

Connect through the Apify MCP server and configurator using the official setup and sign-in guide. The official Apify plugin can configure supported coding assistants. You can also use Apify AI in Console, which is currently in beta and asks for confirmation before starting an Actor.

Choose your assistant

• Claude and Claude Code: Apify setup guide.
• ChatGPT and Codex: Apify setup guides.
• Grok Bot: Apify plugin guide.
• Gemini CLI: MCP server setup.

Connect just this scraper

To keep your setup focused on this scraper, add this configuration to a compatible MCP client:

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com?tools=fetch_cat/likee-public-content-scraper"
    }
  }
}

Use OAuth when your client supports it, or its documented secure Bearer-token configuration. Never put a real token in a prompt or public example.

Use Apify's general server

Alternatively, connect to Apify's general server at https://mcp.apify.com and ask it to find fetch_cat/likee-public-content-scraper, inspect the schema and retrieve your chosen data. Both URLs use Apify's hosted service. Follow the returned run/dataset rather than starting duplicate runs. Check current Pricing before authorizing charges.

Example requests

• “Get recent public videos from Likee_Russia and make a spreadsheet of captions, dates and engagement counts.”
• “Collect 50 recent public videos each from Likee_Russia and baby.miaa, then compare their median views using those samples.”
• “Retrieve the public Likee video at this share link and summarize its caption, author and available engagement metrics.”

Pay with x402

A funded agent can use the official x402 setup to obtain a prepaid, spend-capped API token through Apify AGI, then use the API or a supported authenticated MCP connection.

Direct per-request MCP payment is a separate route with platform eligibility restrictions. It is not verified for this Actor. Use the documented prepaid-token flow when available, rather than assuming direct payment support.

Apify handles payments. Follow its current guide for setup and terms. Keep wallet keys and payment tokens out of prompts and public examples. The agentic payment guide also describes MPP and eligible Skyfire integrations.

FAQ

Can I use this as a Likee video data API?

Yes. Submit supported public targets through the Apify API and retrieve attributed video/profile records from the resulting dataset. It is not an official Likee API.

Does popular mean the most viewed videos on the whole account?

No. It ranks only the scanned recent-video cohort. Increase scan depth when appropriate and inspect completeness before drawing broader conclusions.

Can I get a Likee profile without collecting video rows?

Choose profiles. The Actor still scans a bounded video cohort for analytics, but saves only the creator record. Internal numeric IDs cannot resolve metadata from an empty listing.

Why can the dataset be empty?

Targets may be explicitly unavailable, filters may exclude the scanned videos, or only-new mode may have no unseen matches. Check SUMMARY. A saved creator profile can still be a result when video filters exclude every video.

Related Actors

• TikTok Profile Scraper — export public TikTok creator profiles and available recent-video metadata.
• X / Twitter Posts Scraper — retrieve public posts from profile and post URLs, with text, authors and engagement counts.
• Bilibili Video Search Scraper — search public Bilibili videos and export author, engagement and publication metadata.
• TikTok Sound Scraper — retrieve public TikTok videos using specific sounds, with creator and engagement metadata.
• Instagram AI Transcript Extractor — transcribe public Instagram Reels and videos into speech text and available timestamped segments.

Support and feedback

For custom additions or integrations, email hello@fetchcat.dev.

Found an error or have a feature request? Open an issue with the run URL, a non-sensitive input example and what you expected.

See Apify's guide to sharing runs in Actor issues. Sharing a run gives the developer access to its input, logs and default results, so use a run containing no sensitive data. Leave out API tokens, passwords, cookies, private documents and personal data. Use a public sample URL or a redacted example instead.

Tried this scraper? We'd love to hear how it worked for you. Leave a review to help others choose the right tool and help us improve it. Your feedback means a lot to us.

Made with care for curious people, AI agents and the possibilities in data. ♥