YouTube Video Chapter Timestamp Extractor

Extract only explicit chapter and timestamp lines from public YouTube video descriptions. Built for podcast teams, educators, researchers, editors, and RAG pipeline builders.

Buyer question

Which explicit chapter timestamps can I reuse in editing, education, or RAG workflows?

Start in 30 seconds

{
  "videoUrlsOrIds": [
    "jNQXAC9IVRw"
  ],
  "maxResults": 1
}

Open the workflow-specific starter Task, run the bounded example, inspect the Dataset and free RUN_SUMMARY, then replace the sample videos.

Choose this Actor when

Choose this Actor for a repeatable video with at least one directly extracted chapter or timestamp workflow. Use a broad metadata scraper when you only need raw fields; use this specialist when the evidence rule and billing boundary matter.

First run checklist

1. Keep maxResults at 1 and run the included public example.
2. Inspect the evidence fields and compare Dataset rows with RUN_SUMMARY.
3. Confirm the result matches the public video description or player metadata.
4. Save a Task, schedule, webhook, or API workflow only after the sample is useful.

Evidence and billing

Only timestamp lines explicitly present in the public description are extracted. Missing chapters produce no paid row.

Launch PPE price: $12.00 per 1,000 video with at least one directly extracted chapter or timestamps, or $1.20 for 100. Diagnostics, duplicates, incomplete fetches, baselines, unchanged checks, empty classifications, and unsupported inferences are never billed.

Extract only timestamps explicitly present in public metadata. Do not invent chapter titles or summarize unavailable video content.

Output schema

Billable Dataset fields: videoId, videoUrl, title, durationSeconds, chapters, chapterCount, sourceDescription, evidenceDirect, scrapedAt. The separate RUN_SUMMARY reports videos requested, videos observed, rows saved, free exclusions, and monitor state. Error-only or placeholder rows never enter the Dataset.

Source boundaries

The Actor uses public YouTube video player metadata without login, cookies, a browser, or a residential proxy. Cloud runs use Apify's rotating datacenter proxy because YouTube can require sign-in from shared Actor IPs. It does not return captions, transcripts, subtitles, comments, search results, channel feeds, private videos, members-only content, or age-gated content.

Automation and AI agents

Use Apify Tasks, schedules, API, webhooks, ChatGPT, Claude, Neuton Actors MCP, n8n, Make, Zapier, a warehouse, RAG pipeline, or agent workflow.

Hosted Apify MCP endpoint: https://mcp.apify.com/?tools=neuton/youtube-video-chapter-timestamp-extractor

Explore the YouTube data family

• YouTube Video Metadata Scraper for complete raw public video fields
• YouTube Description Links Intelligence for all explicit outbound links
• Neuton Actors MCP for AI-agent workflows

SEO keywords

YouTube scraper, YouTube metadata API, YouTube Shorts scraper, YouTube sponsor links, YouTube chapters extractor, YouTube video monitor, creator intelligence, Apify YouTube Actor.

Responsible use

Use public metadata for legitimate creator, media, marketing, research, education, and automation workflows. Do not bypass access controls, collect private content, misrepresent sponsorship evidence, or make unsupported audience claims. Review YouTube's current terms and applicable privacy, advertising, and copyright rules before production use.