YouTube extraction / 2026
How to scrape data from YouTube in 2026
YouTube pages provide valuable public metadata even when a workflow does not need the media itself. Normalized video and channel results make titles, descriptions, authors, dates, and links easier to index and combine with other sources.
Quick answer
Use the public page URL you already have.
Send the ordinary public YouTube URL to extractor.sh. Choose JSON for stable fields or Markdown when an AI model will read the result directly. The API uses GET, so an identical successful request can be served from Cloudflare’s edge cache.
curl --get 'https://extractor.sh/api/extract' \
--data-urlencode 'url=https://www.youtube.com/@Cloudflare' \
--data-urlencode 'format=json'Available data
What you can extract
- Public video titles and descriptions
- Channel and playlist feeds
- Author, publication date, and canonical URL
- Normalized Markdown or JSON metadata
AI workflows
Where normalized data helps
- Video discovery agents
- AI research indexes
- Metadata-based topic classification
- Source catalogs for multimodal pipelines
AI-ready output
Markdown for models. JSON for systems.
Raw HTML consumes tokens on navigation, scripts, styling, and interface labels. Clean Markdown keeps the readable hierarchy for LLM prompts and RAG chunks. Normalized JSON is better when your application needs an explicit semantic type, source, author, publication date, media, attributes, and collection items.
Always retain the canonical URL from the response. AI-generated summaries should remain traceable to the public source, especially when the underlying page can change.
Boundaries
Public data only
- Private, removed, member-only, and age-gated content is unavailable.
- Transcripts, captions, spoken content, and media downloads are not included.
- Results describe public videos; they do not analyze the audiovisual content.
extractor.sh does not bypass CAPTCHAs, login walls, paywalls, access controls, or regional restrictions. Review the source’s terms and applicable law before collecting or reusing data.