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Mastodon extraction / 2026

How to scrape data from Mastodon in 2026

Mastodon is distributed across many independently operated instances, but compatible public status pages share a common structure. Normalization gives AI systems one predictable document shape without requiring instance-specific client code.

Quick answer

Use the public page URL you already have.

Send the ordinary public Mastodon 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://mastodon.social/@trwnh/99664077509711321' \
  --data-urlencode 'format=json'

Available data

What you can extract

  • Public status text and canonical link
  • Display name and federated account handle
  • Publication timestamp and content warning
  • Media descriptions supplied by the author

AI workflows

Where normalized data helps

  • Federated social research
  • Public-interest monitoring
  • Source-linked RAG collections
  • Cross-network AI analysis

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, followers-only, deleted, and unavailable statuses are not accessible.
  • Timelines, complete threads, replies, and media downloads are not included.
  • Instances must expose compatible public endpoints.

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.