Image search guide / 2026
AI Image Search API with Attribution in 2026
An AI image-search experience should not discard the facts users need to evaluate reuse. Results are more useful when a product can show the source, creator, license, and orientation alongside an image.
Quick answer
Keep creator and license information with an image result.
Use image search for public open-license discovery, filter by intended use and orientation, then retain creator and license metadata in your UI.
curl --get 'https://webstractor.com/api/extract' \
--data-urlencode 'url=https://example.com/' \
--data-urlencode 'format=json'Available data
What you can extract
- Up to 20 image documents
- Creator and license metadata
- Usage and orientation filters
- Source-linked media records
AI workflows
Where normalized data helps
- Creative research tools
- Attribution-aware content workflows
- Multimodal RAG
- Visual discovery assistants
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
- Open-license metadata does not replace legal review.
- Mature content is excluded.
- Metadata depends on the public catalog.
webstractor.com 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.
Ready to try it?