AI search guide / 2026
AI Web Search API for Agents in 2026
AI search works best when it returns a small, ordered set of public sources rather than a provider-specific browser page. Preserve result URLs, then read only the sources needed for the next reasoning step.
Quick answer
Give agents ordered, source-linked web results.
Use web search when an agent needs to discover public sources before it reads them. The response is a bounded schema-v1 feed with titles, URLs, snippets, locale controls, and optional site restriction.
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 10 ordered public results
- Titles, URLs, and short snippets
- Language, country, and hostname controls
- Markdown or schema-v1 JSON output
AI workflows
Where normalized data helps
- Research assistants
- Grounded answer generation
- Source discovery before RAG ingestion
- Documentation agents
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
- Search snippets are discovery metadata, not a substitute for reading a source.
- Safe search is always strict.
- Pagination and personalized results are not provided.
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?