Agent data guide / 2026

One Web Data API for AI Agents in 2026

Agents often need both retrieval modes: open a known source and discover sources for an unanswered query. A compact API surface keeps these operations consistent without turning the integration into a crawling or browser-automation project.

Quick answer

Use one API for extraction and focused search.

Give an AI agent a small set of GET tools for public URL extraction plus web, news, image, and place search. All endpoints can return Markdown or schema-v1 JSON and share the same account, limits, and credit model.

curl --get 'https://extractor.sh/api/extract' \
  --data-urlencode 'url=https://example.com/' \
  --data-urlencode 'format=json'

Available data

What you can extract

Public webpage extraction
Web and news search results
Image results with attribution metadata
Place results with coordinates and address fields

AI workflows

Where normalized data helps

General research agents
RAG source discovery and ingestion
Multimodal research tools
Tool-using 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

The service does not crawl entire sites or execute arbitrary browser workflows.
All requests must target public information.
Endpoint-specific result limits and attribution requirements still apply.

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.