MCP guide / 2026
Useful MCP Tools for AI Agents in 2026
Tool-using agents need reliable boundaries. Separate discovery from reading, make format choices explicit, and return source-linked results that a client can render or a model can summarize.
Quick answer
Expose narrow tools that map to clear retrieval decisions.
extractor.sh exposes extraction, search, news, images, videos, places, stock search, market movers, and market data through one hosted MCP server.
curl --get 'https://extractor.sh/api/extract' \
--data-urlencode 'url=https://example.com/' \
--data-urlencode 'format=json'Available data
What you can extract
- Known-URL extraction
- Web, news, image, video, and place discovery
- Stock symbol and market-mover tools
- Chart-ready market data
AI workflows
Where normalized data helps
- Coding assistants
- Desktop AI clients
- Research copilots
- Tool-based chat interfaces
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 hosted server is stateless.
- Tools share normal cache and rate limits.
- MCP does not grant access to private pages.
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.