Send us a URL. We return clean, validated schema.org JSON‑LD — not raw HTML, not noisy markdown. Machine-readable facts your AI agent can use immediately. 200+ entity types identified and extracted.
Choose published markup with a low-information warning when needed, a complete page-level entity, or Product verification with field evidence.
Automatically detects the entity type on any page — Restaurant, Product, Event, Person, Article, MedicalCondition, SoftwareApplication, and 200+ more schema.org types.
Every response is specification-compliant JSON-LD with proper @context, @type, and validated property names. Drop it directly into your knowledge graph or downstream pipeline.
Check Product fields against multiple page representations. Receive field-level evidence, contradictions, observation time, and a clear verdict.
Instead of feeding your AI agent 50KB of raw HTML, we deliver a compact JSON object with only the facts that matter. Save tokens, reduce latency, increase accuracy.
Every extraction includes a confidence rating — high, medium, or low — based on extraction source and data quality. Know exactly how much to trust the intel.
Free difficulty check before paying. Know the expected schema type, scraping difficulty, and known blockers for any URL before committing funds.
Choose the response that fits the task: existing Schema.org data, a complete page-level entity, or Product verification with evidence.
Bypass generic page types and drill down into rich organizational entities. We reliably extract nested contact details, founding data, geolocation, and hierarchies straight into clean JSON representations.
Returns concise patent facts including identifiers, inventors, assignees, filing dates, citations, related records, and document links when published on the page.
Returns concise scholarly facts including authors, affiliations, DOI, publication hierarchy, document links, references, and keywords when published on the page.
Pass suggest: true in an API or MCP request to receive a recommended page-level Schema.org type and ready-to-use JSON-LD when existing markup is sparse.
A simple request-to-result flow designed for agent automation.
The public URL is checked for safety and reachability before paid work begins.
Relevant page facts are collected while keeping the response compact and task-focused.
Existing JSON-LD analyzed. If insufficient, AI identifies entity types and extracts structured facts.
Concise Schema.org JSON-LD is returned with confidence or Product verification evidence.
JSON Recon is accessible via the x402 payment protocol — the open standard for machine-to-machine payments over HTTP. AI agents discover our service at /.well-known/x402 and pay per-request using cryptocurrency on Base. No API keys, no subscriptions, no human sign-up required. Our endpoints are also listed in the x402 Bazaar, the protocol's machine-readable service catalog for automated discovery.