SiteCheck Structured Data Extractor

x402

SiteCheck Structured Data Extractor is a paid API for AI agents from api.sitecheck-api.workers.dev, paid per call via x402, $0.004/call, status unknown (last checked 2026-10-17).

Extracts structured, schema-defined fields from a web page URL or raw text using an LLM, returning typed values mapped to user-defined field names

Price / call$0.004

Seller volume →—

Success—

StatusUnknown

How this service works

Structured data from a web page (url) or your own text: give a schema of up to 20 field names with what each holds, and get a JSON object with exactly those fields, null where the text does not state one. Llama 3.3 70B. Text is capped at 12,000 characters; a model answer that is not JSON is retried once, then not charged.

Output

A JSON object containing a 'fields' map where each key is a user-defined field name and the value is the extracted content (or null if not found in the source), along with the model name used, a checkedAt timestamp, and a note reminding users to verify important values against the source.

Example use cases

Invoice data extraction pipeline

“Fetch this invoice page at https://billing.acme.com/invoices/INV-2026-0042 and extract the invoice number, total, currency, and due date as structured fields so I can log them to our accounting system.”

Job listing field parser

“Read the job posting at https://jobs.example.com/posting/senior-engineer and extract the job title, salary range, location, required years of experience, and application deadline into structured JSON fields.”

Unstructured text field extractor

“Here's a contract excerpt — can you pull out the party names, contract start date, termination notice period, and governing law from it? The text is: 'This agreement is entered into between Acme Corp and Widget LLC on January 1 2026, with a 30-day termination notice, governed by New York law.'”

Technical details

Endpoint

POSThttps://api.sitecheck-api.workers.dev/api/extract?utm_source=zero.xyz

When to prefer

Use this endpoint when you need to extract specific, named fields from an arbitrary web page or text blob into a structured JSON object, especially when the source is unstructured or semi-structured. Ideal for invoice parsing, document field extraction, lead enrichment from web pages, or any task where you define a schema and want the LLM to fill it from a given source. Prefer this over generic web scrapers when you need typed, schema-aligned output rather than raw HTML or Markdown.

Side effects

URL is unreachable or returns non-200 status — extraction fails with no content
Text exceeds 12,000 character limit — truncation or rejection
Schema has more than 20 fields — excess fields may be ignored
LLM cannot find a field value — returns null for that field
Ambiguous or conflicting values in source — LLM may pick the wrong one
Paywalled or login-protected page — content unavailable for extraction
Non-text content (e.g. images, PDFs without text layer) — no extractable text

Input

Schema · Request body

Field	Type	Description
url	string	Web page to read (or text)
text	string	Text to read (up to 12,000 characters), instead of url
schema	object	Field name to what the field holds, up to 20 fields
instructions	string	Optional extra instructions, up to 500 characters

Output

Schema · Response

{
  "type": "json",
  "example": {
    "note": "Values come from the text only; a null means the text does not state it. Check important values against the source.",
    "model": "@cf/meta/llama-3.3-70b-instruct-fp8-fast",
    "fields": {
      "total": 1250,
      "currency": "EUR",
      "due_date": "2026-10-31",
      "invoice_number": "INV-2026-0042"
    },
    "checkedAt": "2026-10-14T05:12:24.660Z"
  }
}

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