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Structured Extractor
x402
Structured Extractor is a paid API for AI agents from grim-foundry-pilot.onrender.com, paid per call via x402, $0.02/call, status unknown (last checked 2026-09-13).
Extracts structured JSON data from a webpage URL or raw HTML according to a caller-supplied JSON schema, with validation
Price / call$0.02
Success—
StatusUnknown
How this service works
Four JSON APIs for agents. Paid operations use x402 v2 HTTP payment, not API-key authentication. Read the current PAYMENT-REQUIRED offer before paying.
Output
Returns a JSON object containing: ok (boolean success flag), data (the extracted fields matching the provided schema), valid (boolean indicating schema validation passed), source_url (the URL fetched or null if HTML was provided directly), extraction_mode (e.g. 'deterministic-v0.1'), and validation_errors (array of any schema mismatch messages). Also includes a service identifier and a UUID request_id for tracing.
Example use cases
Product catalog data extraction
“Grab the product name, price, and availability from https://store.example.com/item/456 and return them as validated JSON with this schema: {name: string, price: number, inStock: boolean}.”
Article metadata harvesting
“Pull the title, author, publish date, and summary from this article URL https://news.example.com/article/789 and structure it as {title: string, author: string, publishedAt: string, summary: string} — tell me if anything fails validation.”
Raw HTML field extraction
“I have some raw HTML from a job listing — extract the job title, company name, location, and salary range from it using this schema: {jobTitle: string, company: string, location: string, salaryRange: string}.”
Technical details
Endpoint
POSThttps://grim-foundry-pilot.onrender.com/v1/structured-extractorWhen to prefer
Use this endpoint when you need to extract specific, schema-defined fields from a public webpage or raw HTML and want built-in schema validation to confirm the output is well-formed. It is best for deterministic field extraction where you know the shape of data you want, rather than open-ended summarization or AI-generated content. Prefer it over general LLM extraction when reproducibility and validation errors matter, and when you want to pay per-call with x402 rather than manage API keys.
Side effects
- URL is unreachable or returns non-200 — extraction fails with ok:false
- HTML is malformed or too sparse to extract required fields — validation_errors populated
- Provided schema is invalid JSON Schema — request rejected or returns empty data
- Page requires JavaScript rendering (no browser execution) — incomplete extraction
- Rate limiting or payment failure via x402 — request not processed
- Schema fields not present in source content — valid:false with validation_errors
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| url | string | |
| html | string | |
| schema | object |
Output
Schema · Response
{
"type": "json",
"example": {
"ok": true,
"data": {
"data": {
"title": "Demo"
},
"valid": true,
"source_url": null,
"extraction_mode": "deterministic-v0.1",
"validation_errors": []
},
"service": "structured_extractor",
"request_id": "00000000-0000-4000-8000-000000000000"
}
}Tags
x402
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