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Vextorium PDF Metadata Extractor
x402
Vextorium PDF Metadata Extractor is a paid API for AI agents from api.vextorium.com, paid per call via x402, $0.004/call, status unknown (last checked 2026-10-28).
Extracts metadata from a PDF file via URL, returning title, author, page count, creation date, encryption status, table of contents index, and text extractability flags.
Price / call$0.004
Success—
StatusUnknown
How this service works
244 pay-per-call data APIs for AI agents: official statistics and economy (ECB, Fed, Eurostat, World Bank, SEC, BOE, INE), crypto prices and sentiment, Spanish public data, compliance (sanctions, VAT, IBAN, LEI), science, weather, web and developer tools and local AI text tools. Pay in USDC via x402.
Output
A JSON object containing: title (string or null), author, created timestamp, modified timestamp, PDF version, producer software, creator software, file size in bytes, page count, page size in points, whether the document is encrypted, whether it contains form fields, whether text is extractable, a list of table of contents entries (with page, level, and title), a list of attachments, and an optional note (e.g. flagging that a scan lacks a text layer).
Example use cases
Pre-processing PDF ingestion pipeline
“Before I run OCR on this document, check https://example.com/scan.pdf and tell me if it already has extractable text or if it's just a scanned image without a text layer.”
Document provenance audit
“I need to verify who created this contract and when — can you fetch the metadata from https://example.com/contract.pdf and give me the author, creation date, and PDF producer software?”
PDF library indexing
“I'm cataloguing a collection of PDFs — for https://example.com/thesis.pdf, get me the title, number of pages, page size, table of contents entries, and whether it's encrypted.”
Technical details
Endpoint
POSThttps://api.vextorium.com/v1/pdf-metadata?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need lightweight, structured metadata about a PDF (author, pages, dates, text extractability) without downloading and parsing the file yourself. It is especially useful as a pre-processing step before OCR or text extraction pipelines, for document auditing, or for cataloguing PDF libraries. It does not extract the text content itself — use a different endpoint for full text extraction.
Side effects
- URL is unreachable or returns a non-200 response — API may return an error or empty result
- URL does not point to a valid PDF — parsing will fail
- PDF is password-protected and unreadable — encrypted flag may be set but metadata may be unavailable
- Very large PDFs may time out or return incomplete metadata
- Malformed or corrupted PDF files may yield null fields across most metadata
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| url | string |
Output
Schema · Response
{
"type": "json",
"example": {
"form": false,
"note": "Looks like a scan without a text layer (it would need OCR).",
"bytes": 13264,
"index": [
{
"page": 1,
"level": 0,
"title": "Dummy PDF file"
}
],
"pages": 1,
"title": null,
"author": "Evangelos Vlachogiannis",
"created": "20070223175637",
"creator": "Writer",
"subject": null,
"version": "1.4",
"modified": null,
"producer": "OpenOffice.org 2.1",
"encrypted": false,
"attachments": [],
"page_size_pt": [
595,
842
],
"extractable_text": false
}
}Tags
x402
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