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Quant Agent Shop PDF Text Extractor
x402
Quant Agent Shop PDF Text Extractor is a paid API for AI agents from quantagentshop.com, paid per call via x402, $0.002/call, status unknown (last checked 2026-10-23).
Extracts plain text content from a PDF (by URL or base64), returning per-page text, page count, title, and a truncation flag — no OCR, encrypted PDFs refused.
Price / call$0.002
Success—
StatusUnknown
How this service works
PDF text. Send a public PDF URL or the file as base64 (up to 10 MB); returns the plain text of each page, the page count, the title and a truncated flag (first 200 pages and 2,000,000 characters). Use to read reports, papers, filings or invoices. No OCR: scanned pages come back empty (send page images to /v1/ocr); encrypted PDFs are refused. Typical response 1 to 5 s. Failed calls are not charged.
Output
Returns a JSON object containing an array of plain-text strings (one per page, up to 200 pages), the total page count, the document title if detectable, and a boolean truncated flag indicating whether the document was cut off at the 200-page or 2,000,000-character limit. Scanned pages with no embedded text return empty strings. Response typically arrives in 1–5 seconds.
Example use cases
Research paper content extraction
“Grab the full text from this arXiv paper PDF at https://arxiv.org/pdf/2312.12345 — I need the text of every page so I can summarize the methodology section.”
Financial filing analysis
“Pull the plain text out of this SEC 10-K filing PDF at https://example.com/filing.pdf so I can search it for revenue figures and risk factors.”
Invoice data retrieval
“Here's a PDF invoice encoded in base64 — can you extract all the text from it so I can pull out the line items and total amount?”
Technical details
Endpoint
POSThttps://quantagentshop.com/v1/pdf-text?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need machine-readable text from a digital (non-scanned) PDF — reports, academic papers, SEC filings, invoices, or contracts — accessible via a public URL or encodable as base64 under 10 MB. If the PDF is scanned/image-based, use the OCR endpoint instead. Prefer this over a full webpage-to-PDF pipeline when you already have the PDF URL directly.
Side effects
- Encrypted or password-protected PDFs are rejected with an error
- Scanned/image-only PDFs return empty strings per page (no OCR performed)
- Files exceeding 10 MB are refused
- Malformed or non-PDF URLs return an error
- Inaccessible URLs (404, auth-gated) cause a failure — failed calls are not charged
- Documents over 200 pages or 2,000,000 characters are truncated with truncated=true
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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