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PDF to Text: Extract Text and Metadata from PDF URLs

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Extract the text and metadata (title, author, dates, page count) from PDFs at any URL: reports, filings, papers, manuals, invoices. Whole-document text or text per page, ready for search, AI and RAG. Pay per page, failures free.

Pricing

Pay per event

Rating

0.0

(0)

Developer

Dodge Sucharda

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Total users

Monthly active users

22 days ago

Last modified

Output (one row per PDF; real result from 30 Sep 2026, text shortened)

{
  "url": "https://arxiv.org/pdf/1706.03762",
  "status": "ok",
  "bytes": 2215244,
  "pageCount": 15,
  "pagesRead": 3,
  "title": null,
  "author": null,
  "creator": "LaTeX with hyperref",
  "producer": "pdfTeX-1.40.25",
  "createdAt": "2024-04-10T21:11:43.000Z",
  "text": "Provided proper attribution is provided, Google hereby grants permission to\nreproduce the tables and figures in this paper solely for use in journalistic or\nscholarly works.\nAttention Is All You Need\n..."
}

That run used "Maximum pages per PDF" = 3, so 3 pages were read and charged. Many PDFs, like this one, leave title and author empty in their metadata.

Input

PDF URLs: direct links to PDF files, up to 60 MB each.
Also return text per page: adds pageTexts, an array with one string per page.
Maximum pages per PDF: default 500. You're charged for the pages actually read.
Respect robots.txt: on by default.

Limits

No OCR. Scanned PDFs made of images have no text layer; they return no_text_layer and are free.
Password-protected PDFs return password_protected (free).
Text comes out in the PDF's reading order. Complex multi-column layouts and tables may come out in an awkward order.
The PDF must be reachable by a direct link. Files behind a login are not supported.

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