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x402.shizu.me PDF Text Extractor
x402
x402.shizu.me PDF Text Extractor is a paid API for AI agents from x402.shizu.me, paid per call via x402, $0.005/call, status unknown (last checked 2026-10-01).
Fetches a public PDF by URL and returns its extracted text content as structured JSON with page count and word count
Price / call$0.005
Success—
StatusUnknown
How this service works
Fetch a PDF by URL and extract its text as JSON. Input: url (public http/https pointing to a PDF). Returns {url, pages, word_count, text}. Bounded to the first 50 pages; 3 MB max.
Output
Returns a JSON object with the original URL, number of pages processed (up to 50), total word count, and the full extracted text from the PDF
Example use cases
Example prompt
“Can you pull the text out of this PDF for me — https://example.com/report.pdf — I want to read its contents?”
Technical details
Endpoint
GEThttps://x402.shizu.me/pdf?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need to extract raw text from a publicly accessible PDF file given only its URL, especially when feeding PDF content into an LLM pipeline. Ideal for single-document extraction under 3 MB and 50 pages where you need structured JSON output including page and word counts.
Side effects
- URL is not a valid public HTTP/HTTPS address — returns error
- PDF exceeds 3 MB file size limit — returns error or truncated result
- PDF has more than 50 pages — only first 50 pages are processed
- URL does not point to a PDF file — parsing fails
- PDF is password-protected or encrypted — text extraction fails
- Network timeout fetching the remote PDF — returns error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| input | object |
Output
Schema · Response
{
"type": "json",
"example": {
"url": "https://example.com/file.pdf",
"text": "Extracted text content of the PDF...",
"pages": 3,
"word_count": 412
}
}Tags
x402
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