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402utils PDF Text Extractor
x402
402utils PDF Text Extractor is a paid API for AI agents from 402utils.com, paid per call via x402, $0.005/call, status unknown (last checked 2026-09-13).
Extracts full text, per-page text, and metadata from a PDF file (text layer only, no OCR), accepting either raw PDF bytes or a public URL.
Price / call$0.005
Success—
StatusUnknown
How this service works
Extract text from a PDF: send the PDF bytes directly, or a JSON body with a public {url}. Returns the full text, per-page text, and metadata (page count, title, author). Text layer only — scanned/image-only PDFs return empty text with a no_text_layer warning (no OCR). Max 10 MB.
Output
Returns the complete extracted text from the PDF, an array of per-page text strings, and metadata including page count, document title, and author. If the PDF has no text layer (e.g. scanned images), returns empty text with a no_text_layer warning. Max supported file size is 10 MB.
Example use cases
Aggregate contract clauses from PDF agreements
“I have a bunch of vendor contracts in PDF format that I need to review. Can you extract all the text from each one and break down what's on each page? I also need to know who authored each document if that info is available.”
Index research papers for content discovery
“I'm trying to build a searchable index of academic papers. Can you pull the text from this research PDF and tell me how many pages it has? I'd like the full text plus a breakdown of what's on each page so I can organize the content properly.”
Audit scanned documents for compliance
“We need to process some PDF reports from our suppliers to check for compliance issues. Can you extract all the readable text from this PDF file and give me the page count and document title? I need to make sure the text layer is actually readable before we spend time reviewing it.”
Technical details
Endpoint
POSThttps://402utils.com/v1/pdf-extractWhen to prefer
Use this endpoint when you need to extract the text layer from a PDF document — either by uploading the raw bytes or providing a public URL. Best for text-based PDFs (not scanned images). Prefer this over general document converters when you specifically need per-page text breakdown and PDF metadata (title, author, page count) in a single call.
Side effects
- Scanned or image-only PDF returns empty text with a no_text_layer warning — OCR is not performed
- PDF exceeds 10 MB size limit — request is rejected
- Invalid or inaccessible public URL returns a fetch/network error
- Malformed PDF bytes result in a parsing error
- Password-protected PDFs may fail to parse
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| url | string | Public http(s) URL of a PDF (alternative to sending bytes). |
Output
Schema · Response
{
"type": "json",
"example": {
"meta": {
"title": "Invoice",
"pageCount": 1
},
"text": "Invoice #1042 …",
"pages": [
{
"page": 1,
"text": "Invoice #1042 …"
}
]
}
}Tags
x402
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