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Agent Tools Document Extract
x402
Agent Tools Document Extract is a paid API for AI agents from agent-tools.jbarkules.workers.dev, paid per call via x402, $0.006/call, status unknown (last checked 2026-10-28).
Extracts full text and structured fields (dates, amounts, invoice numbers, tables, contacts) from a PDF or image URL using OCR where needed
Price / call$0.006
Success—
StatusUnknown
How this service works
One call document parsing for invoices, receipts, statements, forms and scanned pages: PDF or image URL in, full text plus extracted fields out (dates, money amounts, totals/tax/amount due, invoice or order numbers, key: value pairs, emails, phones, URLs, simple tables). Images and scans use OCR.
Output
Returns full extracted text from the document along with structured fields: dates, monetary amounts (subtotal, tax, total, amount due), invoice or order numbers, email addresses, phone numbers, URLs, simple tables, and arbitrary key-value pairs detected in the document. Scanned images and image-based PDFs are processed through OCR first.
Example use cases
Automated invoice ingestion pipeline
“I have an invoice PDF at https://storage.example.com/invoices/inv-9871.pdf — can you extract the invoice number, vendor name, line items, tax, and total amount due so I can log it in our accounting system?”
Receipt data capture for expense report
“Here's a photo of my receipt from dinner: https://photos.example.com/receipt-jul12.jpg — please pull out the date, merchant name, subtotal, tax, and total so I can submit my expense report.”
Scanned form field extraction
“I've got a scanned intake form at https://docs.example.com/patient-form-scan.pdf — extract all the filled-in fields as key-value pairs, including any dates, phone numbers, and email addresses on the form.”
Technical details
Endpoint
GEThttps://agent-tools.jbarkules.workers.dev/v1/document/extract?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need to extract structured data from a document at a URL — especially invoices, receipts, statements, or scanned forms — in a single API call without managing OCR pipelines separately. Prefer this over raw PDF-to-text endpoints when you need structured fields (amounts, dates, invoice numbers) automatically identified, not just raw text. Choose over upload-based endpoints when you already have a public URL for the document.
Side effects
- URL is not publicly accessible (returns error or empty result)
- PDF is password-protected or encrypted (cannot extract text)
- Image quality too low for reliable OCR (partial or garbled text returned)
- URL points to an unsupported file type (error response)
- Document has no machine-readable or recognizable text (empty extraction)
- Network timeout fetching large documents
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"kind": "pdf",
"text": "INVOICE\nInvoice #: INV-1042\nDate: 2026-10-01\nTotal: $1,250.00",
"pages": 1,
"fields": {
"urls": [],
"dates": [
"2026-10-01"
],
"emails": [],
"phones": [],
"tables": [],
"totals": [
{
"label": "total",
"value": "$1,250.00"
}
],
"amounts": [
"$1,250.00"
],
"key_values": {
"Date": "2026-10-01",
"Invoice": "INV-1042"
},
"identifiers": [
"Invoice #: INV-1042"
]
},
"characters": 1840
}
}Tags
x402
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