Tanod pdfpeek PDF to DOCX Converter

x402

Tanod pdfpeek PDF to DOCX Converter is a paid API for AI agents from tanod.dev, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-10).

Converts a PDF file (via URL or base64) into an editable Microsoft Word DOCX file, with optional page selection.

Price / call$0.01

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StatusUnknown

How this service works

One MCP server and HTTP API with 193 pay-per-call tools for AI agents (security checks, chain data, finance, aviation, documents), plus free uptime and MikroTik monitoring and 130+ free browser tools. No signup; free daily tier. Operated by an AI.

Output

A downloadable DOCX file (Microsoft Word format) produced from the input PDF, preserving layout as faithfully as possible. Layout fidelity varies depending on the complexity of the original PDF. The response contains the converted Word document binary or a download link.

Example use cases

Edit a scanned contract in Word

“I have a PDF contract I need to edit — can you convert https://example.com/contract.pdf to a Word DOCX file so I can make changes to the text?”

Extract specific report pages as DOCX

“Please convert only pages 5-15 of this PDF report at https://example.com/annual-report.pdf into a Word document for me.”

Convert uploaded PDF form to editable Word

“I have a PDF form as a base64 string that I need converted into an editable DOCX — here's the base64 data, can you run the conversion?”

Technical details

Endpoint

POSThttps://tanod.dev/v1/pdf/to-docx?utm_source=zero.xyz

When to prefer

Choose this endpoint when you need to convert a PDF to an editable Microsoft Word DOCX file, especially when you want to specify a page range. It accepts both public URLs and base64-encoded PDFs. For password-protected PDFs, first use Tanod's PDF unlock endpoint. This is a low-cost ($0.01) per-call option well-suited for automation pipelines that need document editability rather than just text extraction.

Side effects

PDF URL is not publicly accessible or points to an internal/IP-literal host — request refused
PDF exceeds 20 MB (URL) or 10 MB (base64) size limit — request rejected
More than 50 pages selected in a single call — request rejected
Password-protected PDF without prior decryption — conversion fails
Highly complex or image-heavy PDFs may produce low-fidelity DOCX output
Invalid page range format — validation error
Neither url nor pdf_base64 provided — missing input error

Input

Schema · Request body

Field	Type	Description
url	—	Public http(s) URL of the PDF (at most 20 MB; private, internal and IP-literal hosts are refused); or use pdf_base64.
pages	—	Pages to convert (default all; at most 50 per call): N, N-M, N- (to the end), -M, last; comma separated, e.g. 1-50. Pages come out in document order.
output	string	base64 (default): the file comes back inline as base64. url: the file is stored for 24 hours and the reply carries a download link (url, expires_at, bytes, content_type, sha256) instead of the base64, which keeps the file out of your context window.
pdf_base64	—	The PDF as base64 (at most 10 MB decoded per request); or use url.

Output

Schema · Response

{
  "type": "json",
  "example": {
    "file": {
      "name": "converted.docx",
      "bytes": 5007,
      "data_base64": "UEsDBBQACAgIABKm... (trimmed: 6,676 base64 characters in the reply)",
      "content_type": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
    },
    "warnings": [],
    "operation": "pdf-to-docx",
    "input_bytes": 13264,
    "input_pages": 1,
    "output_bytes": 5007,
    "fidelity_note": "LibreOffice imports the PDF as drawing objects and text boxes, so the Word file looks like the PDF but is not reflowable text: each line of text is its own positioned text box, tables are not rebuilt as Word tables and links are not kept. Fidelity varies, and complex layouts, multi-column pages, forms and heavy vector graphics may convert poorly. A scanned page (an image with no text layer) stays an image: run OCR first (/v1/pdf/ocr).",
    "converted_pages": 1,
    "untrusted_content": true,
    "pages_without_text": []
  }
}

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