Tanod Docs PDF Pipeline is a paid API for AI agents from docs.tanod.dev, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-13).
Runs a multi-step PDF processing pipeline (rotate, crop, resize, extract pages, set outlines, flatten, repair, inspect, etc.) on a PDF supplied by URL or base64.
Documents: DOCX template fill, Office to PDF, any file to Markdown, PDF to Word, OCR, PDF pipeline.
Returns a JSON object containing the processed PDF (inline as base64 or as a 24-hour download URL with metadata), plus a per-step report including op name, step number, output bytes, page count, and any active content removed. Also includes totals for input pages, input bytes, output bytes, and number of steps run.
POSThttps://docs.tanod.dev/v1/pdf/pipeline?utm_source=zero.xyzChoose this endpoint when you need to chain multiple PDF operations (up to 10) in a single API call rather than making separate requests for each transformation. It is ideal for workflows like extract-then-resize-then-bookmark or repair-then-flatten. Prefer this over single-operation PDF endpoints when the task has two or more sequential steps, or when you want a unified step-by-step audit report of all operations applied.
| 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. |
| steps | array | The operations to run in order, 1 to 10 of {op, params}: the output of each is the input of the next. inspect and outline return a report and can only be last. The whole call has one 70 s time budget. |
| 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. |
{
"type": "json",
"example": {
"file": {
"name": "bookmarked.pdf",
"bytes": 53412,
"pages": 3,
"data_base64": "JVBERi0xLjcKJb/3... (trimmed: 71,216 base64 characters in the reply)",
"content_type": "application/pdf"
},
"steps": [
{
"op": "extract-pages",
"step": 1,
"pages": 3,
"output_bytes": 52010,
"active_content_removed": {}
},
{
"op": "resize",
"mode": "fit",
"size": "a4",
"step": 2,
"pages": 3,
"output_bytes": 52960,
"resized_pages": 3,
"sizes_truncated": false,
"active_content_removed": {}
},
{
"op": "set-outline",
"step": 3,
"pages": 3,
"replaced": false,
"output_bytes": 53412,
"outline_depth": 1,
"outline_items": 1,
"active_content_removed": {}
}
],
"operation": "pipeline",
"steps_run": 3,
"input_bytes": 140815,
"input_pages": 6,
"output_bytes": 53412,
"untrusted_content": true,
"active_content_removed": {}
}
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