Any URL to Markdown: Web Pages, PDF, Word and Excel for LLMs

What it does

AI agents and RAG pipelines keep running into links they cannot read directly: a PDF report, a linked spreadsheet, a slide deck, an article page full of navigation. Each format usually means another library. Any URL to Markdown works out what the link actually is and routes it to the right converter, so your code only ever handles Markdown.

It handles web pages (main content kept with Mozilla Readability, robots.txt respected), PDFs (text layer read with heading and paragraph detection), Word, Excel and PowerPoint, OpenDocument, EPUB, CSV and JSON. Images and PDF pages without a text layer go through Tesseract OCR in 7 languages. Headings, lists, tables and links are kept, and every result includes a title, metadata, the route used and a tokenEstimate.

Pricing follows what was converted: $1 per 1,000 web pages, $2 per 1,000 documents (a PDF counts once per started 50 text pages) and $3 per 1,000 OCR pages. Failed downloads, unsupported files, robots-blocked pages and empty results are not charged. It fits MCP clients, LangChain or LlamaIndex pipelines, Clay enrichments and n8n, Make or Zapier flows.

How it works

1. You pass a single url, or a list in urls (up to 1,000 per run, duplicates removed).
2. The actor checks robots.txt (on by default), downloads the link and detects its real format rather than trusting the file extension.
3. It routes the file to a converter: Readability for HTML, a layout-aware PDF text reader, Office and EPUB converters, or Tesseract OCR for images and scanned pages when ocr is on.
4. The result is one row per URL with markdown, title, detectedFormat, route, tokenEstimate and metadata such as author, dates and page count.
5. Limits such as maxPdfPages, maxOcrPages and maxRowsPerSheet keep large files in check, and truncated results are flagged.

Input example

A typical run input (JSON). Every field is also available as a form in the Apify console.

{
  "url": "https://arxiv.org/pdf/1706.03762",
  "urls": [
    "https://en.wikipedia.org/wiki/Retrieval-augmented_generation",
    "https://calibre-ebook.com/downloads/demos/demo.docx"
  ],
  "onlyMainContent": true,
  "ocr": true,
  "ocrLanguages": [
    "eng"
  ],
  "maxPdfPages": 500,
  "respectRobotsTxt": true
}

Output example

The sample shows a PDF, a Wikipedia article, a Word file, a spreadsheet and an image, each converted to Markdown with the route and token estimate.

Pricing

Pay per event: you are charged only for the results you receive, with no subscription. Set a maximum total charge on any run and it stops cleanly at the cap.

Prices are read from the live Apify Store listing when this page is built. The listing is always authoritative.

Use cases

How it compares

If your sources are JavaScript-heavy apps or sit behind a login, a browser-based crawler is the better choice. For mixed links to documents and ordinary pages, one converter is simpler than maintaining a scraper, a PDF parser, an Office converter and an OCR engine.

Limits and honest notes

• Web pages are fetched as static HTML, with no browser. Pages that build their content with JavaScript (an empty app shell) are reported, not charged; use a browser-based crawler for those. This actor converts the URLs you give it and does not crawl sites (see Website to Markdown for that).
• PDF pages with a text layer are read exactly; pages without one are read by OCR when it is on (up to 20 per PDF by default, set by maxOcrPages). OCR covers 7 languages (English, German, French, Spanish, Italian, Portuguese, Dutch). Handwriting and low-resolution photos come out poorly. For 29 languages, word boxes and per-page output, use OCR to Text.
• Legacy binary Office files (.doc, .xls, .ppt), RTF, OpenDocument presentations (.odp), HEIC/AVIF images and SVG are not supported. They are reported with a clear reason and never charged.
• Spreadsheets are cut at 1,000 rows per sheet by default (maxRowsPerSheet), and very large results are cut at about 3.5 million characters. Cut rows are marked truncated: true.
• Files up to 50 MB. Password-protected PDFs and pages behind a login can't be read.
• Polite by design: it sends an honest crawler user agent (ActorForge-AnyUrlToMarkdown) and does not pose as a browser. When a site answers 429 (rate limited) or 403 (refused), that URL is retried at most once (429 only, after Retry-After up to 30 s) and the remaining URLs on the same host are skipped as free error rows.
• tokenEstimate is characters divided by 4. That is a good guide for English with GPT and Claude tokenizers, not an exact count.
• Respects your run budget: set a maximum total charge and processing stops cleanly at the cap. No result is delivered without being paid for, and none is charged twice.

FAQ

Use it from code

Run the actor through the Apify API with the input above.

cURL

curl -X POST "https://api.apify.com/v2/acts/actor-forge~any-url-to-markdown/run-sync-get-dataset-items" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"url": "https://arxiv.org/pdf/1706.03762", "urls": ["https://en.wikipedia.org/wiki/Retrieval-augmented_generation", "https://calibre-ebook.com/downloads/demos/demo.docx"], "onlyMainContent": true, "ocr": true, "ocrLanguages": ["eng"], "maxPdfPages": 500, "respectRobotsTxt": true}'

JavaScript (Node.js)

// Node.js 18+ (built-in fetch). Set APIFY_TOKEN in your environment.
const input = {
  "url": "https://arxiv.org/pdf/1706.03762",
  "urls": [
    "https://en.wikipedia.org/wiki/Retrieval-augmented_generation",
    "https://calibre-ebook.com/downloads/demos/demo.docx"
  ],
  "onlyMainContent": true,
  "ocr": true,
  "ocrLanguages": [
    "eng"
  ],
  "maxPdfPages": 500,
  "respectRobotsTxt": true
};

const res = await fetch(
  "https://api.apify.com/v2/acts/actor-forge~any-url-to-markdown/run-sync-get-dataset-items",
  {
    method: "POST",
    headers: {
      Authorization: `Bearer ${process.env.APIFY_TOKEN}`,
      "Content-Type": "application/json",
    },
    body: JSON.stringify(input),
  }
);
const items = await res.json();
console.log(items.length, items[0]);

Python

# pip install apify-client   (set APIFY_TOKEN in your environment)
import os
from apify_client import ApifyClient

client = ApifyClient(os.environ["APIFY_TOKEN"])
run_input = {
    "url": "https://arxiv.org/pdf/1706.03762",
    "urls": [
        "https://en.wikipedia.org/wiki/Retrieval-augmented_generation",
        "https://calibre-ebook.com/downloads/demos/demo.docx"
    ],
    "onlyMainContent": True,
    "ocr": True,
    "ocrLanguages": [
        "eng"
    ],
    "maxPdfPages": 500,
    "respectRobotsTxt": True
}

run = client.actor("actor-forge/any-url-to-markdown").call(run_input=run_input)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

The run-sync-get-dataset-items endpoint waits for the run (up to 5 minutes) and returns the dataset rows directly. For longer runs, start the run asynchronously and read the dataset when it finishes, as the Python example does. Replace APIFY_TOKEN with your own token from the Apify console.

Step-by-step guides

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