PDF to Text & Markdown: Extract PDF Content by URL

Give it a list of PDF URLs and get back clean text or Markdown for each one — headings and paragraphs rebuilt from the PDF's own font sizes, a best-effort Markdown table for simple aligned tables, and metadata (title, author, page count). Built for feeding a RAG pipeline, an LLM prompt, or a row to Google Sheets — anywhere you'd otherwise hand-copy text out of a PDF. No OCR yet: a scanned, image-only PDF is flagged (isScanned) and never charged.

Who it's for

Anyone who has a list of PDF URLs — from a web crawl, a Sheet, a CRM export, or a document management system — and needs a plain PDF to Markdown conversion, not a raw byte stream. Common uses: preparing PDFs to embed for RAG or as LLM context, converting a folder of reports from PDF to Markdown for a wiki, or piping extracted text to Google Sheets or Airtable via an integration.

How to use

1. In the Apify Console. Open the actor page and click Start — the pdfUrls field is already pre-filled with a working example. Results land in the run's dataset as soon as each item is found.
2. Via the API. Call it directly with a POST request — no Console needed once you have an API token:

   curl "https://api.apify.com/v2/acts/accountable_eel~pdf-text-extractor/run-sync-get-dataset-items?token=<YOUR_TOKEN>" \
     -X POST \
     -H "Content-Type: application/json" \
     -d '{"pdfUrls":["https://www.irs.gov/pub/irs-pdf/fw4.pdf"]}'
   

3. On a schedule. Save this actor as an Apify Task with the input you want, then add a Schedule (hourly, daily, weekly) so it runs on its own — no server of your own required.

Input

{
  "pdfUrls": [
    "https://www.irs.gov/pub/irs-pdf/fw4.pdf"
  ]
}

One direct PDF URL per line, for a list of PDF URLs from a crawl, a Sheet, or a CRM export. Accepted formats: https://www.irs.gov/pub/irs-pdf/fw4.pdf, https://arxiv.org/pdf/1706.03762.

{
  "pdfUrls": [
    "https://www.irs.gov/pub/irs-pdf/fw4.pdf",
    "https://arxiv.org/pdf/1706.03762"
  ],
  "pages": "",
  "outputFormat": "markdown",
  "includePageBreaks": false
}

pdfUrls is one direct PDF URL per line — for a list of PDF URLs from a crawl, a Sheet, or a CRM export. A URL pasted without its https:// (common when copied from a spreadsheet cell) is filled in automatically.

• pages (optional) — a page range like "1-5", or a single page like "3". Leave empty to extract every page.
• outputFormat — "markdown" (default) rebuilds #/##/### headings from font sizes and renders any detected table as a best-effort Markdown table; "text" keeps the same paragraphs with no Markdown syntax.
• includePageBreaks — inserts a marker between each page's content (an invisible <!-- page N --> comment in Markdown, "--- Page N ---" in plain text) so a downstream chunker can split by page.

Output

One row per PDF, for example:

query	found	status	url	title	author	pageCount	pagesExtracted	outputFormat	content	wordCount	isScanned	scrapedAt
https://www.irs.gov/pub/irs-pdf/fw4.pdf	true	OK		<title (from pdf metadata)>	<author (from pdf metadata)>				<extracted text/markdown>		<scanned (no text layer)>	1970-01-01T00:00:00.000Z

A URL that isn't a PDF, doesn't exist, or is larger than the 50 MB limit comes back as a row with "found": false and is never charged. A scanned, image-only PDF (isScanned: true) is also never charged — see "No OCR in this version" below.

How this works

1. Download — up to 50 MB per PDF, streamed with a hard cap so one huge file can't run away with your run's memory or your bill.
2. Extract — pdfjs-dist reads the text layer page by page, with each character's font size and position.
3. Reconstruct — lines are grouped by vertical position, a two-column academic layout is detected and read left-column-then-right-column instead of line-by-line across the gutter, consecutive lines of similar size are merged into paragraphs, and a line noticeably bigger than body text becomes a heading (#/##/###, biggest first). A run of 3+ consecutive lines that each split into well-separated clusters is rendered as a best-effort Markdown table.
4. No OCR in this version — if a PDF's text layer is almost empty (a scanned page with no embedded text), isScanned is true, content is null, and the row is never charged.

This is a best-effort reconstruction, not a layout-perfect one:

• Two-column detection works well for the common single-gutter academic layout. An exotic multi-region magazine layout, or a page where both columns happen to align to the exact same text baseline throughout, can read out of order.
• Table detection requires at least 3 consecutive lines with clearly separated columns. A 1-2 row table, or a table with merged or empty cells in irregular places, may render as plain paragraph text instead.
• Line-wrap dehyphenation (joining a word split across two lines by a hyphen) can't always tell a soft line-break hyphen from a real one in a compound word (e.g. "English-to-German" broken exactly at a hyphen can come out as "Englishto-German"). This is a known limitation of automatic PDF text extraction generally, not specific to this actor.

Pricing

• Document processed (up to 20 pages): $2 per 1,000 PDF documents
• Extra page beyond 20: $0.3 per 1,000 PDF documents

Plus a $0.003 start fee per run. Each event above is billed independently, only when it actually returns data — misses (found:false) are never charged.

One document event covers up to 20 extracted pages; a longer document also bills one page event for each page beyond 20, so a 200-page report doesn't cost the same as a 2-page memo. A scanned PDF with no text layer bills nothing at all, even though it still returns a row telling you so.

Use it from Clay, n8n, Make, or an AI agent

This actor runs synchronously over plain HTTP — call it directly from a script, a workflow tool, or an AI agent, no Apify Console needed once you have an API token.

curl "https://api.apify.com/v2/acts/accountable_eel~pdf-text-extractor/run-sync-get-dataset-items?token=<YOUR_TOKEN>" \
  -X POST \
  -H "Content-Type: application/json" \
  -d '{"pdfUrls":["https://www.irs.gov/pub/irs-pdf/fw4.pdf"]}'

n8n. Add an HTTP Request node: Method POST, URL https://api.apify.com/v2/acts/accountable_eel~pdf-text-extractor/run-sync-get-dataset-items?token=<YOUR_TOKEN>, Body Content Type JSON, JSON Body {"pdfUrls":["https://www.irs.gov/pub/irs-pdf/fw4.pdf"]} (swap in an expression from an earlier node for a real value).

Clay. Add an "HTTP API" column: Method POST, URL https://api.apify.com/v2/acts/accountable_eel~pdf-text-extractor/run-sync-get-dataset-items?token=<YOUR_TOKEN>, Body {"pdfUrls":["{{PDF document}}"]}, mapping the row's PDF document into the pdfUrls array.

MCP. In Claude, Cursor, or any MCP client with the Apify MCP server, ask for "PDF to Text & Markdown | Apify" — the agent will find and run this actor.

A common pattern: run this actor on a list of PDF URLs, then send each row's content field to Google Sheets (one row per PDF) as a lightweight PDF-to- Google-Sheets pipeline, or straight into a RAG pipeline's document loader — the Markdown output chunks cleanly on its own #/## headings.

Data & privacy

This actor only reads the PDF at the URL you give it. Nothing is stored beyond the run's own dataset; no PDF content is retained after the run ends.

FAQ

Does it do OCR on scanned PDFs? Not in this version. A scanned or image-only PDF is flagged (isScanned: true) and never charged — no extracted text is fabricated.

What's the file size limit? 50 MB per PDF. A larger file comes back as a free BAD_FORMAT miss.

Can I extract just a few pages from a huge PDF? Yes — set pages to a range like "1-10". Only the requested pages count toward parsing time and billing (pagesExtracted, not pageCount); the whole file still has to be downloaded first, since PDF pages aren't independently fetchable over HTTP.