PDF to Text & Markdown

hipersoft/pdf-to-text-extractor

Extract clean text or Markdown from PDFs in bulk — with an optional per-page JSON view. Feed the output straight into RAG pipelines, LLM prompts and n8n/Make/Zapier steps.

Run this scraper →See the API call

Total users

Monthly users

Total runs

Per pdf extracted

$0.004

Last rebuilt

Oct 26, 2026

Overview

Turn a list of PDF links into clean, ready-to-use text or Markdown — in bulk. Extract the text layer from every PDF, save each result as a file, and get a tidy dataset row per document.

What it does

Extracts clean text from the text layer of each PDF.
Outputs plain text, Markdown, or per-page JSON (page number → text).
Saves one result file per PDF and returns pages, characters and words for each.
Processes many PDFs in one run — one dataset row per document.

Use cases

RAG pipelines — extract, then feed the text to your embedding/indexing step.
LLM prompts — drop clean document text straight into your AI step for summaries, Q&A or classification.
n8n / Make / Zapier — run this as a step, then pass the text on to your AI or database node.
Content & research — pull the readable text out of reports, invoices, papers and manuals at scale.

Input

{
  "pdfUrls": [
    "https://example.com/report.pdf",
    "https://example.com/invoice.pdf"
  ],
  "output": "text"
}

Field	Type	Description
`pdfUrls`	array	Direct links to the PDF files to extract text from.
`output`	string	`text`, `markdown`, or `pages` (per-page JSON).

Output

Each PDF produces one dataset row, plus a saved result file you can download.

{
  "url": "https://example.com/report.pdf",
  "pages": 12,
  "chars": 18540,
  "words": 3120,
  "resultUrl": "https://api.apify.com/v2/key-value-stores/.../records/doc-0001.txt",
  "ok": true
}

Output schema

Field	Type	Description
`url`	string	The source PDF URL.
`pages`	integer	Number of pages in the PDF.
`chars`	integer	Character count of the extracted text.
`words`	integer	Word count of the extracted text.
`resultUrl`	string	Link to the saved text / Markdown / JSON file.
`ok`	boolean	Whether extraction succeeded for this PDF.

FAQ

Does it work on scanned PDFs? It reads the embedded text layer. Image-only scans with no text layer will return little or no text.

Can I automate it? Yes — via integrations on the Apify platform (including n8n, Make and Zapier) and the Apify API.

How am I charged? A flat fee per PDF processed.

Notes

Original clean-room implementation.

Input

Field	Type	Description
`pdfUrls` required PDF URLs	array	List of direct links to PDF files to extract text from. Each URL should point to a downloadable PDF.
`output` Output format	string · text, markdown, pages	Choose the saved format: plain text, Markdown, or a per-page JSON file (page number → text). Default: `"text"`

API

curl -X POST "https://api.apify.com/v2/acts/hipersoft~pdf-to-text-extractor/run-sync-get-dataset-items?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
  "pdfUrls": [
    "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf"
  ]
}'

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("hipersoft/pdf-to-text-extractor").call(run_input={
    "pdfUrls": [
        "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf"
    ]
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('hipersoft/pdf-to-text-extractor').call({
  "pdfUrls": [
    "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf"
  ]
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Pricing

Event	Price	Paid plans from
PDF Extracted Charged per PDF processed to text/markdown.	$0.004	$0.002

You pay only for what the run returns. Set a maximum cost per run and it stops cleanly at that limit.

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