Document-to-JSON Converter

Turn PDFs into structured JSON in seconds. AI-powered, no coding needed.

🚀 What does it do?

Paste a PDF URL → get structured JSON. That's it.

Powered by AI. Instead of rigid templates or fragile regex, an AI model actually reads and understands each document — so it adapts to any layout, language, or vendor, and even handles scanned files. That's why the same tool works on an Italian invoice, a Spanish receipt, or an English contract without any configuration.

Perfect for:

• Accountants — extract invoice data (numbers, dates, totals, VAT, IBAN)

• Developers — automate document processing in your apps

• Business analysts — convert bank statements to spreadsheets

• Legal teams — extract contract clauses and dates automatically

Related MCP server: Invoice Parser MCP

📋 Supported documents

✨ Example output

{
  "success": true,
  "data": {
    "document_type": "invoice",
    "confidence": 0.97,
    "metadata": {
      "invoice_number": "INV-2024-00123",
      "invoice_date": "2024-03-15",
      "currency": "EUR"
    },
    "seller": {
      "name": "Acme S.p.A.",
      "vat_id": "IT01234567890"
    },
    "line_items": [
      {
        "description": "Consulting services",
        "quantity": 1,
        "unit_price": 5000.00,
        "net_amount": 5000.00,
        "vat_rate": 22.0,
        "total": 6100.00
      }
    ],
    "totals": {
      "net_total": 5000.00,
      "vat_total": 1100.00,
      "grand_total": 6100.00
    },
    "payment_info": {
      "iban": "IT60X0542811101000000123456"
    }
  }
}

🧪 Live examples — try them now

Run the Actor on these public sample PDFs (synthetic data) to see the extraction quality for yourself:

Just paste one of these URLs as file_url, pick the matching document_type, and run. Each extraction takes ~15–20 seconds.

🎯 Why this Actor?

🔧 How to use

1. Get a public PDF URL (Dropbox, Google Drive, your server)

2. Select the document type

3. Run the Actor

4. Get your JSON in seconds

That's it. No configuration, no API keys needed.

💰 Pricing

Pay-per-event via Apify. Pay only for successful extractions. No subscription, no hidden fees.

🔒 Privacy

• PDFs are processed and not stored after extraction

• Data is available in your private dataset

• All API keys stay encrypted

📚 Supported OCR languages

eng (English), ita (Italian), spa (Spanish)

Combine with + for multi-language scanned documents: eng+ita+spa (default)

🤖 Built for AI agents (MCP)

This Actor is an MCP server: AI agents can call it directly as a tool to turn any PDF into JSON, with zero configuration — just pass a public file_url. Specialized tools (parse_invoice, parse_bank_statement, parse_contract) and a free parse_generic_document make it easy for an LLM to pick the right one for the task.

🔌 Integrations

Replace YOUR_APIFY_TOKEN with your token from Apify → Settings → Integrations.

Claude Code (CLI)

claude mcp add --transport http apify \
  "https://mcp.apify.com/?actors=opportunity-biz/document-to-json-mcp"

Claude Desktop / Cursor (MCP)

Add to your MCP config (claude_desktop_config.json or Cursor's mcp.json):

{
  "mcpServers": {
    "document-to-json": {
      "command": "npx",
      "args": [
        "-y", "mcp-remote",
        "https://mcp.apify.com/?actors=opportunity-biz/document-to-json-mcp",
        "--header", "Authorization: Bearer YOUR_APIFY_TOKEN"
      ]
    }
  }
}

The agent then sees parse_invoice, parse_bank_statement, parse_contract, and parse_generic_document as tools and calls them on its own.

REST API (any language)

One call in, JSON out — run-sync-get-dataset-items returns the result directly:

curl -X POST \
  "https://api.apify.com/v2/acts/opportunity-biz~document-to-json-mcp/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"file_url": "https://example.com/invoice.pdf", "document_type": "invoice", "validate_totals": true}'

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("opportunity-biz/document-to-json-mcp").call(run_input={
    "file_url": "https://example.com/invoice.pdf",
    "document_type": "invoice",
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

JavaScript / TypeScript

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('opportunity-biz/document-to-json-mcp').call({
  file_url: 'https://example.com/invoice.pdf',
  document_type: 'invoice',
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

n8n

Use an HTTP Request node (POST) to the REST API URL above, or the official Apify node → select document-to-json-mcp → set file_url and document_type. Great for "watch inbox → extract invoice → append to Google Sheet" workflows.

LangChain / CrewAI / any MCP framework

Point your agent framework's MCP client at https://mcp.apify.com/?actors=opportunity-biz/document-to-json-mcp — the parsing tools are exposed automatically.