Document to Markdown & JSON: DOCX, XLSX, PPTX, HTML, EPUB, CSV

Give this tool links to Word, Excel, PowerPoint, HTML, EPUB or CSV files, or upload one, and get clean, structured output for each document: Markdown with headings, lists, tables and image references for text documents, typed JSON rows for every spreadsheet sheet, and metadata (title, author, dates, pages, slides, sheets, word count) for everything. Optional RAG chunks and embedded-image extraction. $2 per 1,000 documents, with no per-page or per-row fees.

What can this document converter do?

• Word to Markdown (DOCX): headings, bold and italic, bullet and numbered lists (including nested levels), tables, links, footnotes and image references.
• PowerPoint to Markdown (PPTX): one section per slide with its title, bullet levels, tables, pictures, chart data as a table, and speaker notes.
• Excel to JSON (XLSX): one JSON object per row for every sheet, with automatic header-row detection (even below title rows), typed values (numbers, booleans, ISO dates), merged cells filled in, saved formula results, and a Markdown table per sheet.
• CSV to JSON: delimiter and encoding detection, typed values, and codes with leading zeros (postcodes, SKUs, IDs) kept as text.
• HTML to Markdown: keeps the main content and drops navigation, headers, footers and cookie banners; links and images become absolute URLs.
• EPUB to Markdown: chapters in reading order, book metadata and a chapter list with word counts.
• RAG chunks: split at headings, paragraphs and table rows with your chunk size and overlap; table headers repeat in every chunk and each chunk carries its heading path.
• Extract embedded images from DOCX, PPTX and EPUB to the run's key-value store, with links in the Markdown.

PDFs are handled by our separate PDF to Text & Tables Extractor, which adds OCR for scanned pages. PDF links given to this tool are skipped and not charged.

What data do you get?

Field	Description
url, fileName, format	The document and its detected format (docx, pptx, xlsx, html, epub, csv, text)
title, author, createdAt, modifiedAt, metadata	Document properties (subject, keywords, company, last modified by and more in metadata)
pageCount, pageCountSource	Word pages from the file's own statistics when Word saved them, otherwise an estimate (500 words per page)
slideCount, sheetCount, chapterCount	Size of presentations, workbooks and e-books
wordCount, characterCount, language, tableCount, imageCount, fileSizeBytes	Content statistics
markdown, text	Full Markdown and (optional) plain text
sheets	Per sheet: name, headerRow, headers, columnTypes, title, rowCount, truncated, rows, mergedRanges
slides, chapters	Per slide title and notes; per chapter title and word count
images	Embedded images: name, type, size, alt text and saved url when extraction is on
chunks, chunkCount	Optional RAG chunks: text, charCount, tokenEstimate, headings
warnings, fullOutputUrl	Notes, and a link to the complete JSON when a very large file does not fit in one dataset item

Who uses it?

• AI and RAG builders loading company handbooks, decks and spreadsheets into vector databases or LLM prompts.
• Data and operations teams turning Excel exports and CSV files into clean JSON for databases, APIs and automations.
• Knowledge-base and documentation teams migrating Word and HTML content to Markdown-based tools.
• Developers who want "document in, JSON out" without maintaining their own conversion servers.

How to use it

1. Click Try for free (or Start).
2. Paste document URLs (or upload a text file of URLs), or upload a file.
3. Choose outputs: Markdown, plain text, image extraction and RAG chunks with your chunk size and overlap.
4. For spreadsheets, pick header detection, typed values and merged-cell handling, or limit to certain sheets.
5. Run it and download JSON, or open the Documents, Markdown and Spreadsheet rows views. Schedule it or call it from the API to convert new files as they arrive.

Input example

{
  "startUrls": [
    {
      "url": "https://api.apify.com/v2/key-value-stores/6tG74dmDqhbuixGpx/records/quarterly-report.docx"
    },
    {
      "url": "https://api.apify.com/v2/key-value-stores/6tG74dmDqhbuixGpx/records/regional-sales.xlsx"
    },
    {
      "url": "https://api.apify.com/v2/key-value-stores/6tG74dmDqhbuixGpx/records/product-roadmap.pptx"
    }
  ],
  "includeMarkdown": true,
  "extractImages": false,
  "chunking": false,
  "headerDetection": "auto",
  "typedValues": true,
  "fillMergedCells": true
}

Output example

The Excel file from the default run (Markdown shortened, first rows shown):

{
  "url": "https://api.apify.com/v2/key-value-stores/6tG74dmDqhbuixGpx/records/regional-sales.xlsx",
  "fileName": "regional-sales.xlsx",
  "format": "xlsx",
  "title": "Regional Sales Q1 2026",
  "author": "Sales Operations, Example Corp",
  "createdAt": "2026-11-05T19:39:12Z",
  "modifiedAt": "2026-11-05T19:39:12Z",
  "sheetCount": 2,
  "wordCount": 147,
  "characterCount": 701,
  "tableCount": 2,
  "imageCount": 0,
  "fileSizeBytes": 8211,
  "markdown": "# Regional Sales Q1 2026\n\n## Sales Q1 2026\n\nRegional Sales - Q1 2026\n\n| Region | Sales rep | Month | Units | Revenue (USD) | Target met | Revenue per unit |\n| -...",
  "sheets": [
    {
      "name": "Sales Q1 2026",
      "headerRow": 3,
      "headers": [
        "Region",
        "Sales rep",
        "Month"
      ],
      "columnTypes": {
        "Region": "string",
        "Sales rep": "string",
        "Month": "date",
        "Units": "integer",
        "Revenue (USD)": "number",
        "Target met": "boolean",
        "Revenue per unit": "number"
      },
      "title": "Regional Sales - Q1 2026",
      "rowCount": 7,
      "columnCount": 7,
      "truncated": false,
      "rows": [
        {
          "_row": 4,
          "Region": "North",
          "Sales rep": "A. Patel",
          "Month": "2026-01-01",
          "Units": 120,
          "Revenue (USD)": 18450.5,
          "Target met": true,
          "Revenue per unit": 153.75
        },
        {
          "_row": 5,
          "Region": "North",
          "Sales rep": "B. Okafor",
          "Month": "2026-02-01",
          "Units": 98,
          "Revenue (USD)": 15020,
          "Target met": false,
          "Revenue per unit": 153.27
        },
        {
          "_row": 6,
          "Region": "North",
          "Sales rep": "C. Novak",
          "Month": "2026-03-01",
          "Units": 143,
          "Revenue (USD)": 22110.75,
          "Target met": true,
          "Revenue per unit": 154.62
        }
      ],
      "hidden": false,
      "mergedRanges": [
        "A7:A8",
        "A1:G1",
        "A4:A6"
      ]
    },
    {
      "name": "Products",
      "headerRow": 1,
      "headers": [
        "SKU",
        "Product",
        "Unit price"
      ],
      "columnTypes": {
        "SKU": "string",
        "Product": "string",
        "Unit price": "number",
        "Launched": "date",
        "In stock": "boolean",
        "Notes": "string"
      },
      "title": null,
      "rowCount": 4,
      "columnCount": 6,
      "truncated": false,
      "rows": [
        {
          "_row": 2,
          "SKU": "00123",
          "Product": "Desk lamp",
          "Unit price": 39.9,
          "Launched": "2024-05-14",
          "In stock": true,
          "Notes": "Best seller"
        },
        {
          "_row": 3,
          "SKU": "00456",
          "Product": "Standing desk",
          "Unit price": 349,
          "Launched": "2025-02-03",
          "In stock": true,
          "Notes": null
        },
        {
          "_row": 4,
          "SKU": "00789",
          "Product": "Monitor arm",
          "Unit price": 89.5,
          "Launched": "2025-09-22",
          "In stock": false,
          "Notes": "Back in stock in April"
        }
      ],
      "hidden": false,
      "mergedRanges": null
    }
  ],
  "metadata": {
    "title": "Regional Sales Q1 2026",
    "author": "Sales Operations, Example Corp",
    "language": "en-US",
    "createdAt": "2026-11-05T19:39:12Z",
    "modifiedAt": "2026-11-05T19:39:12Z",
    "application": "LibreOffice/24.2.7.2$Linux_X86_64 LibreOffice_project/420$Build-2"
  }
}

How much does it cost?

You pay per converted document, whatever its length:

Event	Price	Per 1,000
Document converted	$0.002	$2
Run start	$0.00005

Examples: the 3-document default run costs about $0.006; 500 Word contracts about $1; 10,000 CSV exports about $20. Failed downloads, unsupported formats (including PDFs) and files over your size limit are not charged. A spreadsheet with many sheets or a long book is still one document.

Volume discounts on higher Apify plans. The prices above are for the Apify Free plan. On paid plans the per-result price drops automatically: about 15% lower on Bronze, 25% lower on Silver and 38% lower on Gold and above.

Use it via API, Make, Zapier, n8n or an AI agent

Apify API. Start a run and get the results back in one HTTP request (replace YOUR_API_TOKEN with the token from Apify Console > Settings > Integrations):

curl -X POST "https://api.apify.com/v2/acts/plotpointtech~document-to-markdown-json/run-sync-get-dataset-items?token=YOUR_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"startUrls": [{"url": "https://api.apify.com/v2/key-value-stores/6tG74dmDqhbuixGpx/records/quarterly-report.docx"}, {"url": "https://api.apify.com/v2/key-value-stores/6tG74dmDqhbuixGpx/records/regional-sales.xlsx"}, {"url": "https://api.apify.com/v2/key-value-stores/6tG74dmDqhbuixGpx/records/product-roadmap.pptx"}], "includeMarkdown": true, "extractImages": false, "chunking": false, "headerDetection": "auto", "typedValues": true, "fillMergedCells": true}'

For longer jobs, start the run asynchronously and read the dataset when it finishes. Official apify-client libraries exist for Python and JavaScript; the API tab on this page has ready-made code.

No-code automation. Connect the tool to Make, Zapier, n8n, Google Sheets, Slack, Airtable or any webhook with Apify integrations, and use Schedules in Apify Console to run it hourly, daily or weekly.

AI agents (MCP). Give Claude, ChatGPT, Cursor, VS Code or any MCP-compatible agent direct access to this tool through the hosted Apify MCP server. Add this server URL to your client:

https://mcp.apify.com?tools=plotpointtech/document-to-markdown-json

The agent can then call the tool with the same input fields shown above and read the results.

FAQ

Is it legal to convert these documents? Yes, for documents you are allowed to access and use. The tool downloads exactly the URLs you provide (or your upload) and does not log in anywhere. Respect copyright and the confidentiality of the documents you process; files are processed in your own Apify run and are not shared.

Which formats are supported? DOCX, PPTX, XLSX (and XLSM), HTML web pages, EPUB, CSV/TSV, plain text and Markdown. Older binary .doc, .xls and .ppt files, OpenDocument files and password-protected Office files are not supported; save them as DOCX/XLSX/PPTX first. Use our PDF tool for PDFs.

How are spreadsheet headers and types detected? The header is the first row (within the first 20) whose cells are mostly distinct text and that is followed by data, so title rows above a table are kept separately as the sheet title. Numbers, booleans and dates become JSON types; columns that mix words and numbers in CSV files stay text. Formula cells return the result saved in the file; if a file was never calculated by a spreadsheet app, the formula text is returned with a warning.

How large can files be? Up to 200 MB per file (50 MB by default). Sheets are capped at 10,000 rows by default (set 0 for no limit). If one document's output exceeds what a dataset item can hold (about 9 MB), the complete JSON is saved to the key-value store and linked in fullOutputUrl.

Are page counts exact? Pages exist only after a document is laid out, so DOCX page counts come from the statistics Word stores when it saves a file. When those are missing or stale (common for files generated by software), an estimate is returned and pageCountSource says estimate.

Related tools from Plot Point Technologies

• PDF to Text & Tables Extractor - Markdown + OCR, $0.40/1K: PDFs to text, Markdown and CSV tables, with OCR for scans.
• Website to Markdown Crawler for AI, LLM & RAG - $1/1K: any website as clean Markdown for LLMs and RAG.
• Image OCR - Image to Text in Bulk, Tesseract & AI Vision: text from images in bulk, with AI mode for receipts and handwriting.

Plot Point Technologies is not affiliated with Microsoft, the EPUB or CSV standards bodies, or the publishers of any document you process.

Questions or feature requests: support@plotpoint.tech.

---

If this tool saved you time, we would be grateful for a short review on this page; it helps other people find it. If something did not work as expected, please open an issue on the Issues tab and we will look into it quickly.