Document to Markdown – DOCX, PPTX, XLSX

What it does

Document to Markdown converts office documents, spreadsheets, e-books and PDFs into clean Markdown for LLMs, RAG and search: Word headings, lists and tables become GFM, PowerPoint decks become one section per slide with speaker notes, Excel and OpenDocument sheets become Markdown tables (and, if you want, typed JSON rows), EPUBs become chapters. Give it document URLs, an uploaded file, data: URIs or Apify key-value store records; each document becomes one dataset record. The format is detected from the file itself, so wrong extensions do not matter.

Price per delivered record

Apify free plan: up to 10 items per run. Paid plans have no per-run cap; set maxTotalChargeUsd to cap spend.

Call it from code, an agent or the Console

curl -X POST "https://api.apify.com/v2/actors/sfoln~document-to-markdown/run-sync-get-dataset-items" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"documentUrls":["https://raw.githubusercontent.com/mwilliamson/mammoth.js/791a189230977143cde64dbf9f1d24dce96ac8a1/test/test-data/tables.docx"]}'

{
  "mcpServers": {
    "apify": {
      "type": "http",
      "url": "https://mcp.apify.com?tools=sfoln/document-to-markdown"
    }
  }
}

POST https://api.apify.com/v2/actors/sfoln~document-to-markdown/runs?maxTotalChargeUsd=1
GET  https://api.apify.com/v2/actor-runs/{runId}            # until status is SUCCEEDED
GET  https://api.apify.com/v2/datasets/{defaultDatasetId}/items?format=json

Authenticate with an Apify API token. MCP clients can instead sign in with OAuth when prompted. Example prompt for an agent: Convert https://raw.githubusercontent.com/mwilliamson/mammoth.js/791a189230977143cde64dbf9f1d24dce96ac8a1/test/test-data/tables.docx to Markdown with document-to-markdown and show me the table it contains.

Input fields

The documents to convert: URLs, an uploaded file, data: URIs or key-value store records. Each document produces one dataset record with its Markdown, metadata and per-part sections.

{
  "documentUrls": [
    "https://raw.githubusercontent.com/mwilliamson/mammoth.js/791a189230977143cde64dbf9f1d24dce96ac8a1/test/test-data/tables.docx"
  ]
}

One record per input item

Records land in the run's dataset; a synchronous call returns them directly. Each has a status (ok is charged; everything else is free) and a charged flag. The run's OUTPUT record totals items and charges.

{
  "input": "https://example.com/files/q1-sales.xlsx",
  "status": "ok",
  "charged": true,
  "chargedEvent": "document",
  "source": "document-converter",
  "fetchedAt": "2026-10-14T10:00:00.000Z",
  "url": "https://example.com/files/q1-sales.xlsx",
  "fileName": "q1-sales.xlsx",
  "fileSizeBytes": 8317,
  "sha256": "8b1a9953c4611296a827abf8c47804d7e6c49c6b6b0f6d9a8f5f1f4e2d3c4b5a",
  "format": "xlsx",
  "title": "Sales Workbook",
  "metadata": {
    "title": "Sales Workbook",
    "author": "Example Author",
    "subject": null,
    "description": null,
    "keywords": [],
    "language": null,
    "publisher": null,
    "createdAt": "2026-04-01T09:00:00.000Z",
    "modifiedAt": "2026-04-01T09:00:00.000Z"
  },
  "language": null,
  "pageCount": 0,
  "rowCount": 4,
  "wordCount": 29,
  "charCount": 140,
  "markdown": "## Sales\n\n| Region | Q1 | Q2 | Total | Updated |\n| --- | --- | --- | --- | --- |\n| North | 1240 | 1310 | 2550 | 2026-04-02 |\n| South | 980 | 1002 | 1982 | 2026-04-03 |\n| West | 1105 | 1190 | 2295 | 2026-04-04 |",
  "markdownUrl": null,
  "sections": [
    {
      "type": "sheet",
      "index": 1,
      "title": "Sales",
      "markdown": "## Sales\n\n| Region | Q1 | Q2 | Total | Updated |\n…",
      "hidden": false,
      "rowCount": 4,
      "columnCount": 5
    }
  ],
  "tables": [
    {
      "sheet": "Sales",
      "index": 1,
      "rowCount": 4,
      "columnCount": 5,
      "columns": [
        "Region",
        "Q1",
        "Q2",
        "Total",
        "Updated"
      ],
      "headerRow": true,
      "hidden": false,
      "rows": [
        {
          "Region": "North",
          "Q1": 1240,
          "Q2": 1310,
          "Total": 2550,
          "Updated": "2026-04-02"
        }
      ]
    }
  ],
  "tablesUrl": null,
  "truncated": false,
  "truncation": [],
  "billedBlocks": 1,
  "overageCharged": 0
}

Questions

Which formats are supported?

DOCX, PPTX, XLSX, XLSB, XLS, ODS, CSV/TSV, EPUB, RTF, ODT, HTML, plain text (JSON and XML are returned as code blocks) and PDF (its text layer). The format is detected from the file's bytes, so a wrong extension does not matter. Legacy .doc and .ppt files are not supported: save them as DOCX or PPTX.

How are pages counted for pricing?

PDF pages and slides count as pages; for text documents a page is 3,000 characters of output (about 500 words); spreadsheets count non-empty rows. One document event covers 20 pages or 10,000 rows, each further block of 20 pages or 10,000 rows is one document-overage event ($0.0007).

Can I get spreadsheet data as JSON?

Yes: set includeRows and every sheet's rows come back in tables[].rows as JSON objects keyed by the header row, with numbers, booleans and ISO dates typed.

Is it safe to convert untrusted files?

Archives are checked before they are unpacked (entry count and uncompressed size, so zip bombs are refused), XML entity declarations are refused and nothing in a document is executed. Images, macros and embedded objects are ignored.

Related APIs

• pdf-text-extractor PDF Text Extractor – PDF to Text & Markdown$3 / 1,000
• pdf-ocr-markdown PDF OCR to Markdown Converter$7 / 1,000
• document-to-json Document Parser – AI PDF & Image to JSON$7 / 1,000
• url-to-markdown-summary URL to Markdown & Article Extractor$1.5 / 1,000

This page for agents

• /actors/document-to-markdown.json — this API as JSON
• /actors/document-to-markdown.md — this API as Markdown
• apify.com/sfoln/document-to-markdown.md — the Store listing as Markdown
• /catalog.json — the whole catalogue