MarkItDown Alternative for AI-Ready Markdown

What MarkItDown does well

• Runs entirely on your machine — no upload, no vendor, no data leaving your network.
• Free and open source, with an active community.
• Good coverage of Office formats: DOCX, PPTX, XLSX.
• Easy to script: one command or a few lines of Python.
• Optional LLM integration for image description.

If your documents are digital (not scanned), your volume is modest, and you are comfortable with Python, MarkItDown is a sensible default. We are not going to pretend otherwise.

Where teams hit the ceiling

Side by side

Moving a script over

A typical local script:

from markitdown import MarkItDown

md = MarkItDown().convert("report.pdf")
print(md.text_content)

The hosted equivalent:

import base64, requests

API_KEY = "mf_live_YOUR_KEY"

def convert(path: str) -> str:
    with open(path, "rb") as fh:
        data_url = "data:application/pdf;base64," + base64.b64encode(fh.read()).decode()

    res = requests.post(
        "https://markdflow.org/api/convert",
        headers={
            "Content-Type": "application/json",
            "Authorization": f"Bearer {API_KEY}",
        },
        json={"fileName": path.split("/")[-1], "mimeType": "application/pdf", "fileData": data_url},
        timeout=120,
    )
    res.raise_for_status()
    return res.json()["markdownText"]

print(convert("report.pdf"))

The difference is that the hosted call also gives you blocks, blocksCount and confidence, so your pipeline can decide what to trust.

When you should stay with MarkItDown

• Documents cannot leave your network (regulated data, air-gapped environments).
• Everything you process is a clean digital Office file.
• Volume is tiny and occasional.
• You already have parsing baked into a working pipeline — switching costs more than it returns.

Frequently asked questions