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markitdown

markitdown

Converts PDF, Word, Excel, PowerPoint, HTML, CSV, EPUB, ZIP and other files into Markdown text that language models and search indexes can read. Use when a user asks to convert a document to Markdown, turn a PDF or DOCX into text for an LLM, export spreadsheet tables as Markdown, prepare files for RAG ingestion, batch-convert a folder of office documents, o…

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name: markitdown description: >- Converts PDF, Word, Excel, PowerPoint, HTML, CSV, EPUB, ZIP and other files into Markdown text that language models and search indexes can read. Use when a user asks to convert a document to Markdown, turn a PDF or DOCX into text for an LLM, export spreadsheet tables as Markdown, prepare files for RAG ingestion, batch-convert a folder of office documents, or mentions MarkItDown, "markitdown", or "document to markdown". license: Apache-2.0 compatibility: "Python 3.10-3.14; optional ffmpeg for MP3/M4A audio and exiftool for image metadata" metadata: author: terminal-skills version: "1.0.0" category: documents tags: ["markdown-conversion", "pdf-to-markdown", "office-documents", "rag-ingestion", "llm-preprocessing"] repository: https://github.com/microsoft/markitdown

MarkItDown — Convert documents to Markdown for LLMs

Overview

MarkItDown is a Python library and command-line tool from Microsoft that turns office documents, PDFs, web pages and archives into Markdown. It keeps the structure a model needs (headings, lists, tables, links) and drops visual layout. Conversion runs locally; cloud services (Azure, an LLM for OCR) are opt-in.

Instructions

Installation

python -m venv .venv
source .venv/bin/activate
pip install 'markitdown[all]'
markitdown --version

[all] pulls every converter. Install fewer extras to keep the environment small, or run the tool once through uv without installing it:

pip install 'markitdown[pdf,docx,xlsx]'
uvx --from 'markitdown[pdf]' markitdown q3-board-report.pdf

Available extras: pptx, docx, xlsx, xls, pdf, outlook, audio-transcription, youtube-transcription, az-doc-intel, az-content-understanding, all. A missing extra raises MissingDependencyException and names the extra to install.

Convert from the command line

markitdown q3-board-report.pdf -o q3-board-report.md        # write to a file
markitdown cost-plan-stage-3.xlsx > cost-plan-stage-3.md    # or redirect stdout
cat release-notes.html | markitdown -x html > release-notes.md   # stdin needs a type hint
markitdown handover-pack.zip -o handover-pack.md            # every file inside the ZIP
markitdown "https://docs.python.org/3/library/pathlib.html" -o pathlib.md   # http(s) URL
FlagPurpose
-o, --outputOutput file (default: stdout)
-x, --extensionFile-type hint, for stdin input
-m, --mime-typeMIME type hint
-c, --charsetCharset hint, such as UTF-8
--keep-data-urisKeep base64 images instead of truncating them
-p, --use-pluginsEnable installed third-party plugins
--list-pluginsList installed plugins and exit
-d, --use-docintel with -e, --endpointConvert with Azure Document Intelligence
--use-cu with --cu-endpointConvert with Azure Content Understanding
--cu-analyzer, --cu-file-typesPick an analyzer; limit which file types go to Azure

The command exits with status 1 when conversion fails, so a loop can record failures:

mkdir -p markdown
for f in contracts/*.docx; do
  markitdown "$f" -o "markdown/$(basename "${f%.*}").md" || echo "$f" >> failed.txt
done

Python API

from pathlib import Path

from markitdown import MarkItDown

md = MarkItDown(enable_plugins=False)
result = md.convert_local("contracts/lease-harbour-street.docx")

print(result.title)  # None when the format has no title
Path("lease-harbour-street.md").write_text(result.markdown, encoding="utf-8")

Pick the narrowest method that fits the input:

MethodAccepts
convert_local(path)A file on disk only
convert_stream(stream, stream_info=...)An open binary stream
convert_response(response)A requests.Response fetched by the caller
convert_uri(uri)file:, data:, http: and https: URIs
convert(source)Any of the above; the most permissive

Streams carry no file name, so pass a hint:

from markitdown import MarkItDown, StreamInfo

md = MarkItDown()
with open("uploads/q3-board-report.pdf", "rb") as fh:
    result = md.convert_stream(fh, stream_info=StreamInfo(extension=".pdf"))
print(len(result.markdown))

Errors to handle: FileConversionException (a converter failed, including a missing extra), UnsupportedFormatException (no converter accepts the file), and the built-in FileNotFoundError.

Image descriptions and OCR with an LLM

Out of the box MarkItDown does not OCR. The markitdown-ocr plugin sends embedded images and scanned pages to a vision model through an OpenAI-compatible client.

pip install markitdown-ocr openai
markitdown --list-plugins
from markitdown import MarkItDown
from openai import OpenAI

md = MarkItDown(
    enable_plugins=True,
    llm_client=OpenAI(max_retries=5),
    llm_model="gpt-4o",
    llm_prompt="Extract all text from this image, preserving table structure.",
)
result = md.convert("scans/signed-lease-2026.pdf")
print(result.markdown)

Without the plugin, llm_client and llm_model only add descriptions to image files and pictures inside PPTX. The command line has no flags for the LLM client, so OCR needs the Python API. Without llm_client the plugin loads but silently skips OCR.

Azure Document Intelligence and Content Understanding

Both are paid cloud converters for scans, complex tables, audio and video. Copy the endpoint from the resource's Keys and Endpoint page in the Azure portal. Authentication uses AZURE_API_KEY when that variable is set, otherwise DefaultAzureCredential (for example after az login).

pip install 'markitdown[az-doc-intel,az-content-understanding]'

# Document Intelligence: endpoint read from MARKITDOWN_DOCINTEL_ENDPOINT
markitdown scans/drainage-survey.pdf -d -o drainage-survey.md

# Content Understanding: endpoint of a Microsoft Foundry resource
export MARKITDOWN_CU_ENDPOINT="https://fernhill-docs.services.ai.azure.com/"
markitdown recordings/client-call-2026-09-12.wav --use-cu -o client-call-2026-09-12.md
markitdown invoices/2026-08/inv-20817.pdf --use-cu \
  --cu-analyzer prebuilt-invoice --cu-file-types pdf -o inv-20817.md

With an analyzer, the output starts with YAML front matter holding the extracted fields. -d and --use-cu cannot be combined. In Python, pass docintel_endpoint=, or cu_endpoint= with optional cu_analyzer_id= and cu_file_types=[ContentUnderstandingFileType.PDF] (imported from markitdown.converters), to MarkItDown().

MCP server and Docker

pip install markitdown-mcp
markitdown-mcp                                      # STDIO transport
markitdown-mcp --http --host 127.0.0.1 --port 3001  # Streamable HTTP and SSE

The server exposes one tool, convert_to_markdown(uri), for http:, https:, file: and data: URIs.

git clone https://github.com/microsoft/markitdown.git
cd markitdown
docker build -t markitdown:latest .
docker run --rm -i markitdown:latest < q3-board-report.pdf > q3-board-report.md

Examples

Example 1: Spreadsheet and slides into a prompt

Request: "Convert q3-revenue.xlsx and the board deck to Markdown so I can paste them into a prompt."

markitdown q3-revenue.xlsx -o q3-revenue.md
markitdown q3-board-update.pptx -o q3-board-update.md

Result: every sheet becomes a heading with a table; every slide becomes a block with its notes.

## Q3 Revenue
| Region | July | August | September |
| --- | --- | --- | --- |
| EMEA | 412300 | 398750 | 441900 |
| APAC | 288100 | 301450 | 315200 |

## Headcount
| Team | FTE |
| --- | --- |
| Support | 14 |
| Sales | 9 |
<!-- Slide number: 1 -->
# Q3 Board Update
Revenue up 8% quarter over quarter
Churn down to 2.1%

### Notes:
Mention the EMEA pipeline.

Example 2: Convert a folder and report what failed

Request: "Convert everything under project-archive/ to Markdown, keep the folder structure, and tell me which files came out empty."

from pathlib import Path

from markitdown import FileConversionException, MarkItDown, UnsupportedFormatException

source, target = Path("project-archive"), Path("archive-md")
wanted = {".pdf", ".docx", ".pptx", ".xlsx", ".msg", ".html", ".csv", ".epub"}
md = MarkItDown(enable_plugins=False)
counts = {"ok": 0, "empty": 0, "failed": 0}

for path in sorted(source.rglob("*")):
    if not path.is_file() or path.suffix.lower() not in wanted:
        continue
    try:
        text = md.convert_local(path).markdown.strip()
    except (FileConversionException, UnsupportedFormatException) as exc:
        counts["failed"] += 1
        print(f"FAILED {path}: {type(exc).__name__}")
        continue
    status = "empty" if len(text) < 50 else "ok"
    counts[status] += 1
    if status == "empty":
        print(f"EMPTY  {path}")
    out = target / path.relative_to(source).with_suffix(".md")
    out.parent.mkdir(parents=True, exist_ok=True)
    out.write_text(text + "\n", encoding="utf-8")

print(counts)

Result:

EMPTY  project-archive/2025/mill-lane/drainage-report.pdf
{'ok': 3, 'empty': 1, 'failed': 0}

archive-md/2026/harbour-street/cost-plan-stage-3.md and the other outputs mirror the source tree. The empty file is a scan; route it through the OCR plugin or Azure.

Guidelines

  • No OCR by default. A scanned PDF or a PNG converts to an empty string without an error. Treat very short output as a failure and retry with markitdown-ocr or an Azure converter.
  • Damaged files may not raise. A truncated PDF can fall through to the plain-text converter and return a few bytes. Check output length; do not rely on exceptions alone.
  • Known failures: password-protected PDFs and corrupt Office files raise FileConversionException; legacy .doc files raise UnsupportedFormatException. Re-save them as unlocked PDF or .docx first.
  • Images need a helper. Image files yield EXIF metadata only when exiftool is on PATH (or EXIFTOOL_PATH is set) and a description only when an LLM client is configured.
  • PDF structure is limited. Text and tables are extracted, but headings usually arrive as plain lines because PDFs carry no heading markup.
  • Security: MarkItDown reads files and fetches URLs with the privileges of the process. In a server, never pass user input to convert(); use convert_local() or convert_stream(), restrict paths, and block private, loopback and metadata-service addresses.
  • MCP server: it has no authentication and can read any file the user can. Keep it bound to 127.0.0.1.
  • Audio privacy: built-in transcription uploads the audio to Google's Web Speech API through the SpeechRecognition package. Do not use it for confidential recordings.
  • Cost: every Azure-routed conversion is a billable API call. Limit it with --cu-file-types or cu_file_types.
  • Plugins run third-party code and are off by default. Inspect markitdown --list-plugins before enabling them.
  • Web pages: navigation and footers are converted along with the article, and some sites answer with 403. For article text use a content extractor such as Trafilatura.
  • Pin the version. The 0.1.x series is classified as beta; flags and output details change between releases.
  • When NOT to use it: layout-faithful conversion for human readers, editing or generating Office files, or producing PDFs. MarkItDown only reads documents.
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