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MD-DOCX Converter

Name: MD-DOCX Converter
Author: cjwpenner

by cjwpenner

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MD-DOCX Конвертер

Инструмент на Python для двустороннего преобразования между Markdown (.md) и Microsoft Word (.docx). Разработан для упрощения переноса контента между документами Word и ИИ-инструментами, такими как Claude, ChatGPT и GitHub Copilot.

Что он делает

Преобразует .md → .docx с правильной иерархией заголовков (Название, Заголовок 1–9)
Преобразует .docx → .md в чистый GitHub Flavored Markdown (GFM)
Запускается с простого ярлыка на рабочем столе — не требуется знание командной строки
Обрабатывает заголовки, жирный/курсив/зачеркнутый текст, списки, списки задач, таблицы, цитаты, блоки кода, изображения и гиперссылки

См. MarkdownSyntax.md для получения полной информации о сопоставлении элементов и примечаний о том, что сохраняется, аппроксимируется или отбрасывается.

Related MCP server: Document Reading and Converter Tool

Требования

Windows 10/11
Python 3.11+
Следующие пакеты Python (устанавливаются через pip):

pip install markdown-it-py python-docx

Настройка

1. Клонируйте репозиторий

git clone https://github.com/cjwpenner/md-docx-converter.git
cd md-docx-converter

2. Установите зависимости

pip install markdown-it-py python-docx

3. Создайте ярлык на рабочем столе

pip install pywin32
python create_shortcut.py

Это создаст ярлык MD-DOCX Converter на вашем рабочем столе Windows. pywin32 нужен только для создания ярлыка — он не требуется для запуска самого конвертера.

4. Запустите конвертер

Дважды щелкните MD-DOCX Converter на рабочем столе. Откроется окно консоли с запросом:

MD ↔ DOCX Converter
--------------------
Enter file path:

Вставьте или введите полный путь к вашему файлу .md или .docx и нажмите Enter. Преобразованный файл будет сохранен в той же директории с измененным расширением.

Вы также можете запускать его прямо из командной строки:

python md_docx_converter/converter.py

Примечания по конвертации

Иерархия заголовков

Сопоставление уровней заголовков зависит от контекста:

MD → DOCX: Если в документе ровно один #, он становится Названием (Title) в Word. Все остальные заголовки сдвигаются на один уровень вниз. Если заголовков # несколько, все они становятся Заголовком 1 без Названия.
DOCX → MD: Если в документе есть стиль Название (Title), он становится #. Все заголовки сдвигаются вверх соответствующим образом. Если Названия нет, Заголовок 1 становится #.

Элементы с потерей данных

Форматирование Word, не имеющее эквивалента в Markdown, аппроксимируется как жирный шрифт:

Форматирование Word	Вывод Markdown
Подчеркивание	`жирный`
Выделение цветом	`жирный`
Капитель	`жирный`
Цвет шрифта	Удаляется (текст сохраняется)

Изображения

DOCX → MD: Внедренные изображения извлекаются в папку {filename}_images/ рядом с выходным файлом .md.
MD → DOCX: Изображения, на которые ссылаются по относительному пути, внедряются повторно. Отсутствующие изображения заменяются на [image not found: path].

Интеграция с Claude Code

Этот инструмент интегрируется с Claude Code либо как плагин (рекомендуется — все настраивается двумя командами), либо как автономный MCP-сервер (для ручной настройки или Claude Desktop).

Вариант А: Плагин Claude Code (рекомендуется)

Плагин объединяет конфигурацию MCP-сервера и навык /convert. Выполните эти две команды внутри Claude Code:

/plugin marketplace add cjwpenner/md-docx-converter
/plugin install md-docx-converter@md-docx-converter

Это все — дальнейшая настройка не требуется. После выполнения /reload-plugins Claude получит инструменты конвертации, и вы сможете вызывать навык напрямую:

/md-docx-converter:convert path/to/file.md
/md-docx-converter:convert path/to/report.docx

Или просто попросите естественным языком: "Convert this to a Word document", и Claude автоматически использует инструменты.

Вариант Б: Только MCP-сервер (ручная настройка)

Используйте этот вариант, если вам нужны только инструменты MCP без плагина или если вы настраиваете Claude Desktop, а не Claude Code.

Установите пакет:

pip install mcp-md-docx

Claude Code — зарегистрируйте MCP-сервер:

claude mcp add md-docx-converter --transport stdio -- uvx mcp-md-docx

Claude Desktop — добавьте в %APPDATA%\Claude\claude_desktop_config.json:

{
  "mcpServers": {
    "md-docx-converter": {
      "type": "stdio",
      "command": "uvx",
      "args": ["mcp-md-docx"]
    }
  }
}

Доступные инструменты

Инструмент	Что он делает
`read_docx`	Чтение файла `.docx` — возвращает полный текст Markdown для ИИ
`write_docx`	Создание `.docx` из текста Markdown, написанного ИИ
`convert_md_file_to_docx`	Преобразование файла `.md` на диске в `.docx`
`convert_docx_file_to_md`	Преобразование файла `.docx` на диске в `.md`

После настройки вы можете говорить, например:

"Read report.docx and summarise it"
"Turn this into a Word document and save it to my Desktop"
"Convert all the bullet points in notes.docx into a table"

Структура проекта

md_docx_converter/
├── converter.py       # CLI entry point
├── md_to_docx.py      # Markdown → Word conversion
├── docx_to_md.py      # Word → Markdown conversion
├── heading_mapper.py  # Heading hierarchy pre-scan logic
├── image_handler.py   # Image extraction and embedding
└── launch.pyw         # Desktop shortcut launcher
mcp_md_docx/
├── server.py          # MCP server (four tools)
└── __main__.py        # Entry point for python -m mcp_md_docx
create_shortcut.py     # One-time shortcut setup script
pyproject.toml         # PyPI packaging config

Лицензия

Этот проект лицензирован под GNU General Public License v3.0 (GPLv3). Вы можете свободно использовать, изменять и распространять это программное обеспечение при условии, что любые производные работы также распространяются на тех же условиях лицензии.

См. LICENSE для получения полного текста лицензии.

Сторонние библиотеки

Этот проект зависит от следующих библиотек с открытым исходным кодом, все они лицензированы по MIT:

Библиотека	Назначение	Лицензия
`mcp`	Фреймворк сервера Model Context Protocol	MIT
`markdown-it-py`	Парсер GitHub Flavored Markdown	MIT
`python-docx`	Чтение и запись файлов Word `.docx`	MIT

Полные тексты лицензий воспроизведены в THIRD _PARTY _NOTICES.md.

Available Tools

4 tools

convert_docx_file_to_mdA

Convert a Word (.docx) file to a Markdown (.md) file. The output is saved alongside the input file. Returns the Markdown content.

ParametersJSON Schema

Name	Required	Description	Default
`path`	Yes

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

TDQS

A4/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden. It discloses key behaviors: output file location (saved alongside input) and return value (Markdown content). However, it doesn't mention error handling, file size limits, format compatibility, or permission requirements, leaving gaps for a mutation tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with zero waste: first states core function, second adds crucial behavioral details (output location and return value). It's front-loaded with the primary purpose and efficiently covers additional context without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (file conversion), no annotations, and an output schema (which handles return values), the description is mostly complete. It covers purpose and key behaviors but lacks parameter details and some operational constraints, leaving minor gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It doesn't explain the 'path' parameter at all—no details on format, expected input type, or constraints. The description adds no parameter semantics beyond what the bare schema provides, failing to address the coverage gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action (convert), source format (.docx), target format (.md), and distinguishes from siblings like convert_md_file_to_docx (reverse operation) and read/write_docx (different actions). It precisely defines the tool's function without ambiguity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context (converting Word to Markdown) but doesn't explicitly state when to use this vs. alternatives like convert_md_file_to_docx or read_docx. It provides clear operational context but lacks explicit guidance on tool selection or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

convert_md_file_to_docxA

Convert a Markdown (.md) file to a Word (.docx) file. The output is saved alongside the input file with the same name and .docx extension.

ParametersJSON Schema

Name	Required	Description	Default
`path`	Yes

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

TDQS

A4.2/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden. It discloses the output location behavior (saved alongside input with same name and .docx extension), which is valuable. However, it doesn't mention error handling, file size limits, formatting preservation, or authentication requirements that might be relevant for a file conversion tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, zero waste. First sentence states the core purpose, second sentence provides crucial behavioral detail about output location. Perfectly front-loaded and appropriately sized for this simple tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has an output schema (which handles return values), a single parameter, and no annotations, the description is reasonably complete. It covers the conversion purpose and output location behavior. However, for a file operation tool, additional context about error conditions or limitations would make it more complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% (parameter 'path' has no description in schema), so the description must compensate. While it doesn't explicitly explain the 'path' parameter, the context makes it clear this should be the path to a Markdown file. The description adds meaning by specifying the file type (.md) and the conversion outcome, though it could be more explicit about parameter expectations.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action (convert), source format (Markdown .md file), and target format (Word .docx file). It distinguishes from sibling tools like convert_docx_file_to_md (reverse conversion) and read_docx/write_docx (different operations).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use this tool (converting from Markdown to Word format). It doesn't explicitly state when not to use it or name specific alternatives, but the sibling tool names make the distinction obvious (e.g., use convert_docx_file_to_md for reverse conversion).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

read_docxA

Read a Word (.docx) document and return its full content as Markdown text. Use this when the user asks you to read, summarise, edit, or work with a Word document.

ParametersJSON Schema

Name	Required	Description	Default
`path`	Yes

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

TDQS

A4.2/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It discloses the tool's behavior by stating it reads and returns content as Markdown, but lacks details on error handling, file size limits, or performance aspects. It adds basic context but does not fully compensate for the absence of annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose in the first sentence, followed by usage guidelines in the second. Both sentences are essential and waste no words, making it highly efficient and easy to scan.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (one parameter) and the presence of an output schema (which handles return values), the description is mostly complete. It covers purpose and usage well but could benefit from more behavioral details like error cases or limitations to fully compensate for the lack of annotations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 0%, so the description must compensate. It implies the 'path' parameter is for the document location but does not specify format or constraints. With only one parameter, the baseline is high, and the description adds some meaning by linking it to Word documents, though more detail would improve clarity.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Read a Word (.docx) document') and the resource type, with a precise outcome ('return its full content as Markdown text'). It distinguishes from siblings like 'convert_docx_file_to_md' by emphasizing reading rather than conversion, and from 'write_docx' by focusing on input rather than output.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use this tool ('when the user asks you to read, summarise, edit, or work with a Word document'), which covers common scenarios. However, it does not specify when not to use it or mention alternatives like 'convert_docx_file_to_md' for different purposes, leaving some ambiguity.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

write_docxA

Convert Markdown text to a Word (.docx) document and save it to disk. Use this when the user asks you to create or save a Word document from text or Markdown content. The output_path should be an absolute path ending in .docx.

ParametersJSON Schema

Name	Required	Description	Default
`markdown`	Yes
`output_path`	Yes

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

TDQS

A4.4/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses that the tool saves to disk (a behavioral trait) and specifies the output path format, but lacks details on error handling, file overwriting behavior, or performance characteristics. It adequately covers the core action but misses some operational nuances.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose, followed by usage guidance and parameter specifics in three concise sentences. Each sentence adds value without redundancy, making it efficient and well-structured for quick comprehension.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (2 parameters, no annotations, but has an output schema), the description is mostly complete. It covers purpose, usage, and parameter semantics adequately. The output schema likely handles return values, so the description doesn't need to explain those. Minor gaps remain in behavioral details like error handling.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description must compensate. It explains that 'markdown' is the input text and 'output_path' should be an absolute path ending in .docx, adding crucial semantic context beyond the bare schema. However, it doesn't detail markdown formatting support or path validation rules.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Convert Markdown text to a Word (.docx) document and save it to disk') and distinguishes it from siblings like 'convert_md_file_to_docx' (which likely processes files rather than text) and 'read_docx' (which reads rather than writes). It uses precise verbs and specifies the resource type.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use this tool ('when the user asks you to create or save a Word document from text or Markdown content'), providing clear context for its application. It also implies differentiation from siblings by focusing on text input rather than file processing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

4 tool updatesv0.1.2Apr 19, 2026
- First observedconvert_docx_file_to_md
- First observedconvert_md_file_to_docx
- First observedread_docx
- First observedwrite_docx

Deploy Server

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A3.9/5.0

Scored 2026-04-19 07:30 across 4 tools

Disambiguation2/5

The tools have significant overlap in purpose, particularly between convert_docx_file_to_md and read_docx (both convert DOCX to Markdown), and between convert_md_file_to_docx and write_docx (both convert Markdown to DOCX). The descriptions attempt to differentiate use cases (file conversion vs. content reading/writing), but an agent could easily misselect between these pairs due to unclear functional boundaries.

Naming Consistency4/5

The tool names follow a consistent verb_noun pattern with snake_case throughout (e.g., convert_docx_file_to_md, read_docx). The only minor deviation is that some names include 'file' while others do not, but overall the naming is predictable and readable.

Tool Count3/5

With 4 tools, the count is reasonable for a conversion-focused server, but it feels borderline thin given the overlapping functionality. A more streamlined set might have 2-3 tools instead, as the current count includes redundancy that doesn't add clear value to the surface.

Completeness4/5

For a DOCX-Markdown conversion domain, the tools cover the core bidirectional conversion operations and basic file handling. However, there are minor gaps, such as no tool for editing or manipulating the content in between conversions, which agents might need to work around by combining tools or external processing.

Maintenance

ActivitySlowing

ResponsivenessNo issues

Resources

Need Help?

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