by jackdark425
Convert Markdown to professional Word (.docx) with math, custom styles, tables, images, headers/footers and watermarks —
Converts Markdown documents to professionally formatted Word documents with support for math formulas, custom styling, tables, images, and headers/footers.
AI Group Markdown to Word MCP Server is a community-built MCP server published by jackdark425 that provides AI assistants with tools and capabilities via the Model Context Protocol. Convert Markdown to professional Word (.docx) with math, custom styles, tables, images, headers/footers and watermarks — It is categorized under productivity. This server exposes 4 tools that AI clients can invoke during conversations and coding sessions.
You can install AI Group Markdown to Word MCP Server in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
MIT
AI Group Markdown to Word MCP Server is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
AI Group Markdown to Word MCP Server reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
We wired AI Group Markdown to Word MCP Server into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
According to our notes, AI Group Markdown to Word MCP Server benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
We wired AI Group Markdown to Word MCP Server into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
AI Group Markdown to Word MCP Server is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
AI Group Markdown to Word MCP Server is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
According to our notes, AI Group Markdown to Word MCP Server benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Useful MCP listing: AI Group Markdown to Word MCP Server is the kind of server we cite when onboarding engineers to host + tool permissions.
Strong directory entry: AI Group Markdown to Word MCP Server surfaces stars and publisher context so we could sanity-check maintenance before adopting.
AI Group Markdown to Word MCP Server is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
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A comprehensive Model Context Protocol (MCP) server for converting Markdown documents to professional Word documents with advanced formatting, styling, and layout capabilities.
# Using npx (recommended for one-time use)
npx -y aigroup-mdtoword-mcp
# Or install globally
npm install -g aigroup-mdtoword-mcp
Add to your Claude Desktop configuration (claude_desktop_config.json):
{
"mcpServers": {
"markdown-to-word": {
"command": "npx",
"args": ["-y", "aigroup-mdtoword-mcp"]
}
}
}
{
"mcpServers": {
"markdown-to-word": {
"command": "uvx",
"args": ["aigroup-mdtoword-mcp"]
}
}
}
Convert Markdown content to Word document with full styling support.
Input Schema:
{
markdown?: string; // Markdown content (required if inputPath not provided)
inputPath?: string; // Path to Markdown file
filename: string; // Output filename (without extension)
outputPath?: string; // Custom output directory
styleConfig?: StyleConfig; // Advanced styling configuration
}
Example Usage:
Convert this markdown to a Word document:
# Project Report
## Executive Summary
This is a sample report with **bold text** and *italic text*.
- Feature 1: Complete Markdown support
- Feature 2: Advanced styling system
- Feature 3: Professional document layout
| Column 1 | Column 2 | Column 3 |
|----------|----------|----------|
| Data 1 | Data 2 | Data 3 |
| Data 4 | Data 5 | Data 6 |
Mathematical formula: $E = mc^2$
Convert structured data (CSV/JSON) to formatted Markdown tables.
Input Schema:
{
data: string; // CSV or JSON data
format: 'csv' | 'json'; // Data format
style?: string; // Table style preset
hasHeader?: boolean; // Whether data includes headers
}
template://customer-analysis - Business analysis report templatetemplate://academic - Academic paper templatetemplate://business - Professional business reporttemplate://technical - Technical documentationtemplate://minimal - Clean minimal templatestyle-guide://quick-start - Quick styling referencestyle-guide://advanced - Advanced styling optionsstyle-guide://templates - Template usage guidemetrics://conversion-stats - Conversion performance datametrics://memory-usage - Memory usage statistics{
document: {
defaultFont: "宋体",
defaultSize: 24,
defaultColor: "000000",
page: {
size: "A4",
orientation: "portrait",
margins: { top: 1440, bottom: 1440, left: 1440, right: 1440 }
}
},
headingStyles: {
h1: { font: "黑体", size: 64, color: "000000", bold: true },
h2: { font: "黑体", size: 32, color: "000000", bold: true }
}
}
The server includes 12 professionally designed table styles:
Full style configuration supports:
src/
├── index.ts # Main MCP server implementation
├── converter/
│ └── markdown.ts # Markdown to DOCX converter
├── template/
│ └── presetLoader.ts # Template system
├── types/
│ ├── index.ts # Core types
│ ├── style.ts # Style configuration types
│ └── template.ts # Template types
└── utils/
├── tableProcessor.ts # Table processing utilities
├── mathProcessor.ts # Mathematical formula processing
├── imageProcessor.ts # Image handling utilities
├── styleEngine.ts # Style application engine
└── errorHandler.ts # Error handling utilities
Run the test suite:
npm test
Available test scenarios:
We welcome contributions! Please see our Contributing Guidelines for details.
This project is licensed under the MIT License - see the LICENSE file for details.
This project supports deployment to Cloudflare Workers. Follow these steps to deploy:
npm install -g wranglerwrangler loginUpdate wrangler.toml with your account ID:
[env.production]
account_id = "your-account-id-here" # Replace with your Cloudflare account ID
Deploy to Cloudflare Workers:
wrangler deploy
After deployment, your service will be accessible via:
https://your-worker.your-subdomain.workers.dev/ - Main info pagehttps://your-worker.your-subdomain.workers.dev/health - Health checkhttps://your-worker.your-subdomain.workers.dev/mcp - MCP protocol endpointhttps://your-worker.your-subdomain.workers.dev/convert - Simplified HTTP APIhttps://your-worker.your-subdomain.workers.dev/.well-known/ai-plugin.json - OpenAI plugin manifesthttps://your-worker.your-subdomain.workers.dev/openapi.yaml - OpenAPI specification (YAML)https://your-worker.your-subdomain.workers.dev/openapi.json - OpenAPI specification (JSON)https://your-worker.your-subdomain.workers.dev/logo.png - Plugin logoFor detailed deployment instructions, see docs/DEPLOYMENT_INSTRUCTIONS.md.
**AI Group Markdown to Word MC
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.