Markdown Word Counter Mcp

Markdown Word Counter MCP Server

A Model Context Protocol (MCP) server that provides word counting functionality for Markdown files, with support for both Chinese characters and English words.

Features

• Accurate Word Counting: Properly handles both Chinese characters and English words
• Minimal Processing by Default: Only normalizes whitespace, preserves all content
• Configurable Processing: Control what gets processed with flexible options
• Markdown-Aware: Optionally removes Markdown syntax while preserving content
• HTML Tag Removal: Optionally strips HTML tags from content
• Link Processing: Optionally extracts text from Markdown links
• Two Tools Available:
  • count_words: Get total word count with options
  • detailed_word_count: Get detailed statistics with processing info

Processing Options

By default, only whitespace is normalized. All other processing is optional:

• remove_html_tags (default: false) - Remove HTML tags like <div>, <p>
• process_markdown_links (default: false) - Extract text from [text](url) links
• remove_markdown_headers (default: false) - Remove header markers #, ##, etc.
• remove_markdown_lists (default: false) - Remove list markers -, *, +
• normalize_whitespace (default: true) - Collapse multiple spaces/newlines

Installation

1. Clone or download this repository
2. Install dependencies:

   npm install
   

3. Build the project:

   npm run build
   

Usage

As MCP Server

Add to your MCP client configuration (e.g., mcp_settings.json):

{
  "mcpServers": {
    "markdown-word-counter": {
      "command": "node",
      "args": [
        "/path/to/markdown-word-counter-mcp/build/index.js"
      ]
    }
  }
}

Available Tools

count_words

Count total words in a Markdown file.

Parameters:

• file_path (string, required): Path to the Markdown file
• remove_html_tags (boolean, optional): Remove HTML tags (default: false)
• process_markdown_links (boolean, optional): Process Markdown links (default: false)
• remove_markdown_headers (boolean, optional): Remove headers (default: false)
• remove_markdown_lists (boolean, optional): Remove list markers (default: false)
• normalize_whitespace (boolean, optional): Normalize whitespace (default: true)

Example (Default - Minimal Processing):

{
  "file_path": "document.md"
}

Example (Enable All Processing):

{
  "file_path": "document.md",
  "remove_html_tags": true,
  "process_markdown_links": true,
  "remove_markdown_headers": true,
  "remove_markdown_lists": true
}

detailed_word_count

Get detailed word count statistics with processing information.

Parameters:

• Same as count_words

Example:

{
  "file_path": "document.md",
  "remove_markdown_headers": false
}

Standalone Usage

You can also run the server directly:

npm start

Development

• npm run dev: Watch mode for development
• npm run build: Build the TypeScript code
• npm start: Run the built server

Word Counting Logic

The server uses the following logic to count words:

1. Remove HTML tags: Strips all HTML markup
2. Process Markdown links: Extracts link text, removes URLs
3. Remove Markdown syntax: Headers (#), lists (-, *, +)
4. Normalize whitespace: Collapses multiple spaces
5. Count separately:
   • Chinese characters: Using Unicode range [\u4e00-\u9fa5]
   • English words: Using word boundaries \b\w+\b
6. Sum totals: Chinese chars + English words = Total words

Examples

Default Processing (Minimal - Only Normalize Whitespace)

For a file containing:

# Hello 世界

This is a [link](http://example.com) with **bold** text.

- 中文测试
- English test

Default result (preserves all Markdown syntax):

• Chinese Characters: 4 (中文测试)
• English Words: 13 (Hello This is a link http example com with bold text English test)
• Total Words: 17

Full Processing (All Options Enabled)

Same file with all processing enabled:

{
  "file_path": "document.md",
  "remove_html_tags": true,
  "process_markdown_links": true,
  "remove_markdown_headers": true,
  "remove_markdown_lists": true,
  "normalize_whitespace": true
}

Result with full processing:

• Chinese Characters: 4 (世界中文测试)
• English Words: 7 (Hello This is a link with bold text English test)
• Total Words: 11

License

MIT