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Mcp Wordcounter

@qpd-von a year ago
9 Apache-2.0
FreeCommunity
AI Systems
A Model Context Protocol server for analyzing text documents with word and character counting capabilities

Overview

What is Mcp Wordcounter

mcp-wordcounter is a Model Context Protocol server designed for analyzing text documents, providing functionalities for counting words and characters.

Use cases

Use cases for mcp-wordcounter include analyzing text documents for academic purposes, content creation, and any scenario where text statistics are needed for better understanding or processing of text data.

How to use

To use mcp-wordcounter, you can run it as a CLI tool with the command ‘npx mcp-wordcounter’. Alternatively, you can integrate it into Claude Desktop by adding it to your configuration file.

Key features

Key features include counting words in documents, counting total characters (including spaces), counting characters excluding spaces, and processing files directly without exposing content to LLMs.

Where to use

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Content

MCP Word Counter

A Model Context Protocol server that provides tools for analyzing text documents, including counting words and characters. This server helps LLMs perform text analysis tasks by exposing simple document statistics functionality.

Features

  • Count words in documents
  • Count total characters (including spaces)
  • Count characters excluding spaces
  • Process files directly without exposing content to LLMs

Installation

npm install mcp-wordcounter

Usage

As a CLI tool

npx mcp-wordcounter

In Claude Desktop

Add to your Claude Desktop configuration (claude_desktop_config.json):

{
  "mcpServers": {
    "mcp-wordcounter": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-wordcounter"
      ],
      "alwaysAllow": [
        "analyze_text"
      ]
    }
  }
}

Available Tools

analyze_text

Counts words and characters in a text document.

Parameters:

  • filePath (string, required): Path to the text file to analyze

Returns:

  • Word count
  • Character count (including spaces)
  • Character count (excluding spaces)

Example response:

{
  "content": [
    {
      "type": "text",
      "text": "Analysis Results:\n• Word count: 150\n• Character count (including spaces): 842\n• Character count (excluding spaces): 702"
    }
  ]
}

Development

# Install dependencies
npm install

# Build the project
npm run build

# Run in watch mode during development
npm run watch

# Test with MCP Inspector
npm run inspector

License

MIT License - see LICENSE file for details.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Tools

No tools

Comments

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