analytics-data

Word Counter

by qpd-v

Use our Word Counter to quickly count the words in Word docs. Get accurate word and character counts with this word coun

Analyze text documents, including counting words and characters, through Node.js.

github stars

10

Privacy-focused — content not exposed to LLMsLocal file processing

best for

  • / Writers tracking document length
  • / Content editors analyzing text metrics
  • / Students checking assignment word counts

capabilities

  • / Count words in text documents
  • / Count characters including spaces
  • / Count characters excluding spaces
  • / Process local text files directly

what it does

Analyzes text files to count words and characters without exposing file content to LLMs. Processes documents locally through a simple Node.js interface.

about

Word Counter is a community-built MCP server published by qpd-v that provides AI assistants with tools and capabilities via the Model Context Protocol. Use our Word Counter to quickly count the words in Word docs. Get accurate word and character counts with this word coun It is categorized under analytics data. This server exposes 1 tool that AI clients can invoke during conversations and coding sessions.

how to install

You can install Word Counter 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.

license

Apache-2.0

Word Counter is released under the Apache-2.0 license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

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:
• Word count: 150
• Character count (including spaces): 842
• 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.

FAQ

What is the Word Counter MCP server?
Word Counter is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Word Counter?
This profile displays 10 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
MCP server reviews

Ratings

4.510 reviews
  • Shikha Mishra· Oct 10, 2024

    Word Counter is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Piyush G· Sep 9, 2024

    We evaluated Word Counter against two servers with overlapping tools; this profile had the clearer scope statement.

  • Chaitanya Patil· Aug 8, 2024

    Useful MCP listing: Word Counter is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Sakshi Patil· Jul 7, 2024

    Word Counter reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Ganesh Mohane· Jun 6, 2024

    I recommend Word Counter for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Oshnikdeep· May 5, 2024

    Strong directory entry: Word Counter surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Dhruvi Jain· Apr 4, 2024

    Word Counter has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Rahul Santra· Mar 3, 2024

    According to our notes, Word Counter benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Pratham Ware· Feb 2, 2024

    We wired Word Counter into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Yash Thakker· Jan 1, 2024

    Word Counter is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.