README.md

metadata

title: Text Counting MCP Server
emoji: 🔢
colorFrom: blue
colorTo: green
sdk: gradio
sdk_version: 4.44.1
app_file: mcp_server.py
pinned: false

Text Counting MCP Server

A comprehensive text analysis and counting operations server built with Gradio, featuring both a web interface and MCP (Model Context Protocol) server capabilities.

Features

This application provides 13 different text counting and analysis functions:

• Letter Counter: Count alphabetic characters in text
• Word Counter: Count words in sentences or paragraphs
• Sentence Counter: Count sentences using multiple punctuation marks (., !, ?)
• Paragraph Counter: Count paragraphs separated by double line breaks
• Vowel Counter: Count vowel characters (a, e, i, o, u)
• Consonant Counter: Count consonant characters
• Special Character Counter: Count special symbols and punctuation
• Digit Counter: Count numeric digits (0-9)
• Whitespace Counter: Count spaces, tabs, and line breaks
• Uppercase Letter Counter: Count capital letters
• Lowercase Letter Counter: Count lowercase letters
• Unique Word Counter: Count distinct words in text
• Syllable Counter: Estimate syllables with enhanced algorithm

Quick Start

Prerequisites

• Python 3.8+
• pip package manager

Installation

1. Clone or download the project

   git clone <repository-url>
   cd hugging-face
   

2. Create and activate virtual environment (recommended)

   python -m venv .venv
   
   # On Windows:
   .venv\Scripts\activate
   
   # On macOS/Linux:
   source .venv/bin/activate
   

3. Install dependencies

   pip install gradio
   

Running the Application

Web Interface Mode:

python mcp_server.py

The application will launch at http://localhost:7860 with a tabbed interface for each counting function.

MCP Server Mode:

# Enable MCP server functionality by setting mcp_server=True in the code
python mcp_server.py

Usage Examples

Web Interface

1. Navigate to the launched URL (typically http://localhost:7860)
2. Select the desired counting function from the tabs
3. Enter your text in the input field
4. View the results instantly

Python API

from mcp_server import count_letters, count_words, count_syllables

# Count letters
result = count_letters("Hello World!")  # Returns: 10

# Count words  
result = count_words("This is a test sentence.")  # Returns: 5

# Count syllables
result = count_syllables("beautiful")  # Returns: 3

Project Structure

hugging-face/
├── mcp_server.py          # Main application with Gradio interface
├── mcp.json              # MCP server configuration
├── agent.json            # Agent configuration
├── README.md             # This file
├── .gitignore           # Git ignore rules
└── .venv/               # Virtual environment (created after setup)

Configuration

MCP Server Configuration

The mcp.json file defines the MCP server capabilities and tool definitions. It includes:

• Server metadata (name, version, description)
• Tool definitions with parameter schemas
• Capability declarations

Environment Setup

• Python virtual environment in .venv/
• Gradio for web interface
• MCP server capabilities built into Python application

Function Details

Enhanced Features

1. Robust Input Handling: All functions accept any input type and convert to string
2. Improved Algorithms:
   • Sentence counting uses regex for multiple punctuation marks
   • Syllable counting handles silent 'e' and edge cases
3. Error Handling: Functions gracefully handle empty inputs and special cases
4. Type Safety: Full type hints and comprehensive docstrings

Algorithm Highlights

• Syllable Counter: Uses vowel grouping with silent 'e' detection
• Sentence Counter: Regex-based splitting on .!? patterns
• Letter Counter: Only counts alphabetic characters (excludes numbers/symbols)

Development

Code Quality Features

• Complete type hints for all functions
• Comprehensive docstrings with Args: blocks
• Input validation and type conversion
• Error handling for edge cases
• Consistent code formatting

Adding New Functions

1. Define the function with proper type hints
2. Add comprehensive docstring with Args: and Returns: sections
3. Include input validation (str(input) conversion)
4. Add the function to the Gradio interface
5. Update MCP configuration if needed

Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/new-counter)
3. Make your changes following the code quality standards
4. Add tests if applicable
5. Submit a pull request

License

This project is licensed under the ISC License - see the LICENSE file for details.

Troubleshooting

Common Issues

"ModuleNotFoundError: No module named 'gradio'"

pip install gradio

"JSON-RPC error: Not Acceptable: Client must accept text/event-stream"

• This occurs when mcp_server=True is enabled but the client doesn't support event streams
• For web interface only, ensure mcp_server=False or remove the parameter

Virtual Environment Issues

# Recreate virtual environment
rm -rf .venv
python -m venv .venv
.venv\Scripts\activate  # Windows
pip install gradio

Performance

• Lightweight algorithms optimized for text processing
• Efficient character iteration using generator expressions
• Memory-efficient for large text inputs
• Real-time processing suitable for interactive use

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Built using Python, Gradio, and MCP