Local Utilities
Provides essential utility tools for text processing, file operations, and system tasks.
🛠️ Local Utilities MCP Server
A comprehensive Model Context Protocol (MCP) server built with FastMCP that provides essential utility tools for text processing, file operations, system tasks, and more.
🌟 Features
🌡️ Temperature Conversion
- Convert between Celsius and Fahrenheit
- High precision calculations with 2 decimal places
📁 File Operations
- Read text files with full content display
- Write content to files with automatic directory creation
- List directory contents with file sizes and icons
🔐 Security & Hashing
- Calculate MD5, SHA1, SHA256 hashes
- Hash text strings or entire file contents
- Base64 encoding and decoding
📊 Text Analysis
- Count words, characters, and lines
- Calculate detailed text statistics
- Average words per line and characters per word
🕒 Date & Time
- Get current date and time information
- Custom formatting with Python strftime
- Detailed breakdown (year, month, day, weekday, etc.)
🔑 Password Generation
- Generate secure passwords with customizable options
- Control length and character sets
- Include/exclude uppercase, lowercase, numbers, symbols
🚀 Quick Start
Prerequisites
- Python 3.8 or higher
- Compatible MCP client (LM Studio, Claude Desktop, etc.)
Installation
-
Clone the repository:
git clone https://github.com/aiforhumans/local-utils-mcp.git cd local-utils-mcp -
Create and activate a virtual environment:
python -m venv .venv # Windows .venv\Scripts\activate # macOS/Linux source .venv/bin/activate -
Install dependencies:
pip install -r requirements.txt
Running the Server
Start the MCP server:
python server.py
The server runs on stdio transport by default, which is compatible with most MCP clients.
🔧 Configuration
LM Studio Integration
Add this configuration to your LM Studio mcp.json file:
{
"mcpServers": {
"local-utils": {
"command": "python",
"args": ["path/to/your/server.py"],
"env": {}
}
}
}
Claude Desktop Integration
Add to your Claude Desktop configuration:
{
"mcpServers": {
"local-utils": {
"command": "python",
"args": ["path/to/your/server.py"]
}
}
}
📖 API Reference
Available Tools
convert_temp(value: float, unit: str)
Convert temperature between Celsius and Fahrenheit.
Parameters:
value: Temperature value to convertunit: "C" for Celsius to Fahrenheit, "F" for Fahrenheit to Celsius
Example:
convert_temp(25, "C") → "77.00 °F"
convert_temp(77, "F") → "25.00 °C"
read_file(file_path: str)
Read and return the contents of a text file.
Parameters:
file_path: Absolute or relative path to the file
Returns: File contents with path information
write_file(file_path: str, content: str)
Write content to a text file with automatic directory creation.
Parameters:
file_path: Path where to write the filecontent: Text content to write
list_directory(directory_path: str = ".")
List contents of a directory with file sizes.
Parameters:
directory_path: Path to directory (defaults to current directory)
Returns: Formatted list with file/folder icons and sizes
calculate_hash(text_or_path: str, hash_type: str = "sha256", is_file: bool = False)
Calculate cryptographic hash of text or file content.
Parameters:
text_or_path: Text string or file path to hashhash_type: "md5", "sha1", or "sha256" (default)is_file: Set totruewhen hashing a file
base64_encode_decode(text: str, operation: str = "encode")
Encode or decode text using Base64.
Parameters:
text: Text to encode/decodeoperation: "encode" or "decode"
get_datetime_info(format_string: str = "%Y-%m-%d %H:%M:%S")
Get comprehensive current date and time information.
Parameters:
format_string: Python strftime format string for custom formatting
text_stats(text: str)
Calculate detailed statistics for the given text.
Parameters:
text: Text to analyze
Returns: Lines, words, characters, and averages
generate_password(length: int = 12, include_uppercase: bool = True, include_lowercase: bool = True, include_numbers: bool = True, include_symbols: bool = False)
Generate a secure random password.
Parameters:
length: Password length (default: 12)include_uppercase: Include A-Z (default: true)include_lowercase: Include a-z (default: true)include_numbers: Include 0-9 (default: true)include_symbols: Include special characters (default: false)
🧪 Testing
Run the test suite to verify functionality:
python test.py
This will test all core functions and verify the server can be imported correctly.
🔨 Development
Adding New Tools
To extend the server with additional tools:
- Create a new function with the
@mcp.tool()decorator:
@mcp.tool(
description="Your tool description here"
)
async def your_new_tool(param1: str, param2: int = 10) -> str:
"""
Your tool implementation.
Args:
param1: Description of parameter 1
param2: Description of parameter 2 with default value
Returns:
String result of the tool operation
"""
try:
# Your tool logic here
result = f"Processed {param1} with value {param2}"
return result
except Exception as e:
return f"Error: {str(e)}"
- Add proper error handling and meaningful return messages
- Update the README with documentation for your new tool
- Test your tool to ensure it works correctly
Project Structure
local-utils-mcp/
├── server.py # Main MCP server
├── requirements.txt # Python dependencies
├── README.md # This file
├── .gitignore # Git ignore rules
├── test.py # Test suite
└── .venv/ # Virtual environment (not in git)
🤝 Contributing
Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.
- Fork the repository
- Create your feature branch (
git checkout -b feature/AmazingFeature) - Commit your changes (
git commit -m 'Add some AmazingFeature') - Push to the branch (
git push origin feature/AmazingFeature) - Open a Pull Request
📋 Requirements
- Python 3.8+
- FastMCP 2.9.0+
- MCP 1.9.4+
See requirements.txt for complete dependency list.
📄 License
This project is licensed under the MIT License - see the LICENSE file for details.
🔗 Related Projects
- FastMCP - The FastMCP framework used to build this server
- Model Context Protocol - Official MCP documentation
- LM Studio - Popular MCP client for local AI models
⭐ Support
If you find this project helpful, please consider giving it a star on GitHub!
Made with ❤️ for the MCP community
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