Auto Favicon MCP Server
# Auto Favicon MCP Server
An MCP (Model Context Protocol) server that automatically generates complete favicon sets from PNG images or URLs. This server creates a comprehensive set of favicon files including various sizes, Apple touch icons, and a manifest.json file.
## Features
- **PNG to Favicon**: Generate favicon sets from local PNG files
- **URL to Favicon**: Download images from URLs and generate favicon sets
- **Complete Icon Set**: Creates multiple sizes (16x16, 32x32, 48x48, 64x64, 128x128, 256x256)
- **ICO Format**: Generates traditional favicon.ico files
- **Apple Touch Icons**: Creates Apple-specific touch icons for iOS devices
- **Web App Manifest**: Generates manifest.json for Progressive Web Apps
## Installation & Usage
### MCP Client Configuration
Add to your MCP client configuration:
```json
{
"mcpServers": {
"favicon-generator": {
"command": "uvx",
"args": ["auto-favicon"],
"env": {}
}
}
}
```
## Available Tools
- `generate_favicon_from_png`: Generate favicon set from a local PNG file
- `generate_favicon_from_url`: Download image from URL and generate favicon set
## Requirements
- Python 3.12+
- uv package manager
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: one processes a local PNG file, while the other downloads an image from a URL. There is no ambiguity or overlap in their functionality, making it easy for an agent to choose the correct tool based on the input source.
Both tools follow a consistent verb_noun pattern with 'generate_favicon_from_' prefix, using snake_case throughout. The naming is predictable and clearly indicates the action (generate) and the source (png or url), ensuring readability and coherence.
With only 2 tools, the server feels thin for a favicon generation domain, as it might lack operations like validation, customization (e.g., size adjustments), or cleanup. However, it covers the core functionality of generating favicons from different sources, which is reasonable but minimal.
The server covers the basic generation from PNG and URL sources, but there are notable gaps such as support for other image formats (e.g., JPEG, SVG), customization options (e.g., specifying sizes), or error handling tools. This limits flexibility but allows for core workflows.