Daisyui MCP
A local MCP server that specifically provides DaisyUI component documentation, enabling efficient token usage through tool calls and supporting queries for component lists and access to detailed documentation.
rating : 2 points
downloads : 3.3K
What is the DaisyUI MCP Server?
The DaisyUI MCP Server is a locally running Model Context Protocol server that specifically provides documentation and reference information for the DaisyUI component library to AI assistants (such as Claude, ChatGPT, etc.). It allows your AI assistant to understand and use various UI components of DaisyUI, helping you quickly build beautiful web interfaces.How to use the DaisyUI MCP Server?
You only need to install and run this server locally, and then add the corresponding MCP server settings to the configuration of your AI assistant. After that, your AI assistant can access the detailed documentation of more than 60 DaisyUI components, including usage methods, code examples, and style class names.Use Cases
When you need an AI assistant to help you: 1) Design web interfaces; 2) Write DaisyUI component code; 3) Understand the usage and styles of DaisyUI components; 4) Quickly build prototypes or complete projects.Main Features
Save Token Usage
Provide component documentation on - demand through the MCP tool instead of sending all content at once, significantly reducing token consumption in AI conversations.
Full Component Coverage
Supports all more than 60 components of DaisyUI, including common UI elements such as buttons, cards, modals, tables, forms, etc.
Automatically Update Documentation
You can obtain the latest component documentation from the official DaisyUI at any time to ensure that you are using the latest version of information.
Highly Customizable
You can edit the existing component documentation or add your own custom components to meet specific project requirements.
Fast and Lightweight
Built on FastMCP, it runs fast and consumes few resources, suitable for long - term local operation.
Advantages
Completely free to use, based on an open - source license
Runs locally, ensuring data privacy
Save tokens in AI conversations and improve efficiency
Documentation can be customized to meet project requirements
Keep in sync with the official DaisyUI for updates
Limitations
Relatively basic functions, no advanced interactive features
Requires local installation and configuration
Does not include the advanced features of the official DaisyUI Blueprint MCP
Requires basic knowledge of command - line operations
How to Use
Download and Install
Clone the project repository and install Python dependencies. It is recommended to use a virtual environment to manage dependencies.
Get Component Documentation
You need to obtain the DaisyUI component documentation before the first run. This will download the latest component information from the official source.
Run the MCP Server
Start the local MCP server so that the AI assistant can connect and access the component documentation.
Configure the AI Assistant
Add the MCP server settings to the configuration of your AI assistant (such as Claude Desktop). You need to adjust the path according to your operating system.
Usage Examples
Quickly Understand Available Components
When you are not sure what components DaisyUI provides, you can ask the AI assistant to list all available components.
Get Specific Component Usage
When you need to understand the detailed usage and code examples of a specific component.
Build a Complete Page
Ask the AI assistant to help you build a complete page or component combination using DaisyUI.
Frequently Asked Questions
What is the difference between this server and the official DaisyUI Blueprint MCP?
Do I need to install DaisyUI?
How to update the component documentation?
Which AI assistants are supported?
Can I add my own component documentation?
Related Resources
DaisyUI Official Website
Official documentation and demos of DaisyUI
Model Context Protocol
Official documentation and specifications of the MCP protocol
GitHub Repository
Source code and latest version of this project
FastMCP Framework
The MCP server framework used in this project

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