MCP 服务器

DaisyUI MCP Server

A token-efficient local MCP server that exposes DaisyUI component documentation via tools, enabling AI assistants to build UIs using DaisyUI components.

README

🌼 DaisyUI MCP Server

A token-friendly local MCP server for DaisyUI component documentation

Give your AI assistant the power to build beautiful UIs with DaisyUI 🚀

Features • Installation • Docker • Usage • Configuration

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✨ Features

🎯 Token-Efficient — Only exposes relevant context via MCP tools, saving precious tokens
📚 60+ Components — Full coverage of DaisyUI's component library
🔄 Auto-Updatable — Fetch the latest docs anytime with one command
✏️ Customizable — Edit or add your own component docs to fit your project
⚡ Fast & Lightweight — Built with FastMCP for optimal performance

🛠️ MCP Tools

This server exposes two tools that AI assistants can use:

Tool	Description
`list_components`	📋 Lists all available DaisyUI components with short descriptions
`get_component`	📖 Gets the full documentation for a specific component (classes, syntax, examples)

💡 The component docs are pulled from daisyui.com/llms.txt and stored locally as markdown files. This way you can also add your own custom components or edit existing ones to your liking or project needs.

💬 Example Prompts

Try asking your AI assistant:

"What DaisyUI components are available?"

"Implement a responsive card grid using DaisyUI"

"How does the modal component work? Show me an example"

📦 Installation

1. Clone the repository

git clone https://github.com/birdseyevue/fastmcp.git
cd fastmcp

2. Create a virtual environment (recommended)

python -m venv venv

# Windows
venv\Scripts\activate

# macOS/Linux
source venv/bin/activate

3. Install dependencies

pip install -r requirements.txt

🐳 Docker

You can also run the MCP server using Docker.

Build and run with Docker

docker build -t daisyui-mcp .
docker run -i --rm daisyui-mcp

Using Docker Compose

docker compose up --build

The docker-compose.yml mounts the local components/ directory as a volume, so any changes you make to component docs on the host are reflected inside the container.

Docker configuration for AI assistants

<details> <summary><b>📁 Docker Configuration</b></summary>

{
  "servers": {
    "daisyui": {
      "command": "docker",
      "args": ["run", "-i", "--rm", "daisyui-mcp"]
    }
  }
}

</details>

🚀 Usage

First-time setup

Upon first run, the MCP server will not have any component docs. Fetch them by running:

python update_components.py

This fetches the latest llms.txt from DaisyUI and generates all the markdown files in /components.

Running the server

python mcp_server.py

Updating component docs

If DaisyUI releases new components or updates their docs, simply run:

python update_components.py

⚙️ Configuration

Add the MCP server to your AI assistant's configuration:

<details> <summary><b>📁 Generic Configuration</b></summary>

{
  "servers": {
    "daisyui": {
      "command": "<path-to-repo>/venv/Scripts/python.exe",
      "args": ["<path-to-repo>/mcp_server.py"]
    }
  }
}

</details>

<details> <summary><b>🪟 Windows Example</b></summary>

{
  "servers": {
    "daisyui": {
      "command": "C:/Users/username/Downloads/fastmcp/venv/Scripts/python.exe",
      "args": ["C:/Users/username/Downloads/fastmcp/mcp_server.py"]
    }
  }
}

</details>

<details> <summary><b>🍎 macOS/Linux Example</b></summary>

{
  "servers": {
    "daisyui": {
      "command": "/home/username/fastmcp/venv/bin/python",
      "args": ["/home/username/fastmcp/mcp_server.py"]
    }
  }
}

</details>

📁 Project Structure

fastmcp/
├── 🐍 mcp_server.py          # The MCP server
├── 🔄 update_components.py   # Script to fetch/update component docs
├── 📋 requirements.txt       # Dependencies (just fastmcp)
├── 🐳 Dockerfile             # Docker image definition
├── 🐳 docker-compose.yml     # Docker Compose configuration
└── 📂 components/            # Markdown files for each component
    ├── button.md
    ├── card.md
    ├── modal.md
    ├── table.md
    └── ... (60+ components)