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
<div align="center">
🌼 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
</div>
✨ 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)
🤝 Contributing
Contributions are welcome! Feel free to:
- 🐛 Report bugs
- 💡 Suggest new features
- 📝 Improve documentation
- 🔧 Submit pull requests
📄 License
<div align="center">
This project is licensed under the MIT License — see the LICENSE file for details.
Free to use, modify, and distribute! Have fun! 🎉
</div>
<div align="center">
Made with ❤️ for the DaisyUI community
⭐ Star this repo if you find it useful!
</div>
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.
