High-performance code intelligence MCP server. Indexes codebases into a persistent knowledge graph — average repo in milliseconds. 158 languages, sub-ms queries, 99% fewer tokens. Single static binary, zero dependencies.
MCP server for DaisyUI component docs
This repo runs a local MCP server that serves DaisyUI component documentation in small pieces. An agent can list available components or fetch one component’s full markdown docs when needed. The docs are stored locally under `components/`, and `update_components.py` can refresh them from DaisyUI’s public `llms.txt`. That keeps the context token-friendly while still letting the agent work with DaisyUI patterns and examples.
Builders who want Claude Code, Codex, Cursor, or any MCP-capable agent to use DaisyUI docs while they build interfaces.
You can design and implement DaisyUI UI without dumping the whole component library into your prompt.
What it does
Component listing
`list_components` returns the available DaisyUI components with short descriptions.
Component lookup
`get_component` returns the full markdown docs for one component, including classes, syntax, and examples.
Local markdown cache
Component docs live in the `components/` folder so the server can answer without repeated web fetches.
Doc refresh script
`update_components.py` pulls the latest DaisyUI docs from `llms.txt` and regenerates the component files.
Docker support
`Dockerfile` and `docker-compose.yml` let you run the MCP server in a container.
How to get it
- 1Run
git clone https://github.com/birdseyevue/fastmcp.git cd fastmcp
- 2Run
python -m venv venv # Windows venv\Scripts\activate # macOS/Linux source venv/bin/activate
- 3Run
pip install -r requirements.txt
- 4Upon first run, the MCP server will not have any component docs. Fetch them by running
python update_components.py
- 5Run
python mcp_server.py
- 6If DaisyUI releases new components or updates their docs, simply run
python update_components.py
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
🌼 Heads up
This repo has been a fun little project, and it's pretty cool seeing it hit 70+ stars and 15+ forks, thank you! But I wanted to let anyone new know that DaisyUI has finally released official "Skills" over at daisyui.com/docs/skill/. I now recommend using that one since it's official and, honestly, just better for modern AI models. This repo will still work if you're already using it, but for new projects I'd go with the official skill. I'd at least recommend you check it out and see if it fits your needs better. Thanks again for the support, and happy coding! 🌼
✨ 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
📁 Docker Configuration
{
"servers": {
"daisyui": {
"command": "docker",
"args": ["run", "-i", "--rm", "daisyui-mcp"]
}
}
}
🚀 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:
📁 Generic Configuration
{
"servers": {
"daisyui": {
"command": "<path-to-repo>/venv/Scripts/python.exe",
"args": ["<path-to-repo>/mcp_server.py"]
}
}
}
🪟 Windows Example
{
"servers": {
"daisyui": {
"command": "C:/Users/username/Downloads/fastmcp/venv/Scripts/python.exe",
"args": ["C:/Users/username/Downloads/fastmcp/mcp_server.py"]
}
}
}
🍎 macOS/Linux Example
{
"servers": {
"daisyui": {
"command": "/home/username/fastmcp/venv/bin/python",
"args": ["/home/username/fastmcp/mcp_server.py"]
}
}
}
📁 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
This project is licensed under the MIT License — see the LICENSE file for details.
Free to use, modify, and distribute! Have fun! 🎉
Made with ❤️ for the DaisyUI community
⭐ Star this repo if you find it useful!
Files in the repo
- components
- .gitignore
- docker-compose.yml
- Dockerfile
- LICENSE
- mcp_server.py
- README.md
- requirements.txt
- update_components.py
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