KS
Killer-Skills

ai-elements — Categories.community agent-tools, agents, ai-sdk, ai-sdk-agents, tanstack-ai, tanstack-ai-tools, tools

v1.0.0
GitHub

About this Skill

Ideal for AI Agents like Cursor and Claude Code needing pre-built UI components for AI-native applications Registry for AI agent tools with adapters for ai-sdk and tanstack-ai

# Core Topics

endalk200 endalk200
[1]
[0]
Updated: 3/1/2026

Quality Score

Top 5%
49
Excellent
Based on code quality & docs
Installation
SYS Universal Install (Auto-Detect)
Cursor IDE Windsurf IDE VS Code IDE
> npx killer-skills add endalk200/ai-registry/ai-elements

Agent Capability Analysis

The ai-elements MCP Server by endalk200 is an open-source Categories.community integration for Claude and other AI agents, enabling seamless task automation and capability expansion. Optimized for agent-tools, agents, ai-sdk.

Ideal Agent Persona

Ideal for AI Agents like Cursor and Claude Code needing pre-built UI components for AI-native applications

Core Value

Empowers agents to build conversations, messages, and more using shadcn/ui and adapters for ai-sdk and tanstack-ai, streamlining the development of AI-driven interfaces with seamless integration of custom registries

Capabilities Granted for ai-elements MCP Server

Building AI-powered chat interfaces
Creating custom AI-native application UI components
Integrating ai-sdk and tanstack-ai adapters for enhanced functionality

! Prerequisites & Limits

  • Requires shadcn/ui adoption
  • Limited to AI-native application development
Project
SKILL.md
6.6 KB
.cursorrules
1.2 KB
package.json
240 B
Ready
UTF-8
SKILL.md
Readonly

AI Elements

AI Elements is a component library and custom registry built on top of shadcn/ui to help you build AI-native applications faster. It provides pre-built components like conversations, messages and more.

Installing AI Elements is straightforward and can be done in a couple of ways. You can use the dedicated CLI command for the fastest setup, or integrate via the standard shadcn/ui CLI if you've already adopted shadcn's workflow.

Quick Start

Here are some basic examples of what you can achieve using components from AI Elements.

Prerequisites

Before installing AI Elements, make sure your environment meets the following requirements:

  • Node.js, version 18 or later
  • A Next.js project with the AI SDK installed.
  • shadcn/ui installed in your project. If you don't have it installed, running any install command will automatically install it for you.
  • We also highly recommend using the AI Gateway and adding AI_GATEWAY_API_KEY to your env.local so you don't have to use an API key from every provider. AI Gateway also gives $5 in usage per month so you can experiment with models. You can obtain an API key here.

Installing Components

You can install AI Elements components using either the AI Elements CLI or the shadcn/ui CLI. Both achieve the same result: adding the selected component’s code and any needed dependencies to your project.

The CLI will download the component’s code and integrate it into your project’s directory (usually under your components folder). By default, AI Elements components are added to the @/components/ai-elements/ directory (or whatever folder you’ve configured in your shadcn components settings).

After running the command, you should see a confirmation in your terminal that the files were added. You can then proceed to use the component in your code.

Usage

Once an AI Elements component is installed, you can import it and use it in your application like any other React component. The components are added as part of your codebase (not hidden in a library), so the usage feels very natural.

Example

After installing AI Elements components, you can use them in your application like any other React component. For example:

tsx
1"use client"; 2 3import { 4 Message, 5 MessageContent, 6 MessageResponse, 7} from "@/components/ai-elements/message"; 8import { useChat } from "@ai-sdk/react"; 9 10const Example = () => { 11 const { messages } = useChat(); 12 13 return ( 14 <> 15 {messages.map(({ role, parts }, index) => ( 16 <Message from={role} key={index}> 17 <MessageContent> 18 {parts.map((part, i) => { 19 switch (part.type) { 20 case "text": 21 return ( 22 <MessageResponse key={`${role}-${i}`}> 23 {part.text} 24 </MessageResponse> 25 ); 26 } 27 })} 28 </MessageContent> 29 </Message> 30 ))} 31 </> 32 ); 33}; 34 35export default Example;

In the example above, we import the Message component from our AI Elements directory and include it in our JSX. Then, we compose the component with the MessageContent and MessageResponse subcomponents. You can style or configure the component just as you would if you wrote it yourself – since the code lives in your project, you can even open the component file to see how it works or make custom modifications.

Extensibility

All AI Elements components take as many primitive attributes as possible. For example, the Message component extends HTMLAttributes<HTMLDivElement>, so you can pass any props that a div supports. This makes it easy to extend the component with your own styles or functionality.

Customization

After installation, no additional setup is needed. The component’s styles (Tailwind CSS classes) and scripts are already integrated. You can start interacting with the component in your app immediately.

For example, if you'd like to remove the rounding on Message, you can go to components/ai-elements/message.tsx and remove rounded-lg as follows:

tsx
1export const MessageContent = ({ 2 children, 3 className, 4 ...props 5}: MessageContentProps) => ( 6 <div 7 className={cn( 8 "flex flex-col gap-2 text-sm text-foreground", 9 "group-[.is-user]:bg-primary group-[.is-user]:text-primary-foreground group-[.is-user]:px-4 group-[.is-user]:py-3", 10 className 11 )} 12 {...props} 13 > 14 <div className="is-user:dark">{children}</div> 15 </div> 16);

Troubleshooting

Why are my components not styled?

Make sure your project is configured correctly for shadcn/ui in Tailwind 4 - this means having a globals.css file that imports Tailwind and includes the shadcn/ui base styles.

I ran the AI Elements CLI but nothing was added to my project

Double-check that:

  • Your current working directory is the root of your project (where package.json lives).
  • Your components.json file (if using shadcn-style config) is set up correctly.
  • You’re using the latest version of the AI Elements CLI:
bash
1npx ai-elements@latest

If all else fails, feel free to open an issue on GitHub.

Theme switching doesn’t work — my app stays in light mode

Ensure your app is using the same data-theme system that shadcn/ui and AI Elements expect. The default implementation toggles a data-theme attribute on the <html> element. Make sure your tailwind.config.js is using class or data- selectors accordingly:

The component imports fail with “module not found”

Check the file exists. If it does, make sure your tsconfig.json has a proper paths alias for @/ i.e.

json
1{ 2 "compilerOptions": { 3 "baseUrl": ".", 4 "paths": { 5 "@/*": ["./*"] 6 } 7 } 8}

My AI coding assistant can't access AI Elements components

  1. Verify your config file syntax is valid JSON.
  2. Check that the file path is correct for your AI tool.
  3. Restart your coding assistant after making changes.
  4. Ensure you have a stable internet connection.

Still stuck?

If none of these answers help, open an issue on GitHub and someone will be happy to assist.

Available Components

See the references/ folder for detailed documentation on each component.

Related Skills

Looking for an alternative to ai-elements or building a Categories.community AI Agent? Explore these related open-source MCP Servers.

View All

widget-generator

Logo of f
f

widget-generator is an open-source AI agent skill for creating widget plugins that are injected into prompt feeds on prompts.chat. It supports two rendering modes: standard prompt widgets using default PromptCard styling and custom render widgets built as full React components.

149.6k
0
Design

chat-sdk

Logo of lobehub
lobehub

chat-sdk is a unified TypeScript SDK for building chat bots across multiple platforms, providing a single interface for deploying bot logic.

73.0k
0
Communication

zustand

Logo of lobehub
lobehub

The ultimate space for work and life — to find, build, and collaborate with agent teammates that grow with you. We are taking agent harness to the next level — enabling multi-agent collaboration, effortless agent team design, and introducing agents as the unit of work interaction.

72.8k
0
Communication

data-fetching

Logo of lobehub
lobehub

The ultimate space for work and life — to find, build, and collaborate with agent teammates that grow with you. We are taking agent harness to the next level — enabling multi-agent collaboration, effortless agent team design, and introducing agents as the unit of work interaction.

72.8k
0
Communication