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import { generateMetadata } from "../utils/metadata"
export const metadata = generateMetadata( "Model Context Protocol", "Use prompt-kit components directly in your AI tools through MCP." )
The Model Context Protocol (MCP) allows AI tools to access prompt-kit components directly. This enables you to browse, preview, and add components without leaving your coding environment.
MCP is an open protocol that standardizes how applications provide context to LLMs. Think of it as a plugin system that connects your AI tools to external data sources and tools.
Learn more about MCP:
The setup process depends on your AI tool.
.cursor/mcp.json file in your project root<CodeBlock
language="json"
code={{ "mcpServers": { "prompt-kit": { "description": "prompt-kit registry", "type": "stdio", "command": "npx", "args": ["-y", "shadcn@canary", "registry:mcp"], "env": { "REGISTRY_URL": "https://www.prompt-kit.com/c/registry.json" } } } }}
/>
For other AI tools that support MCP, refer to their specific documentation on how to configure MCP servers. Use the same server configuration above, adapting the file location as needed.
Once configured, you can start using the prompt-kit components in your AI tool's chat.
<CodeBlock language="text" code="Add the PromptInput component from prompt-kit to my project" />
<CodeBlock language="text" code="Show me the documentation and preview for the PromptTextarea component" />
<CodeBlock language="text" code="Build a chat app with prompt-kit using: ChatContainer with ScrollButton inside, plus Message and PromptInput" />
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