Shadcn UI v4 MCP Server

The Shadcn UI v4 MCP Server addresses a common pain point for developers building AI‑powered coding assistants: the need to expose rich, framework‑specific UI component libraries in a way that an assistant can query and retrieve on demand. By packaging the full suite of shadcn/ui v4 components—alongside their Svelte, Vue, and React Native counterparts—into a single MCP endpoint, the server lets an AI assistant fetch component code, demos, and metadata without the user having to manually search GitHub or copy snippets. This eliminates friction in rapid prototyping and reduces the risk of version mismatches, as the server always pulls the latest source from the official repositories.

At its core, the server offers a set of intuitive resources that mirror the structure of each component library. A client can request the raw TypeScript implementation, the accompanying example usage, or a directory tree that shows how components are organized. The metadata endpoint supplies dependency lists, brief descriptions, and configuration hints, enabling an assistant to not only paste code but also explain how to integrate it into a project. The ability to browse directories directly means that the assistant can suggest entire blocks—such as dashboards, calendars, or forms—that are ready for copy‑and‑paste into a new application.

Key capabilities include:

• Multi‑framework support: One API call can retrieve React, Svelte, Vue, or React Native implementations, allowing the same assistant to serve developers across different stacks.
• Smart caching and rate‑limit handling: The server caches GitHub responses and respects API limits, ensuring reliable performance even under heavy usage.
• Component demos: Example implementations help developers understand context and usage patterns, making the assistant a more effective teaching tool.
• Metadata access: Dependency lists and configuration details enable automated environment setup, so the assistant can suggest installing the exact packages needed for a component.

Real‑world scenarios where this server shines include: an AI coding tutor that walks students through building a responsive dashboard in Svelte, or a collaborative pair‑programming session where an assistant instantly supplies the correct React Native component for a mobile form. In continuous integration pipelines, the server can be queried to verify that a newly added component complies with the latest shadcn/ui standards, catching regressions early.

Integration is straightforward within existing MCP‑compatible workflows. An AI assistant simply calls the appropriate resource endpoint, parses the returned JSON, and injects the code into the user’s editor or documentation. Because the server exposes a clean, version‑controlled source of truth, developers can trust that the snippets they receive are up to date and fully tested by the upstream maintainers. This level of reliability is a standout advantage over ad‑hoc copy‑paste methods, ensuring that AI assistants become a true extension of the developer’s toolchain rather than a temporary shortcut.