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MCP Servers · Jpisnice

shadcn-ui-mcp-server

An MCP server that exposes shadcn/ui component source code, metadata, and examples to AI assistants. Supports React, Svelte, Vue, and React Native implementations with multi-framework switching and optional GitHub API integration for higher rate limits.

Talk to DEV.co Discuss Implementation

Source: GitHub — github.com/Jpisnice/shadcn-ui-mcp-server

2.8k

GitHub stars

296

Forks

TypeScript

Primary language

MIT

License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

Field	Value
Repository	Jpisnice/shadcn-ui-mcp-server
Owner	Jpisnice
Primary language	TypeScript
License	MIT — OSI-approved
Stars	2.8k
Forks	296
Open issues	3
Latest release	v2.0.0 (2026-01-30)
Last updated	2026-05-16
Source	https://github.com/Jpisnice/shadcn-ui-mcp-server

What shadcn-ui-mcp-server is

TypeScript-based Model Context Protocol server providing programmatic access to shadcn/ui v4 components via GitHub API integration. Supports stdio and SSE transports, smart caching, and Docker deployment with configurable UI primitive libraries (Radix/Base for React).

Quickstart

Get the shadcn-ui-mcp-server source

Clone the repository and explore it locally.

terminalbash

1git clone https://github.com/Jpisnice/shadcn-ui-mcp-server.git2cd shadcn-ui-mcp-server3# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

AI-Assisted UI Development

Provide Claude, ChatGPT, or other LLMs real-time access to shadcn/ui component implementations, enabling AI to generate production-ready component code with correct dependencies and usage patterns.

Multi-Framework Component Reference

Enable development teams to compare and learn shadcn implementations across React, Svelte, Vue, and React Native from a single MCP server, useful for polyglot teams or framework migration projects.

Production AI Deployment

Deploy via Docker Compose with SSE transport to support multiple concurrent LLM clients in enterprise environments, with health checks and GitHub token-based rate limit management.

Implementation considerations

GitHub token provisioning and rotation must be managed securely; avoid hardcoding tokens in deployment configs. Use environment variables or secrets management systems.
SSE transport in production requires proper CORS configuration, SSL/TLS termination, and load balancer setup if scaling to multiple server instances.
Component metadata caching reduces GitHub API calls but may lag behind upstream shadcn/ui releases; document cache invalidation strategy.
Multi-framework switching (React/Svelte/Vue/React Native) is stateless per server invocation; concurrent framework requests require separate server instances or stateful routing logic.
Docker deployment assumes Node.js runtime availability; verify container image size and security scanning (no supply-chain or SBOM details provided in README).

When to avoid it — and what to weigh

Non-shadcn/ui Projects — This server is purpose-built for shadcn/ui ecosystems. If your project uses Material-UI, Chakra, or other component libraries, a different MCP server or custom tool would be required.
Offline or Air-Gapped Environments — The server requires real-time GitHub API access to fetch component source code. It cannot function without internet connectivity to github.com.
Strict Rate-Limit Constraints — Without a GitHub token, unauthenticated requests are limited to 60/hour. If your AI workload exceeds this, token provisioning and monitoring become mandatory operational requirements.
Proprietary or Private Component Libraries — This server only exposes public shadcn/ui repositories. Internal or forked component variants would require custom MCP server modifications or private repository fork management.

License & commercial use

MIT License. Permits commercial use, modification, and distribution with attribution. No warranty provided. See https://opensource.org/licenses/MIT for full terms.

MIT is a permissive OSI-approved license. Commercial use, modification, and redistribution are permitted provided the license and copyright notice are preserved. No additional commercial licensing or royalties apply. However, standard liability disclaimers in MIT apply; use in production AI systems should include legal review of liability implications.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

Signal	Assessment
Maintenance	Active
Documentation	Strong
License clarity	Clear
Deployment complexity	Moderate
DEV.co fit	Strong
Assessment confidence	High

Security considerations

GitHub tokens (personal access tokens) are handled via CLI args or environment variables; ensure tokens are not logged or exposed in deployment configs. SSE transport over HTTP requires TLS in production. No explicit supply-chain security details (SBOM, signed releases, or dependency scanning) provided. Typical TypeScript/npm supply-chain risks apply; audit dependencies before production use.

Alternatives to consider

Custom MCP Server (DIY)

Build a lightweight MCP server directly interfacing with your component library's GitHub or internal repository. Provides full control but requires engineering investment and maintenance.

RAG Pipeline (LLamaIndex, LangChain)

Implement a vector-based retrieval system over shadcn/ui docs and source code. Offers semantic search and offline capabilities but adds complexity and LLM token overhead.

Call GitHub API Directly

Bypass MCP and invoke GitHub API calls directly from your LLM integration. Minimal abstraction but requires token management and rate-limit handling in application code.

Software development agency

Build on shadcn-ui-mcp-server with DEV.co software developers

Deploy the shadcn-ui-mcp-server to enable Claude, ChatGPT, and other LLMs to generate production-ready component code. Start with npx, scale with Docker Compose.

Talk to DEV.co

Related open-source tools

Surfaced by semantic similarity across the DEV.co open-source index.

mcp-ui mcp-server-browserbase mcp-use

Related on DEV.co

Explore the category and the services that help you build with it.

MCP Servers AI Development Services AI-Powered Application Development Web App Development Cloud Deployment & DevOps Talk to DEV.co

shadcn-ui-mcp-server FAQ

Does this server work with private or forked shadcn repositories?

Not out-of-the-box. It fetches from official shadcn/ui, shadcn-svelte, shadcn-vue, and react-native-reusables repos. Custom or private forks would require modifying the source code to point to alternate GitHub URLs.

What happens if my GitHub API token expires or rate limit is hit?

The server falls back to 60 requests/hour unauthenticated rate limit. LLM requests may timeout or fail if throttled. Token rotation and monitoring should be part of operational runbooks.

Can I run multiple framework servers simultaneously (e.g., React and Vue at the same time)?

Each MCP server instance is tied to one framework per invocation. To support multiple frameworks concurrently, deploy separate server instances on different ports or use a router/load balancer to dispatch requests.

Is the SSE transport production-ready for high-concurrency scenarios?

Theoretically yes, but real-world production use requires proper SSL/TLS, CORS config, load balancing, health checks, and GitHub rate-limit resilience testing. Docker Compose example provided but no performance benchmarks or SLA data included in documentation.

Software developers & web developers for hire

shadcn-ui-mcp-server rarely ships on its own. As a software development company, DEV.co handles the surrounding work — data modeling, service integration, deployment, and the mcp servers glue code that production actually requires.

Integrate Shadcn UI with Your AI Workflow

Deploy the shadcn-ui-mcp-server to enable Claude, ChatGPT, and other LLMs to generate production-ready component code. Start with npx, scale with Docker Compose.

Talk to DEV.co Schedule a Consultation