"A guide to interface components in UI design" matching MCP servers:

Enables AI assistants to generate production-ready, professional UI design systems and components from simple descriptions, with real images, animated components, and automated quality checks.

Provides production-ready examples of MCP servers that demonstrate building rich, interactive UI components for ChatGPT, including authentication flows, product search with carousels, shopping cart checkout, and membership signups with state management.

Enables AI to inspect and interact with UI elements, supporting control mode for the runner's own UI and SDK mode for external applications.

Enables bidirectional synchronization between IDEs and Figma for Design System management, allowing developers to generate React components and synchronize design tokens, icons, and components across platforms.

Local MCP server for A-share stock trading via Tonghuashun, offering account/position queries, buy/sell/cancel orders with risk controls and forced user confirmation; currently simulated with a reserved interface for real broker channels.

A management interface for MCP servers built with Angular 17 and Bootstrap 5.

Enables agents to convert Markdown into WhatsApp-compatible formatting, including styled text, lists, and tables that fit a phone's monospace width.

MCP server that annotates any web page with hover labels — zero extensions, works in any browser

Enables AI assistants to present interactive choices to users via browser popups, supporting single and multiple selections with optional custom input.

Enables users to control the cursor in Figma through verbal commands using an agentic AI agent, streamlining the design process with a new interaction method.

Enables local Windows UI automation and screen capture, targeting windows that are difficult to automate such as games and legacy apps, with tools for window management, mouse and keyboard input, and desktop capture.

Turn natural language into 3D models in Fusion 360. 64 CAD tools including sketches, extrudes, fillets,and JIS standard parts.

Enables AI agents to capture screenshots from Android devices and emulators, and manage connected devices for UI analysis and testing. Supports device listing, screenshot capture, and integrates with Claude Desktop, Gemini CLI, and GitHub Copilot.

Automates the conversion of Figma designs into TypeScript React components and integrates with GitHub to create pull requests for the generated code. It includes visual regression testing with Playwright and accessibility validation to ensure implementations match the original designs.

Enables comprehensive UI/UX development workflows through integrated tools for component development with Storybook, Tailwind CSS styling, Framer Motion/GSAP animations, Playwright testing, and automated design system generation. Provides end-to-end automation for visual regression testing, accessibility compliance, and UX optimization analysis.

Give any LLM agent a real Android or iPhone. 62 MCP tools: tap, swipe, type, screenshot, screen-tree reading, app launch, camera, TTS, crash reports, batched execution. Android via ADB, iPhone via WebDriverAgent, on-device inference, Docker+KVM emulators. Works with Claude Code, Cursor, LangChain, LlamaIndex, and any MCP client. MIT.

Provides AI-powered tools to apply UX/UI best practices, Nielsen's heuristics, cognitive biases, and Material-UI patterns to React components. Enables automated application of responsive design, Apple design patterns, and complete UX guidelines through natural language commands.

Enables downloading content from various social media platforms through a unified API. Provides a single tool to download media from multiple social networks using the Social Download All In One service.

Enables AI agents like Claude to interact with Figma designs through 50+ tools for creating, styling, and manipulating design elements, components, and variables via a WebSocket relay and Figma plugin.

A standalone proxy that transforms any OpenAPI or Swagger-described REST API into an MCP server by mapping API operations to executable MCP tools. It enables AI clients to interact with existing web services through automated HTTP requests based on their official documentation.