"Semantic UI" matching MCP servers:

Provides AI coding assistants with on-demand access to component specs, test scenarios, accessibility requirements, and build guides from the Web UI Component Specification.

Enables UI debugging on physical iOS devices by bridging to an in-app DebugBridge HTTP service, supporting UI inspection, element interaction, log retrieval, and runtime validation.

Enables AI-driven UI inspection and optimization by scanning websites with configurable viewports, capturing screenshots, running deterministic accessibility and layout checks, and generating prioritized reports with fix prompts.

Enables agents and users to query mapped UI flows, retrieve immutable revision-bound browser evidence and screenshots, compare flow changes across revisions, and inspect coverage gaps or UI impact.

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.

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.

Enables estimating LLM hallucination and confabulation by clustering sampled responses into semantic equivalence classes and computing semantic entropy. It provides a plug-and-play validation filter for agent pipelines using the MCP protocol.

Enables detecting LLM hallucinations and confabulations by clustering sampled responses into semantic equivalence classes and computing semantic entropy.

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 AI agents to inspect Unity UI Toolkit screens, examine element structure and styles, and capture screenshots without entering Play Mode or building a Player.

Enables AI agents to drive Playwright-based browser automation for UI testing, returning JSON/HTML reports with screenshots without server-side LLM or test scripts.

Enables AI coding agents to inspect a project's design tokens and component catalog, audit React/Tailwind files against seven static UI quality rules, score overall UI health, and apply auto-fixes that are re-audited and reverted on regression. It works both locally over filesystem access and remotely on raw TSX/JSX or CSS snippets passed directly as strings.

Provides comprehensive UI test automation capabilities including intelligent test creation, test healing, and manual test conversion through browser automation using Playwright.

Human-to-AI code review bridge. Annotate UI elements in the browser with review comments, and AI agents read the feedback via MCP to fix code automatically — with full element context (CSS selector, styles, DOM path, accessibility info). 10 MCP tools, framework-agnostic Web Component, zero-config install via uvx.

Provides Android UI automation tools via MCP, enabling device interaction, UI snapshot, and gesture recording.

Lets AI agents visually inspect web elements, test CSS edits in real-time, and iterate until pixel-perfect, functioning like browser DevTools for debugging UI issues.

Visual CVE audit dashboard for npm, Python, Go, and Rust projects. Scans your project manifests (package-lock.json, requirements.txt, go.sum, Cargo.lock) against OSV.dev live data, opens a browser dashboard for human review, then applies fixes only after explicit confirmation. Supports multi-service monorepos in one command.

An MCP server that gives coding agents hands and eyes on an Android device, providing 19 tools for building, testing, installing, UI inspection, input, logs, and toolchain diagnosis. It returns concise, structured results to make the build-debug loop efficient.

MCP server for WeChat Mini Program debugging and automation, enabling agents to perform UI operations, screenshots, and regression testing through natural language commands.

MCP server for screen recording on macOS, iOS Simulator, and Android, with key-frame extraction via ffmpeg, enabling AI agents to capture UI motion and transient visual states.