"A design and prototyping tool for user interface and user experience (UI/UX) design" matching MCP servers:

An MCP server for external computer-use that launches, observes, and interacts with any X11 application via AT-SPI2 accessibility tree and xdotool input injection.

Enables AI coding agents to audit rendered web pages for design and UI defects by measuring geometry, styles, contrast and motion in a local browser and judging them against evidence-tiered rules. Findings come back as short, fixable items expressed in the project's own design tokens, while only sanitized numeric measurements leave the machine.

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 end-to-end testing of voice-enabled web applications by simulating a synthetic user with a virtual microphone, virtual speakers, a real browser, and a viewable display, allowing audio injection, speech capture/transcription, and browser automation.

An MCP server that measures how faithfully one UI reproduces another, returning a score and actionable findings for improvement.

Compare design and implementation screenshots using pixel-by-pixel analysis, generating visual diff images and metrics.

An MCP server for auditing and analyzing user interfaces across 20 platforms based on 30 fundamental UX laws. It provides automated code detection, platform-specific checklists, and comparative analysis to optimize design usability.

Provides a hand-written MCP server integrated with a LangGraph agent to benchmark multiple agent topologies and measure their failure rates.

Enables creating, validating, and simulating Crack-style story chat through a unified MCP server, with template and keyword management, automated project audits, session play, and persona-separated testing to prevent omniscience.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

Enables AI agents to validate design system constraints, including WCAG accessibility, token relationships, and consistency, through MCP tools like validate, explain, and suggest-fix.

Compares Figma frames to live pages, checking colors, fonts, and border radii, and generates a shareable HTML report.

An MCP server that provides comprehensive UX best practices covering accessibility, usability, UI patterns, design systems, performance, and more, enabling clients to analyze and generate UX-optimized code and recommendations.

Enables AI-powered visual analysis of webpages for UI/UX assessment, including screenshot capture, element detection, accessibility auditing, and comprehensive JSON reporting.

Lets developers and MCP agents run deterministic local HTML audits, turning inline HTML into structured findings for missing labels, unnamed buttons, skipped headings, ambiguous links, duplicate IDs, and missing landmarks. It also exposes a rule list and returns stable, actionable reports without external API keys.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

Enables coding agents to see the UI they just changed without flooding their context window, returning a structured text summary (console errors, failed requests, overflow, layout shifts, accessibility violations) plus small crops of only the regions that changed since the last capture. All output is fitted into a chosen token budget, with captures stored on disk and evicted automatically.

Enables coding agents and CI to verify rendered web UIs against design token usage, layout constraints, and accessibility rules, returning concise pass/fail verdicts with actionable findings.

Enables AI coding agents to build, evaluate, and validate ServiceNow Next Experience UI Framework components and projects, helping keep component code and now-ui.json manifests in sync while using live instance API metadata.

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.