"Computer Aided Design" matching MCP servers:

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

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

Enables agents to measure a live page or Figma frame against a reference design, reporting exact numerical deviations in layout, spacing, typography, colors, states, and animations before any baseline exists.

Audits any site's UX the way a design-literate reviewer would — contrast, tap targets, type scale, colour discipline, scan patterns, copy — and returns the rule, the source line and the exact fix.

Grades MCP servers on agent usability (A–F) — description quality, schema design, tool naming and token cost, the properties that decide whether a model picks the right tool. Benchmarked across 36 popular servers; a third scored D or F.

Enables AI assistants to summarize Playwright test runs, identify flaky tests, heuristically triage failures, generate Playwright test stubs, and retrieve recent GitHub CI status through MCP tool calls.

Provides AI assistants with visual feedback for responsive web design by capturing screenshots and extracting DOM layout data through the Viewpo macOS app. It enables automated UI verification and responsive behavior comparison across multiple viewport breakpoints.

Enables AI agents to conduct UX reviews of web applications, detecting and fixing AI-generated design and usability issues while preserving the original style.

Enables MCP clients to open websites, capture screenshots at multiple breakpoints, and run automated design audits for issues like overflow, small tap targets, low contrast, missing alt text, tiny text, and clipped content.

An MCP server that audits websites for accessibility (WCAG 2.1 AA/EAA), performance, SEO, design quality, and mobile responsiveness, providing actionable scores, grades, and prioritized fixes.

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

An MCP server for in-loop design review of web previews. It enables agents to submit a preview URL, receive structured findings with suggested fixes, and recheck after applying changes, while never editing code itself.

Voice-powered bug reporting MCP server with 13 tools. Captures console logs, network errors, DOM traces, and developer voice descriptions. AI reads structured reports to find and fix bugs automatically. Chrome Extension + Python CLI.

Provides an LLM with a real Chromium browser to perform web tasks, recording every action into a structured trace for later verification of goal completion.

Gives AI coding agents a ten-phase frontend design pipeline (audit, style direction, build, review, verify, perf, brand) with an exclusive style menu. Its verify_page tool loads a URL in a real Playwright browser at mobile and desktop viewports and returns screenshots, ARIA snapshots, console errors, failed requests, horizontal-overflow offenders, axe-core violations, and pointer type.

This is an unofficial, community-built MCP server for qTest Manager. Not affiliated with or endorsed by Tricentis. Browse projects, modules, and test cases Create/delete test design modules Create and manage test execution cycles Add test cases into execution suites

Orchestrates full-stack frontend engineering—from intent discovery and design genome generation to automated multi-viewport QA—through JSON-RPC tools for AI agents.

Checks what local coding agents such as Claude Code, Codex and Cursor really did: files changed, commands run and test results read from test output, not the agent's word. Unclear test results can be double-checked by Laya (on your computer) or TypeSafe's Jev (cloud, your own API key). Read-only.

Lets Claude design, run and compare local robotics experiments — swarm behaviours, formations, coverage, cooperative localisation and synthetic visual odometry — through tools for cataloguing worlds, launching runs and campaigns, tuning parameters, saving floor plans and diffing metrics. Everything executes on the user's machine via a stdio JSON-RPC process, so runs are reproducible and no data leaves the host.