"Servers for creating UI in Figma using MCP" matching MCP servers:

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 agents to convert Figma frames into self-contained HTML and then iteratively verify the rendered code in Chromium against the design using pixel diffs and element bounding-box checks until it converges.

Enables agents to compare a live web page against a Figma frame and receive a bounded JSON verdict of design deviations, without sending screenshots or mockups through the model context.

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.

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 lets AI agents see, act on, and verify the rendered Neovim UI, like a Playwright for Neovim. It provides tools to launch/attach to Neovim, observe the screen, send input, and wait for conditions.

MCP server that gives Claude deep awareness of your frontend codebase by scanning components, hooks, services, routes, and data flow for React or Vue projects.

MCP server that helps AI agents create UIs that don't look AI-generated by auditing components, refining copy, suggesting themes, and checking accessibility/contrast.

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.

Enables AI agents to rapidly drive and inspect real web pages through persistent browser sessions, using accessibility-tree snapshots and DevTools-grade diagnostics to identify and diagnose issues.

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 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.

Comprehensive MCP server for end-to-end UI development, offering tools to generate components, manage design tokens, audit accessibility, autofix issues, inspect live pages, compare screenshots, and more across multiple frameworks.

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 Claude to inspect and drive native macOS app UIs during development via an in-process view tree and screenshot renderer, without requiring screen recording permission.

Enables AI agents to inspect UI screen recordings as token-efficient image sheets with changed regions boxed, single-frame flicker flagged, and speech aligned to frames. Exposes watch_video and zoom_video tools so agents can pull dense keyframes across any time range or one sharp full-resolution frame, all processed locally.

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 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.