"Resources for Frontend Coding" matching MCP servers:

Provides 8 MCP tools for frontend design: load design system, generate components, scaffold pages, review consistency, extract tokens, check WCAG 2.2 AA, test responsiveness, and export to Figma.

Enables high-craft web design and engineering through OKLCH color systems, fluid typography, Three.js 3D scenes, frontend security audits, multi-viewport capture, and Python-backed design verification.

Enables AI coding agents to search public design-system catalogs and retrieve only the relevant tokens or sections for a chosen brand, so generated UI matches a specified visual style instead of generic AI output.

Enables evidence-grounded web design analysis by searching GDWEB references and generating isolated, per-reference DESIGN_INDEX specification documents for LLM-driven frontend development.

Gives LLM agents spatial awareness inside Autodesk Maya, enabling scene inspection and measurement, aesthetic and engineering audits, camera planning, checkpoint/rollback safety, asset import, and viewport or render previews. Agents can also execute arbitrary Python in Maya to build and verify 3D scenes against engineering rules instead of writing blind.

MCP server with 12 tools for design, UX, conversion, and product knowledge from Frontend Masters courses by Paul Boag and Sarah Drasner, enabling audits, accessibility checks, layout recommendations, and more.

Provides AI assistants with frontend development tools including component scaffolding, bundle analysis, accessibility checks, and responsive design guidance. Enables automated generation of React components with tests and stories, bundle optimization recommendations, and WCAG compliance fixes.

Generates randomized English Markdown frontend design directions using curated catalogs, with optional soft compatibility scoring. Does not call an LLM.

Enables frontend developers to read Moonvy design files, extract page lists, layer trees, node styles, design tokens, and download assets such as cutouts and snapshots for precise frontend implementation.

Connects MCP-aware AI clients to a live SketchUp session so users can create and modify 3D models, apply materials, perform booleans and joinery, and export scenes through natural-language prompts.

An MCP server that provides AI assistants read-only access to Looba, a community platform for UI snippets and design inspiration, enabling snippet discovery and integration into frontend projects.

It lets AI coding agents look up design tokens, component specifications, and prohibition rules on demand, then validate generated HTML or JSX with the same lint logic used by CI and editor hooks so violations are caught and corrected immediately. It also exposes the design constitution and rule sets as resources for reference during generation.

Reverse-engineers design videos and images into structured frontend implementation specifications using vision LLMs and FFMPEG for frame-level analysis.

Enables AI-driven 3D modeling and scene creation in Blender, allowing LLMs to create, modify, and manipulate objects, materials, and assets through natural language.

Converts Figma designs into production-ready React components with design token extraction, widget registry integration, and micro-frontend module generation.

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

Converts Figma designs into structured code context with token-aware styling, enabling AI agents to generate production-level frontend code.

An MCP server that provides access to Google Gemini models via Vertex AI, enabling text generation, multi-turn chat, image/video generation, and frontend design through Claude Code.

Enables AI coding assistants to directly access Lanhu design drafts, generate frontend code, parse PRDs, and download design assets.

Enables Large Language Models to access and manipulate Autodesk Revit models through a pyRevit-based bridge and the Model Context Protocol.