"Material Design Icons" matching MCP servers:

Provides access to Ant Design component library documentation and information for automated code generation. Enables searching components by category or keyword, retrieving component props, examples, API documentation, and available icons.

Provides software design guidance via MCP, including SOLID principles, design patterns, pattern scaffolding, and heuristic code-smell detection to help review and refactor code.

This MCP server renders UI design artifacts headlessly, runs deterministic linters, and manages stateful design review loops with an independent vision critic.

Enables AI assistants to discover, document, and generate React code using the pastel-themed Baby Design UI component library. It provides tools for retrieving design tokens and component specifications to streamline the development of user interfaces.

Enables auditing UI for icon accessibility, suggesting icons based on action semantics, rendering constrained inline SVGs, and reading the full icon policy via MCP tools.

Enables auto-configuration and validation of React components against a glassmorphic design token system using an AST correction engine. It supports managing UI presets, enforcing design uniformity in Monaco IDE, and exporting tokens as CSS, Tailwind, or JavaScript variables.

Enables AI assistants to search for real Iconify icons, check icon names and properties, retrieve version-matched pyside-iconify usage references, and statically validate pyside-iconify code before running it.

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 coding agents to read ground truth about a React design system — components, props, cva variants, tokens and docs — over MCP so they write UI that matches it. It also exposes a check_ui linter agents run on their own output, returning rule ids, locations and concrete fixes before review.

Enables AI agents to audit and fix CSS for generic AI-built design patterns, covering fonts, palettes, contrast, and type scales.

Enables Codex to scaffold small framework-free websites and critique them with sourced, severity-annotated findings that teach better design and development choices.

An MCP server that provides design-pattern selection expertise to AI coding agents.

Enables consulting oracle AI models (Codex or Claude) for expert reasoning and analysis on complex problems, architectural decisions, and design tradeoffs through a unified CLI interface.

Enables the generation and iterative refinement of React UI components from natural language descriptions or design images using Vercel's v0 API. It provides tools for design-to-code workflows and chat-based component development within Claude, Cursor, and other MCP environments.

An MCP server that enables AI to interact with the private 'my-design' React component library and design tokens for UI generation and technical support. It provides tools for component searching, API documentation retrieval, and migration guidance based on specific internal design specifications.

Enables Claude to consult GLM-4.6's architectural intelligence for system design, code analysis, scalability patterns, and technical decision-making. Provides specialized tools for enterprise architecture consultation, distributed systems design, and code review through the Model Context Protocol.

Comprehensive MCP server for Fluent UI React v9 development, providing component knowledge, design tokens, code generation, and validation tools.

A local MCP server that audits software projects against the UK ICO Age Appropriate Design Code (Children's Code) entirely on the user's machine.

Automates frontend integration by mapping messy API JSON responses to Vue or React Design System components, generating Zod schemas for type-safe data transformation with live UI previews in chat.

Enables AI to analyze, query, and manage a graph-based representation of software architecture for impact analysis, dependency tracking, and design.

Enables AI to directly read and analyze Lanhu design drafts and requirement documents to generate HTML, CSS, and structural analyses. It allows users to extract design slices and process prototype pages directly within AI clients.

An MCP server for Arabic UI/UX design, offering tools to generate design tokens, build RTL components, stitch layouts, and audit RTL compliance using Material 3 Expressive and Google Stitch.

Enables coding agents to audit frontend source for generic AI UI patterns and WCAG 2.1 contrast failures, extract Design DNA from local stylesheets or live URLs, and export Tailwind v4 tokens. It also applies complete design presets to synchronize agent rule files and MCP configuration.

Provides intelligent design pattern recommendations using semantic search through a comprehensive catalog of 200+ patterns across 20 categories. Users can describe programming problems in natural language to discover appropriate design patterns with contextual recommendations.

Enforces design systems and vocabulary via ontology checks, candidate scanning, linting, and structural search across repositories.

A read-only MCP evidence server for chip verification and RTL debugging that exposes structured design and waveform data from Synopsys Verdi databases via MCP tools and CLI. It provides auditable evidence like contexts, objects, connectivity, traces, waveforms, and source mappings without modifying RTL or design DBs.

MCP server for Next2D application development that generates code following MVVM + Clean Architecture + Atomic Design patterns, validates architecture, and provides API references.

Enables AI coding tools like Cursor to access Figma design data through the Model Context Protocol, allowing accurate implementation of designs across frameworks. Based on NCDS (NHN Commerce Design System) with enhanced source generation capabilities.

Enables asking a consuming app in plain language to audit its design system usage, returning tables that sort every value and component by origin—design system, app-named, or none—along with token and contrast checks.

Exposes the 23 Gang of Four design patterns to AI coding agents for generation, canonical examples, AST-based detection, validation, and anti-pattern refactoring in Python codebases.

AI code analysis tools that plug into Claude Code, Cursor, VS Code, and any MCP client, providing six specialized tools for explaining code, debugging, code review, security audit, automation script generation, and MCP blueprint design.

Enables AI coding agents to access evidence-backed repository memory, code graph, project DNA, and deterministic change validation so they understand design decisions, past bugs, and invariants while working.

Enables an LLM to triage hard-to-extract Vue components by feeding it structured coupling analysis, dependency graphs, and design tokens, then generating decoupling suggestions with before/after code, composable wrappers for store-bound components, and full rewrite-and-extract operations.

Enables AI tools to read, edit, check, and export the currently open Figma file locally, with support for design files, FigJam boards, and Slides decks plus quality checks and design-to-code workflows.

Self-hosted design audit MCP server that reviews UI code against Nielsen's heuristics and an accessibility rubric, returning scores and fixable findings. It also enables verifying previously flagged issues against updated code.

Enables agents to grade other MCP servers for LLM usability, covering descriptions, schema design, naming, token cost, and consistency, while also explaining grading rules.

Enables Cursor and Claude Code to read design tokens and rules, and validate component code against a design system before generating UI.

Enables AI coding agents to extract Figma design data and convert it into Flutter widgets and screens. Supports theme setup, component analysis, asset exports, and provides Flutter implementation guidance from Figma designs.

Enables coding agents to search and extract design themes, review UI source with deterministic rules, and install shadcn-compatible React/Radix components from a local registry. Provides editable guidance topics and rendered spacing evidence without requiring an account for public catalog, guidance, and review calls.

Provides a real API for coding agents to look up design system components, props, and tokens, preventing guessed answers.