"Resources and Assistance for Website Design, Frontend UX Flow, and Backend Design" matching MCP servers:

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

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.

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

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

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.

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.

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

A zero-dependency local MCP server that audits and auto-fixes React/Next.js frontend code smells, unused imports, and responsive UI issues

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.

An MCP server that provides tools for frontend development, including i18n issue detection, OpenAPI type generation, and project structure analysis.

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.

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.

Enables coding agents to load backend anti-slop rules and deterministically audit TypeScript/backend files for violations like SELECT *, SQL interpolation, N+1 calls, silent catches, stack leaks, type escapes, and TODOs, plus verify TypeScript compilation. Returns PASS/FAIL findings so agents can fix issues before shipping.

Enables coding agents to load frontend anti-slop rules and deterministically verify generated React, Next.js, and Tailwind UI before completion. It audits for common AI-generated patterns, checks stylesheet/token wiring, provides real or placeholder images, and verifies TypeScript compilation.

Enables AI agents to analyze and scaffold React/Next.js applications enforcing Feature-Sliced Design (FSD) conventions, providing tools for project analysis, rule retrieval, and entity generation.

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.

A comprehensive MCP server for frontend analysis. It provides Google Lighthouse audits, code quality checks, SEO metadata verification, accessibility analysis, and bundle optimization for React and Next.js projects.

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 AI agents to perform read-only static analysis of Node.js backend projects, detecting database query anti-patterns, async bottlenecks, connection pooling mistakes, and dependency hygiene issues while returning structured evidence-backed findings.

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.

Fetches and structures Ant Design v4 component documentation into JSON format, enabling AI agents to search, analyze, and retrieve component metadata, APIs, and examples.

A local, read-only MCP server that analyzes Python backend projects by providing tools to scan, map, and selectively read files, reducing token usage for AI clients.

An MCP server that analyzes and traces business code flows across your codebase, enabling developers to quickly understand the complete execution path of features from frontend to backend to database.

Integrates with Claude Code to execute AI-powered code analysis and workflow automation, supporting pre-defined scenarios like code review and security audit.

A Model Context Protocol server that helps programmers understand code by providing explanations, tech stack analysis, and best practice suggestions through prompt templates.

Analyzes frontend project code (React, Vue, Angular) and converts it into AI-understandable flow diagrams and object structures. Provides tools for code analysis, variable/function/component inspection, and project structure insights.

Turns a codebase into a persistent knowledge graph so AI coding agents can answer structural questions about functions, call chains, routes, and cross-service links through graph queries instead of reading files one by one.

Reusable MCP server for Python backend development with FastAPI, MongoDB, and Stackraise support.

Enables coding agents to compile supplied files, run optional focused tests, and get static findings across ten programming languages, providing a deterministic feedback loop on the code they are about to return.

Integrates Google's Gemini AI models into Claude Code and other MCP clients to provide second opinions, code comparisons, and token counting. It supports streaming responses and multi-turn conversations directly within your existing AI development workflow.