"Understanding Frontend and Backend Development" matching MCP servers:

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

Enables coding agents to visually verify front-end changes by capturing screenshots at real breakpoints, identifying the single element responsible for overflow, and surfacing console and network errors.

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.

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.

An MCP server implementing a 7-stage agentic frontend workflow—from design audit to PR review—including AI-driven component generation, browser validation, E2E testing, and CI self-healing.

An MCP server that visually reviews UI edit requests by comparing screenshots before and after edits, ensuring changes satisfy user requests.

Provides tools for frontend testing including code analysis, test generation, test execution, and React component testing for Jest and Cypress frameworks.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

Provides a hand-written MCP server integrated with a LangGraph agent to benchmark multiple agent topologies and measure their failure rates.

Enables AI clients to reproduce reported UI issues in an isolated, policy-restricted browser context, gather sanitized evidence, distinguish observed facts from candidate causes, and produce structured reports plus reviewable Playwright regression tests.

An MCP server that reviews UI edit requests by comparing before and after screenshots, providing visual feedback on whether changes satisfy the user's requirements.

Enables LLM tools to control iOS Simulator, manage Expo/Metro development servers, capture screenshots and videos, stream logs, and execute UI automation tests via Detox for React Native/Expo applications.

Enables backend test quality analysis for GPA e-commerce, including coverage analysis, reverse engineering, architecture mapping, and test suite generation.

A Model Context Protocol server for JavaScript/TypeScript development, providing tools to run scripts, tests, builds, and dependency management with framework and package manager detection.

Enables AI-powered frontend code review and unit test generation for Phabricator diffs, supporting React/TypeScript analysis, multi-dimensional code review (performance, security, accessibility, i18n), and intelligent test case generation with Vitest/Jest support.

An MCP server that provides comprehensive tools for managing iOS simulators, including device control, app lifecycle management, and UI automation. It enables developers to boot devices, install apps, capture screenshots, and simulate user interactions through natural language commands.

Enables LLMs to interact directly with generated REST services by discovering and invoking CRUD tools and reading exposed resources for list and get-by-id data.

Validates .mcp.json and claude_desktop_config files to catch duplicate server names, missing binaries, invalid environment variables, and unreachable endpoints. Reports each problem along with how to fix it, so silently failing MCP servers can be diagnosed and repaired.

Enables MCP clients to retrieve lab performance scores and field Core Web Vitals data for web pages via Google APIs.

Enables users to run synthetic support-agent evaluations, preserve and inspect traces, score results deterministically, inject failures, and enforce release review gates through MCP tools, resources, and prompts.

Checks MCP servers by URL, npm package, or official MCP Registry search, reporting availability, response speed, exposed tools, resources, and prompts. It flags changes since prior runs as breaking, warning, or info using saved snapshots.

Windows桌面截图与窗口自动化工具，支持后台操作、不抢焦点，可截取窗口/屏幕、模拟鼠标键盘、点击菜单等。

AI-powered backend diagnostics MCP server that statically analyzes frontend and backend code to catch cross-boundary bugs, contract drift, missing validation, security gaps, and performance anti-patterns before deployment.

Provides a framework for running multiple MCP servers using FastAPI, stdio, and streamable-http transports, with an echo tool for testing and integration with MCP Inspector.

Maps Electron app IPC handlers to MCP tools and provides 33 built-in CDP tools for DOM automation, screenshots, interaction, and debugging, enabling Claude Code to directly control your Electron app.

Enables AI coding assistants to scan an iOS, Android, Flutter, React Native or Expo project for App Store and Google Play rejection risks, returning deterministic findings that cite the guideline section, link to the official Apple or Google page and explain how to fix each problem. Nothing leaves the machine and no AI is used in the checks.

A production-oriented reliability, benchmarking, and evaluation system that layers multi-version protocol negotiation, adaptive streaming, connection pooling, and resilience onto an MCP agent runtime.

Exposes MAID Runner validation tools (validate, snapshot, test) as MCP tools, resources, and prompts for AI agents like Claude Code and Aider, enabling seamless integration with AI development workflows.

Connects AI agents to Minecraft servers via RCON to execute commands, monitor logs, and perform read-only SQLite database queries. It is specifically designed to facilitate AI-assisted plugin development, live debugging, and automated testing workflows.