"A tool for evaluating Tailwind CSS class quality in HTML" matching MCP servers:

Enables coding agents to turn OpenSpec intents and Git changes into revision-bound proofs by planning, selecting, and running the smallest safe protection set, then verifying composite verdicts and explaining evidence or unresolved states.

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

Review AI-generated HTML slides or reports in the browser, anchor comments to specific passages, and have the agent fix them via MCP, with tools for inspection, commenting, layout checking, and export to PDF/PPTX.

Automates repository analysis, test planning, and generation of end-to-end tests with Playwright, acting as an intelligent quality assistant.

Enables running SQL warehouse validation checks through natural-language questions in MCP clients, while reusing the same logic for automated pipeline and CI/CD runs.

Generates precise, measurable quality evaluation standards and scoring criteria for any task, transforming vague requirements into specific dimensions that guide execution and improve work quality.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

Hybrid code quality analysis server combining fast logic-based checks with AI-powered deep analysis, offering tools for summaries, quick wins, and trend tracking.

Enables code agents to run risk-based Jev quality reviews on focused diffs through a read-only MCP tool, returning structured scores and weakness hints without modifying code.

🚀 Kill the Junior AI Era. 🤖 Level up your AI code to Principal standards. No more sloppy lines or junior mistakes. Automated ESLint ✨ TypeScript 🔧 Prettier 🎨 SonarQube 🛡️ Security 🔒 Complexity 📊 in seconds. High-stakes quality, forced to ship only the best. ⚡🏆 Goodbye, bad code. Hello, Principal Engineer. 🚀✨

Enables automated HTML export quality assurance with structured receipts, audit logs, and reviewer-ready evidence through a paid remote MCP server.

Enables comprehensive video quality analysis including metadata extraction, GOP structure analysis, quality metrics comparison (PSNR, SSIM, VMAF), artifact detection, and transcoding effect assessment through FFmpeg-based tools.

Audits MCP tool descriptions for quality and reliability, scoring them 0-100, detecting smells, and providing rewritten versions for better agent accuracy.

Generates quality control plans and inspection reports from technical-drawing PDFs: tolerances, fits, threads, GD&T and surface finishes are extracted automatically by Imnoo's drawing analysis, numbered as balloons with acceptance limits and measuring instruments, and exported as a ballooned drawing PDF, an inspection package and an Excel measurement report.

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.

Connects AI coding assistants to PyCharm's code quality inspections and optionally SonarQube for IDE, providing unified, de-duplicated code analysis results without uploading source code.

An MCP server that deterministically scores landing pages on conversion-critical signals and blocks ad spend on low-quality pages to prevent wasted budget.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

Protects AI agents from bad tool outputs, schema mismatches, and tool poisoning by validating, sanitizing, and scoring reliability of tool responses.

Provides tools to test regex patterns for correctness, performance (ReDoS), and memory usage, and suggests safe rewrites. Enables LLMs to iterate on regex generation with verifiable feedback.