"A guide to building a website" matching MCP servers:

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.

Enables auditing any public website, returning a scored plain-English report that flags issues costing customers, covering speed, phone experience, search visibility, contact options, writing quality, and modernity.

Analyzes Playwright test results to provide structured QA insights, including test metrics, failure analysis, bug report drafts, and release-quality recommendations.

Provides an LLM with a real Chromium browser to perform web tasks, recording every action into a structured trace for later verification of goal completion.

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

Enables Claude to generate executable test cases from decision tables in CSV, JSON, or Markdown formats. Provides intelligent test planning guidance and generates Playwright/API test code with TypeScript support.

MCP server for end-to-end QA automation: generates test scenarios, discovers Playwright locators, creates TypeScript test code, executes tests, and creates GitHub issues for failures.

MCP server for AI-powered QA analysis. It enables analyzing test failures, identifying root causes, suggesting fixes, classifying defects, detecting flaky tests, and generating test cases and bug reports.

MCP-first A/B testing server that enables agents to manage experiments (create, update traffic splits, read results, apply winning variants) from tools like Claude Code, with self-hosted Cloudflare backend.

Enables AI incident-response agents to connect over MCP to a simulated service environment, receive alerts, gather diagnostic evidence, execute safe SOP actions, and verify recovery.

Enables AI assistants to answer QA questions in a single call, covering run reports, failure grouping by root cause, flaky versus regressed test detection, and coverage gaps. Also exposes raw TestRail API access when a question needs it.

Evaluates MCP servers by running read-only checks and returning a graded report with an A-F letter grade.

Broccoli turns "the agent reads a stack trace and guesses" into "the agent drives the real debugger": it sets breakpoints, steps, inspects live variables over the Debug Adapter Protocol, and proposes a fix you approve in a diff — never applied silently.

Enables evidence-led website reconstruction through a browser-first workflow that audits sites, requests approval before building, and verifies rebuilt pages against pixel and console checks.

A template for building a custom Playwright MCP server that enables AI-driven browser automation, translating high-level test intentions into dynamic Playwright actions.

Enables agents to turn a plain-language description of a device into a complete, validated build package — parts list, 3D-printable parts, wiring, firmware code, picture assembly guide, and tests — that anyone can assemble without electronics experience.

Enables agents to drive a local-only headless Chrome for Testing to navigate local dev servers, take screenshots at mobile and desktop widths, click through interactions, and assert a clean console with no failed requests, all as MCP tools.

Spring AI Playground is a self-hosted web UI platform for building low-code tools and dynamically exposing them via built-in MCP server for AI agents.

Enables checking whether a Meta, LinkedIn, or Google Ads campaign is structurally able to serve and convert before spending, by inspecting schedule, bid, destination, approval, geo, and budget fields through read-only tools. It also reconciles reported spend across the three platforms against a ledger to surface discrepancies, armed campaigns, and drift.

Enables MCP-compatible clients to execute Playwright-based UI and API test suites (login, inventory, checkout, API, regression) and receive structured JSON test results.