"A search for a URL" 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.

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-test-runner is an MCP server that lets your AI client (Claude / Cursor / Codex / Gemini) drive your entire QA loop end-to-end: * Run tests across pytest / Jest / Cypress / Go / Maestro — single MCP surface, one env var to switch * Analyze a URL (Web DOM probe) or a live mobile screen (Maestro hierarchy) to extract testable modules + candidate cases * Generate runna

MCP server that generates ISO/IEC/IEEE 29119-3 compliant test plan drafts from project information, providing a structured resource for the standard's test plan outline and a tool for draft creation.

An MCP server that provides an LLM with a real Chromium browser via Playwright, recording every action taken toward a stated goal and producing a structured trace so the run can be audited for goal achievement.

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

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.

A multi-task MCP server for AI code optimization and testing that integrates with VSCode/Cursor, CLI tools, and autonomous agents. It provides tools for running tests, generating code improvements, and managing objectives across different environments.

A local MCP server that gives Cursor Agent three focused QA tools for analyzing user stories, creating test charters, and drafting bug reports, with built-in safety rules and reusable workflows.

A lightweight MCP server for security reviews that injects security requirements before code generation, scans dependencies for CVEs, and verifies generated code without disrupting workflow.

Enables coding agents to run an evidence-backed visual QA loop for browser interfaces, including inspecting a running app, retrieving findings with screenshots, and rechecking only the captures affected by a fix.

An AI-powered QA automation server that integrates Jira, GitHub, Jenkins, AWS, and Webex into a unified interface for QA engineers.

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.

AI-powered E2E testing MCP server. Point at a URL — AI generates test scenarios, runs Playwright tests, and self-heals failures automatically. Works on Canvas and Flutter Web apps.

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 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.