"MCP server that acts as a professor/teacher for AI agents" 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 automated QA testing by running a pipeline of AI agents that generate test scenarios, architect test layers, write Playwright tests, and review code, all grounded in feature requirements and API contracts.

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

Enables LLMs to inspect and test other MCP servers by listing and calling their tools, reading resources, and getting prompts. Supports stdio, SSE, and HTTP transports for both local and remote MCP server inspection.

Enables MCP clients to run and track scans, inspect quota usage, redeem existing studio report rights, and list or download generated reports through the associated REST API. It operates locally over stdio with API-key authentication and bounded retry/polling behavior.

Zero-Config, Fully AI-Managed End-to-End Testing for all code gen platforms.

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.

Reads a small-business website like a customer would and shows where they get stuck. Every AI answer has to quote the page, and the server checks the quote before it counts.

Checks a site for AI crawlers: which of 11 AI crawlers its robots.txt lets in, whether its llms.txt follows llmstxt.org, and what its home page says without scripts. Findings with evidence; no scores, no model calls, no telemetry.

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.

A licensed, locally run Playwright E2E testing MCP server for Claude Desktop and Cursor. It lets AI coding agents inspect semantic accessibility structure, validate role-based browser flows with explicit assertions, and generate reusable Playwright tests.

Enables AI agents to manage Autotest AI projects, screens, test cases, and test runs through natural language commands.

MCP server for measuring, tracking, scoring, and improving AI agent reliability with tools for recording interactions, scoring reliability, analyzing failures, recommending improvements, generating audit reports, and checking MCP health.

Enables agents to work with Robot Framework by discovering tests and resources, drafting tests from requirements, dry-running and executing suites, and parsing output.xml results.

Enables agents and teams to manage versioned delivery work items, role-tagged handoffs, revision- and source-bound evidence, QA gate evaluation, and release-owner attestations through MCP tools.

Enables scanning text for policy and safety issues, generating test suite outlines, and checking the configuration/health of the evaluation setup.

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.

Enables input/output policy validation via MCP, including scanning text for policy and safety issues, generating test suite outlines, and checking configuration health.

An MCP server for validating AI-generated code through automated browser testing, evidence collection, and intelligent diagnostics.

Enables AI assistants to write and run mobile UI tests on Android and iOS simulators via natural language, supporting native and WebView apps without Appium.

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.

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.

Accessibility AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

An MCP server that generates, runs, and triages tests by introspecting Python modules or web pages, using structured LLM outputs for scenario generation and failure analysis.

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.

An MCP server for validating JSON against schemas, checking email deliverability, verifying URLs, assessing data quality, and validating API responses using RFC-compliant checks and heuristic analysis.

Enables AI assistants to interact with the Scorecard REST API for exploring endpoints, making test requests, and integrating the SDK into applications.

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.