"Collaboration Between Multiple AIs via MCP (Master Control Program)" matching MCP servers:

AI 規格大師 — MCP server bridging specs (Linear / JIRA / GitHub Issues / Notion / Markdown / Figma) to tests, with bidirectional traceability and a spec-quality coach. Sibling to mk-qa-master.

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

Portable governance control-promotion CLI and MCP server.

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.

Enables AI coding assistants to run pre-publish security and code-quality scans across 17 categories, generate a 0–100 security score and Markdown report, quickly check critical vulnerabilities, and receive fix/refactor suggestions by finding ID.

Enables MCP clients such as Claude to drive the user's real Chrome in the background via the DevTools Protocol through a companion extension, exposing 32 tools for navigation, form input, screenshots, snapshots, script evaluation, network and console inspection, performance tracing and raw CDP commands, with control off by default and limited by allowed sites and blocked domains.

Enables coding agents to request, track, and verify independent cross-model reviews with structured findings, attachment hashes, and provenance receipts via Chrome Bridge, Codex, or Responses transports.

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 AI assistants to automate WeChat Developer Tools for mini programs, allowing navigation, inspection, and manipulation of pages and components through the miniprogram-automator API.

Enables rapid analysis of landing pages for SEO compliance, conversion structure, color contrast accessibility, and performance metrics with automated optimization suggestions and code snippets.

Enables comprehensive control of iOS simulators and real devices through AI assistants, supporting app management, UI automation, screenshots, media operations, and location simulation for iOS development and testing workflows.

A local observation-only MCP server for macOS that provides secure, atomic evidence capture with strict target approval and manifest-based output.

Detects whether sensitive data like emails, SSNs, and phone numbers survive in supposedly redacted PDFs, running entirely locally via WebAssembly.

A universal MCP server that dynamically generates and simulates actions for any query, maintaining state between sessions.

MCP server providing three QA tools: parse JUnit XML reports, detect flaky tests across multiple runs, and evaluate quality gates with pass/fail decisions.

Enables MCP clients to control a Nordic PPK2 for power profiling: configure source/measurement modes, set voltage, power DUT, measure current/power/energy, and capture logic channels.

MCP server for WeChat Mini Program debugging and automation, enabling agents to perform UI operations, screenshots, and regression testing through natural language commands.

MCP server for semi-manual QA test execution on real Smart TVs (Tizen/webOS) and local Chrome via Chrome DevTools Protocol, enabling remote control, state inspection, and profiling.

Scans live web pages and single-page apps across multiple viewports to detect WCAG 2.1 AA accessibility violations and returns concrete, browser-verified fixes grounded in WCAG success criteria and techniques.

Generates synthetic time-series test data with configurable trend, seasonality, noise, anomalies, and multiple correlated streams, outputting JSON, CSV, or SQL.