"Foundry Virtual Tabletop" matching MCP servers:

A Docker-based MCP server that enables AI to securely run Foundry test commands in isolated containers, with automatic dependency management and cleanup.

Enables end-to-end testing of voice-enabled web applications by simulating a synthetic user with a virtual microphone, virtual speakers, a real browser, and a viewable display, allowing audio injection, speech capture/transcription, and browser automation.

Virtual phone number platform for AI agents — rent numbers across 200+ countries, receive SMS, and manage the full activation lifecycle.

Enables playing and observing a running Unreal Engine 5 game through virtual gamepad, keyboard, and mouse input, plus screen capture, log streaming, and UMG UI inspection and control.

Enables programmatic control and AI-driven E2E testing of iOS virtual machines by exposing display, touch input, and navigation tools. It provides hardware key emulation, app navigation, and raw touch interactions with inline screenshot feedback for real-time visual context.

An MCP server for automating virtual or physical Android devices using the Gbox SDK. It enables users to manage app installations, capture screenshots, and perform complex UI actions through natural language instructions.

Enables AI assistants to interact with Sauce Labs testing platform through natural language, providing access to device cloud management, test job analysis, build monitoring, and testing infrastructure insights. Supports both Virtual Device Cloud (VDC) and Real Device Cloud (RDC) with comprehensive test analytics and team collaboration features.

Connects AI tools to BlazeMeter's Service Virtualization platform, enabling natural language management of virtual services, transactions, and configurations.

MCP server for refereeing tabletop RPG sessions by analyzing transcripts against a configurable charter, providing deterministic findings on rule violations like unanswered questions or unacknowledged dice rolls.

Enables AI agents to inspect, interact with, and automate VTable virtual tables and surrounding web UIs through MCP, including trusted clicks, cell reading, drag-and-drop, browser/Playwright control, and interactive UI panels for test case execution.

Automates Android Virtual Device operations by enabling users to start emulators, execute development commands, and capture screenshots. It facilitates Android testing workflows by returning command outputs and visual feedback directly to AI assistants.

A Model Context Protocol (MCP) server implementation that allows AI assistants to run k6 load tests through natural language commands, supporting custom test durations and virtual users.

MCP server that lets AI agents see and interact with terminal/CLI applications through virtual terminals and PNG screenshots.

Let agents list, schedule, and pull evidence packets for your org’s incident-response tabletop exercises (evidence of practice, never a compliance verdict).

Enables AI agents to automate Linux desktop GUI by launching and interacting with Wayland applications in isolated virtual KWin sessions, or connecting to live desktops for collaborative automation.

▎ Enables AI assistants to unleash a crowd of role-played virtual users — impatient shoppers, seniors, keyboard-only users, privacy hawks, chaos monkeys — on a website. Each persona browses in a real Chromium browser, files UX/QA findings in character, and the site receives a damage report with an S–F survival grade. Accusations can be cross-examined by up to three independent verification engines

Provides bounded, observable access to graphical apps, browsers, terminals, Android devices, virtual machines, and SSH hosts through MCP tools, enabling safe automation and app QA.

Enables spec-driven development workflows with AI assistants, providing tools for managing specification lifecycles, task dependencies, code navigation, testing, and automated reviews through a unified CLI and MCP interface.

Enables running k6 load tests with customizable duration and virtual users via natural language, with real-time output and LLM-powered analysis.