"Debugging WebRTC SDK Implementation Issues in Visual Studio 2019" matching MCP servers:

Enables stateless, pure-visual control of Android devices and emulators through adb shell, providing screen capture, coordinate-based taps, swipes, keyboard input, and arbitrary adb command execution for agent-driven interaction.

Give any LLM agent a real Android or iPhone. 62 MCP tools: tap, swipe, type, screenshot, screen-tree reading, app launch, camera, TTS, crash reports, batched execution. Android via ADB, iPhone via WebDriverAgent, on-device inference, Docker+KVM emulators. Works with Claude Code, Cursor, LangChain, LlamaIndex, and any MCP client. MIT.

Enables AI agents to prepare and inspect STL/3MF files and run offline slicing on an isolated Windows desktop while leaving the mouse, keyboard, and visible desktop usable; also supports an X2D dual-nozzle workflow with offline validation of sliced 3MF archives and nozzle assignments.

Enables a Copilot Studio agent to operate a dedicated, disposable Windows VM by running commands, PowerShell scripts, file operations, and background jobs over authenticated HTTPS.

Enables mobile device automation for Android (via ADB) and iOS Simulator (via simctl), allowing you to control devices with natural language through screenshots, UI interactions, text input, and app management.

Enables AI agents to use Mint as a safety layer for file operations on macOS, providing storage growth analysis, cleanup suggestions, and journaled, reversible deletions via MCP tools.

Enables debugging and automation of native Electron applications on macOS through DOM inspection, UI automation, global hotkeys, and Chrome DevTools Protocol integration.

Stop Package Chaos: Unveil Your Mac’s Setup for Targeted ML Debugging

Windows desktop automation MCP server enabling screenshot capture, precise visual locating of UI elements via vision models, and automated mouse clicking.

A Model Context Protocol (MCP) server that enables AI assistants to control and interact with Android devices, allowing for device management, app debugging, system analysis, and UI automation through natural language commands.

Enables programmatic control over tmux terminal sessions for SSH access, command execution, and terminal automation. Supports creating sessions, sending commands, capturing output, and managing multiple panes for interactive debugging and monitoring.

MCP server that lets Claude Desktop or another MCP client trigger macOS sound and visual notifications through a task_status tool.

Fast file search across Windows (Everything SDK), macOS (Spotlight/mdfind) and Linux (locate/plocate). Single search tool with platform-specific filters, sorting and an optional configurable tool name.

Lets AI agents see and operate a physical computer below the OS level over WebRTC, from BIOS/UEFI and boot menus to installers and login screens. Provides HDMI screenshots, USB keyboard and mouse input, ATX power and Wake-on-LAN control, and virtual media such as CD-ROM images, disks, and a file-transfer USB drive.

Enables managing Keyboard Maestro macros with natural language commands, including creation, editing, execution, and debugging.

Enables AI agents to interact with Android devices through visual UI element detection and automated interactions. Provides comprehensive Android automation capabilities including touch gestures, text input, screenshots, and video recording via uiautomator2.

Enables MCP-compatible AI agents to access IBM z/OS jobs, datasets, USS files, and operational diagnostics through the Zowe SDK, with structured tool outputs and guardrails for mainframe operations.

Your sysadmin co-pilot — an AI that administers Linux through typed, approval-gated, Ed25519-audited actions instead of shell strings. Reference implementation of the LACS standard.

Enables AI-powered visual automation workflows by providing tools for searching nodes, creating and validating workflows, and executing automation scripts via natural language.

A server implementation that enables natural language interactions with UniFi network devices by wrapping the UniFi Network API for AI agents like Goose and Claude.

A privacy-first macOS MCP server that enables AI agents to capture screenshots of pre-approved application windows for development and debugging tasks.

An MCP server for headless Qt/PySide6 GUI testing that enables AI assistants to launch desktop applications via Xvfb and perform visual verification. It supports widget discovery, screenshot capture, and simulated user interactions like clicks, typing, and keyboard shortcuts.

Exposes the HyperDbg hypervisor-assisted, ring-0 debugger to LLM agents, enabling low-level debugging operations with safety features like read-only mode and confirmation gates.

Enables interaction with a persistent PowerShell session through LM Studio. Provides tools to run commands, manage directories, and handle environment variables while maintaining session state between calls.

Provides cross-platform terminal access through MCP, enabling AI assistants to create and manage interactive terminal sessions, execute commands, and capture visual snapshots on Windows, Linux, and macOS.

Enables MCP agents to run, continue, observe, check status of, and abort bounded GUI automation tasks through a shared local runtime with visual detection and deterministic input.

MCP server for capturing screenshots of desktop windows on Windows. Allows AI assistants to see what's on screen for UI development, debugging, and iterating on designs.

A high-performance Model Context Protocol (MCP) server built for Windows. Leveraging the native Everything SDK, it provides AI models (like Claude, GPT, Gemini) with millisecond-speed file searching, statistical analysis, and disk usage insights.

Enables LLMs to capture and analyze screenshots of your screen, windows, or regions with smart detection capabilities. Features natural language queries, automatic window targeting, and text enhancement for UI debugging and visual inspection.

Enables AI assistants to control Ubuntu desktops through screenshots, mouse clicks, and keyboard interactions using AT-SPI integration and computer vision. It features optimized element detection and workflow batching for fast and accurate visual interaction with desktop applications.