"User interfaces (UI) or UI design resources" matching MCP servers:

Small MCP server for GNOME Wayland desktop automation, enabling element lookup, activation, typing, screenshots, and wait helpers through AT-SPI and Mutter RemoteDesktop.

Enables AI agents to automate GUI interactions across Windows, Linux, macOS, Android, iOS, and browsers using structured platform APIs first, with vision grounding as a fallback for robust cross-platform computer use.

Enables local Windows UI automation and screen capture, targeting windows that are difficult to automate such as games and legacy apps, with tools for window management, mouse and keyboard input, and desktop capture.

Enables Claude to see and interact with any macOS application using natural language commands. Perfect for testing Mac applications, UI automation, and app development with AI assistance.

Bridges Claude Code to CNCjs to enable remote control and monitoring of GRBL-based CNC machines. It provides a comprehensive toolset for managing G-code jobs, machine movement, and safety operations through natural language.

A server that provides rich UI context and interaction capabilities to AI models, enabling deep understanding of user interfaces through visual analysis and precise interaction via Model Context Protocol.

A secure MCP gateway for Termux that exposes filesystem, shell, and Termux:API tools over a local HTTP endpoint with admin controls, job management, and upstream support.

MCP server that interacts with the Phone Link Windows app via UI Automation to read messages, calls, notifications, and photos, and perform actions like sending SMS and making calls.

Web agent that keeps working when a task leaves the browser: deterministic routing between the page DOM and Windows UI Automation, with LLM-free skill replay.

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

Enables MCP-speaking AI agents to operate a desktop and browser through structured UI inspection, mouse/keyboard gestures, tab-scoped browsing, and approved local screen recording with editing.

An open-source MCP server that lets any coding agent operate your computer like a person does—reading the UI through accessibility trees, clicking and typing in the background, showing an agent pointer, zooming into regions, and driving your signed-in Chrome on macOS, Windows, and Linux.

Playwright for the entire OS. Give AI agents eyes and hands on any desktop app — find, click, type, and read UI elements across Linux, macOS, and Windows.

Provides an MCP server for local low-power screen vision, enabling AI agents to perform OCR and UI detection on inaccessible screens (games, remote desktops) using NPU acceleration and system OCR.

Enables AI agents to see and drive a real Android phone over plain ADB: screenshots and numbered UI trees, gestures, typing with accents and emoji, SMS/RCS reading and prepared replies, notifications, files, and settings, with no root and no app installed on the phone. Safeguards mask security codes and require explicit confirmation before sending, paying, deleting or confirming anything.

A TypeScript-based bridge between AI models and Android device functionality, enabling interaction with Android devices through ADB commands for tasks like app installation, file transfer, UI analysis, and shell command execution.

Reports the local user's current activity and idle state, including idle duration, idle threshold comparison, and timestamps, so agents can decide whether to wait for user feedback or keep working autonomously. All activity data is collected on-device through operating-system APIs and returned only to the connected MCP client.

Enables AI agents to control Android devices through the Android Debug Bridge, covering device listing, shell commands, app install/uninstall, logcat reading, screenshots, UI automation (tap/swipe/type/key events), dumpsys queries, file transfer, port forwarding, permission management, and Wi-Fi pairing. Failures are mapped to typed, actionable causes and tool calls are safety-annotated and guardrailed, with multi-device calls scoped explicitly by serial.

Enables low-cost agent models to control Windows applications through a compact, state-safe proxy over Open Computer Use, reducing model-visible context by up to 99.8% with support for record/replay and reusable UI component memory.

Gives AI agents safe, bounded, non-blocking access to Linux sysadmin inspection tasks, including CPU, RAM and disk healthchecks, memory-safe log tailing with regex filtering, and user-level systemd service and timer auditing. All operations run without sudo or unrestricted root shells, avoiding interactive pager hangs and context window flooding.