"Understanding Abstract Syntax Trees (AST)" matching MCP servers:

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.

macctl is an accessibility-first macOS desktop automation MCP server that lets AI clients see the screen, inspect app accessibility trees, control mouse/keyboard, manage windows, and run commands, all behind tiered permissions and audit logging.

Windows computer-use MCP server: accessibility-first element actions (UIA), UI read as diffed text trees instead of screenshots, guarded raw input, and a cross-session arbiter that yields to the human. 19 tools.

This server enables AI agents to operate Windows and Linux computers by observing the screen, understanding the UI through accessibility, OCR, and vision, and performing mouse, keyboard, window, clipboard, and system actions with verification and recovery.

This Model Context Protocol server enables AI assistants to interact directly with Ansible, allowing them to execute playbooks, manage inventory, check syntax, and perform other Ansible operations.

Enables high-speed native macOS automation for Claude by interacting directly with the Accessibility API, AppleScript, and UI trees instead of using screenshots. It allows users to read app states, click elements, and type text semantically across any macOS application.

Enables local macOS computer use by letting agents click, type, and inspect accessibility trees without stealing focus, through an unofficial host for OpenAI Computer Use.

Enables MCP clients to start and stop local read-only Windows 11 screen observation sessions, then inspect redacted screen state, UI trees, frames, and wait for changes, title matches, or idle periods through stdio tools.

Enables AI assistants to write, validate, debug, and execute AutoHotkey v2 scripts on Windows, with tools for syntax checking, script execution, active window inspection, library search, and live debugging via DBGp protocol.

Enables AI agents to observe and control the user's live desktop by listing apps, reading accessibility trees, and performing clicks, typing, scrolling, dragging, and other input actions with per-action approvals and local audit archives.

Enables AI assistants to inspect and control macOS apps via accessibility trees, screenshots, OCR, and input simulation, with a visible pointer.

Enables AI clients on Windows to control the local mouse, keyboard, and screen understanding via MCP stdio, allowing automated workflows like viewing the screen, locating elements, clicking, typing, and verifying results.

Enables MCP clients to discover desktop applications with structured metadata and receive native accessibility trees and screenshot content through Open Computer Use, preserving upstream tool results and image blocks.

Controls a real Linux desktop from any MCP host. Reads accessibility trees, takes screenshots, and drives clicks, scrolls, and keystrokes across GNOME, KDE/KWin, Hyprland, i3, and COSMIC.

Enables AI agents to automate real desktop applications across Windows, Linux, and macOS using incremental screen perception, accessibility trees, OCR, and window management, dramatically reducing token usage compared to screenshot-per-step approaches.

Enables AI agents to automate Android and iOS devices, including emulators and physical devices, by capturing screenshots, reading UI accessibility trees, performing touch and text input, and managing app lifecycle and logs.

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.

Enables instant file and folder searching on Windows using Everything's blazing-fast search engine, supporting powerful search syntax including wildcards, regex, size filters, date filters, and comprehensive file information retrieval.

Enables the model to observe and control the live desktop via accessibility trees and screenshots, performing actions like clicking, typing, scrolling, dragging, and setting values.

Enables AI agents to safely and truthfully control local desktop applications via native accessibility trees, supporting element inspection and automation without proprietary binaries or fake success responses.