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Glama

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Alternatives to Touchpoint

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  • A
    license
    Not graded
    quality
    B
    maintenance
    Lets AI agents see and control desktop applications through the accessibility layer, enabling clicking, typing, scrolling, dragging, and window/app management across macOS, Windows, and Linux entirely on the local machine.
    25
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables AI agents to observe and operate real desktops, mobile devices, and browser pages through screenshots, native accessibility trees, and web automation, including clicking, typing, hotkeys, and UI lookup across macOS, Linux, Windows, Android, and iOS.
    7
    Apache 2.0
  • A
    license
    A
    quality
    C
    maintenance
    Enables AI agents to observe and operate a real Windows or Linux desktop like a human — snapshotting screen geometry, active window, OCR text and normalized UI elements, then clicking, typing, scrolling and managing windows with built-in verification and recovery. Backends are chosen automatically per action (UIA/AT-SPI → OCR → vision → PyAutoGUI), so browsers, IDEs, office suites and canvas apps are all controllable without any browser-automation MCP.
    29
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    Enables AI agents to see and control your desktop with tools for screenshots, clicks, typing, and more, all locally on macOS and Windows.
    107 npm
    MIT
  • A
    license
    A
    quality
    B
    maintenance
    Computer use for any AI agent on macOS, Windows and Linux. It reads apps through the accessibility tree and screenshots, acts on elements by index, runs locally with no account, and the person at the keyboard can stop it at any time.
    13
    4
    MIT

TDQS

A4/5.0

Scored across 27 tools

Disambiguation5/5

Each tool targets a distinct resource and action: discovery (apps, windows, find, snapshot, screenshot), element inspection (get_element), input (click, set_value, set_numeric_value, focus, select_text, type_text, press_key), and window management (activate, minimize, close, move, resize, fullscreen). Overlaps like find vs wait_for are differentiated by polling behavior, and mouse_move/scroll have distinct roles.

Naming Consistency5/5

All tools follow a consistent lower_snake_case verb_noun pattern (mouse_move, minimize_window, activate_window, set_value, wait_for_window, etc.). Exceptionally uniform, with no mixed conventions or vague verbs. Even atypical names like 'find', 'snapshot', and 'action' function as clear verbs.

Tool Count4/5

At 27 tools, the count exceeds the typical 3-15 range, but the domain (cross-platform UI automation) justifies the breadth. Each tool covers a distinct operation—discovery, inspection, input, window manipulation, and waiting—with no redundancy. The count feels justified by the complexity required to handle various platforms and web content.

Completeness5/5

The surface is remarkably complete for UI automation: it covers discovery (apps/windows/elements), inspection (snapshot, get_element, read_text), interaction (click, type, set_value, scroll, drag via coordinate/action), and synchronization (wait_for, wait_for_app, wait_for_window). The generic `action` tool covers any raw accessibility action, providing a fallback for unforeseen operations. No critical dead-ends.

Maintenance

ActivityInactive
ResponsivenessOutdated data