multi_uiautomator2
Related Servers
Alternatives to multi_uiautomator2
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityCmaintenanceAn MCP server that provides tools for controlling Android devices using uiautomator2, enabling AI to automate tasks like tapping, swiping, and managing apps.41Apache 2.0
- FlicenseAqualityDmaintenanceAn MCP server designed for Android development, enabling AI assistants to directly control Android devices for screenshots, UI analysis, app management, and more.19-
- FlicenseNot gradedqualityBmaintenanceEnables agents to interact with Android via text-based UI trees instead of screenshots, supporting taps, swipes, input, macro recording, and device control through an MCP server and CLI.-
- AlicenseNot gradedqualityCmaintenanceMCP server that enables LLMs to control Android devices via ADB, providing tools for screen interaction and UI inspection.1MIT
- FlicenseAqualityDmaintenanceA MCP server that enables AI assistants to control Android devices via ADB, supporting device info, screen control, input simulation, app management, shell execution, file transfer, and UI parsing.20-
- AlicenseAqualityDmaintenanceA 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.8430Apache 2.0
TDQS
Scored across 24 tools
Tools are largely distinct, but there is some overlap between screenshot/get_screen_elements (both observe the screen) and among the AI-powered tools (ai_debug_screen vs ai_understand_screen vs ai_execute_goal). Descriptions clarify differences, but an agent might occasionally misselect between observation and AI analysis tools.
Most tool names follow a verb_noun pattern (e.g., list_devices, start_app, input_text). The main deviation is 'screenshot', which is a noun without an explicit verb, and 'press_key' could be seen as slightly inconsistent but still clear. Overall, the naming is predictable and readable.
With 24 tools, the server is on the heavier side (16-25 is considered heavy). However, the count is justified by the breadth of features: device management, app lifecycle, UI interactions, observation, and AI delegation. Still, some tools (like the three AI ones) might be consolidated, making the set feel slightly bloated.
The toolset covers the core lifecycle: device connection, app control, UI interaction (tap, swipe, scroll, input), observation (screenshot, get_screen_elements), and waiting/finding elements. It lacks explicit handling of system dialogs or advanced gestures, but the AI tools can cover some gaps. Overall, no critical dead ends for typical automation workflows.