Computer Control
Computer Control MCP provides computer automation capabilities through a server that enables AI assistants to control mouse movements, keyboard input, take screenshots, perform OCR, and manage windows. Built with PyAutoGUI, RapidOCR, and ONNXRuntime, it offers similar functionality to Anthropic's 'computer-use' tool but with zero external dependencies. The implementation supports operations like clicking, typing, dragging, capturing screen content with text recognition, and window management, making it particularly useful for automating desktop tasks and enabling AI systems to interact directly with graphical user interfaces.
I/O
heuristic · beta该 skill 无 npm 包，暂用描述启发式推断 I/O；接入后可实测。
综合分
效果测评卡
进行中 · 待运行真实 I/O 已解决「输入输出是什么」；下一步接 agent 真跑，量化「效果好不好」。
Enables automation of Android devices and iOS simulators through a unified API. Supports device listing, screenshots with automatic compression for LLM processing, tap and swipe gestures by coordinates or element text, text input, app launching and installation, UI hierarchy inspection, device logs retrieval, and shell command execution. Provides cross-platform device control for mobile testing and debugging workflows.
Provides direct control over iOS simulators and physical iPhones through a unified interface that combines Facebook's idb for simulators and WebDriverAgent for physical devices. Features automated device discovery, real-time screen streaming via WebSocket for physical devices, and comprehensive interaction tools including tap, swipe, text input, button presses, screenshot capture, app launching, and UI element scanning. Supports both global and project-scoped setup with auto-configuration for Claude Code, Cursor, Codex, and OpenCode.
WeChat Mini-Program Agent enables AI-driven automation and testing of WeChat Mini Programs through a wrapper around miniprogram-automator's WebSocket interface to WeChat DevTools. Supported operations include page navigation, screenshot capture, UI element interaction, DOM inspection, and scenario testing. A serial execution model ensures predictable test flows for agent-first development workflows.