Midscene is a multimodal automation framework designed to enable AI agents to perceive, navigate, and manipulate graphical user interfaces across web, mobile, and desktop environments. By leveraging vision-capable AI models, the platform interprets interface screenshots to execute tasks based on natural language instructions, removing the reliance on traditional, brittle code-based selectors.
The framework distinguishes itself through its ability to decompose high-level goals into autonomous, multi-step sequences that function consistently across diverse platforms. It provides a visual grounding feedback loop that maps natural language commands to specific screen coordinates, while offering interactive execution tracing and visual reports that allow developers to replay and troubleshoot the agent's decision-making process.
Beyond core automation, the project supports structured data extraction from visual elements and integrates with existing development pipelines through native interfaces for Python and Java. It also provides command-line and tool-based exposure, allowing external AI coding assistants to trigger interface actions or inspect application states programmatically.
The framework includes utilities for managing application lifecycles, attaching to active browser sessions, and connecting to remote or headless environments. Performance is optimized through execution plan caching and real-time screenshot streaming to reduce latency during automated workflows.
