Enables AI clients to list configured cameras, fetch current JPEG frames from video files, webcams, or RTSP/HTTP streams, run local YOLO object detection, and count objects inside named polygonal zones using normalized coordinates. Answers come back as compact JSON with timestamps and image age, so a model can respond to questions like "Is anyone there?" or "How many cars are parked?" while only requesting the actual image when needed.
An MCP server that provides LLM agents with direct access to webcam hardware for capturing high-resolution photos and recording video sequences. It enables autonomous agents to monitor environments and interact with the physical world through standard Model Context Protocol tools.
An MCP server that enables interaction with local camera devices to capture and process images. It allows LLMs to access video devices with configurable settings such as resolution, orientation, and image format.
Provides OpenCV computer vision capabilities for AI assistants, enabling image processing, object detection, face detection, and video analysis through natural language.
Enables AI coding agents to capture screens and webcam frames, extract on-screen text with OCR, wait for visual changes, and obtain AI-generated scene descriptions.