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Enable AI agents to perceive and understand physical spaces through depth vision.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "rosclaw-vision-mcp" yet — see the docs or source repo.
Observe the current desk scene through the RealSense camera, identify visible objects, estimate their relative positions, and return a structured list with names, directions, and distances.
A list of visible desk objects with their approximate spatial positions and distance information.
Analyze the current depth view from the camera, determine whether obstacles exist in the forward path, and report the nearest obstacle's position and estimated distance.
A result indicating whether obstacles exist, where the nearest one is, and a brief assessment for avoidance.
Inspect the current room view, summarize the main spatial structure, identify elements such as walls, floor, and furniture, and describe traversable areas.
A concise description of the room layout, including key environmental elements and traversable space.
Enable AI to understand images with vision analysis, detection, and color extraction.
Connect LLMs with ROS robots for intelligent control and automation.
Connect LLMs to ROS robots for command-driven interaction and automation.
Let a local AI watch screens and automate native desktop actions.
Give AI agents real-time vision, spatial, acoustic, and environmental perception.
Analyze images through one MCP tool using any OpenAI-compatible endpoint.