vision-eyes
Related Servers
Alternatives to vision-eyes
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityAmaintenanceProvides local image understanding for text-only LLMs with tools for image analysis, OCR, object detection, and cropping, all processed on-device.2MIT
- AlicenseNot gradedqualityCmaintenanceEnables AI assistants to perform local computer-vision-based image recognition and editing, including cropping, resizing, rotating, background removal, drawing text and shapes, object detection, OCR, overlays, and metadata inspection without sending images to external servers.MIT
- AlicenseNot gradedqualityCmaintenanceEnables text-only LLMs to perceive images entirely on-device, providing vision capabilities like image description, OCR, table extraction, UI analysis, and region focusing without any cloud APIs or API keys.MIT
- AlicenseAqualityDmaintenanceEnables AI agents to analyze images, extract text, compare images, and analyze video through any OpenAI-compatible vision model.4151 npm20MIT
- FlicenseAqualityNot gradedmaintenanceEnables AI agents to analyze images through vision AI providers (Gemini, OpenAI, Claude), performing tasks like image description, object detection with bounding boxes, region-specific analysis, and precise color extraction without consuming context window with raw pixels.4-
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to process images locally via file paths—converting, resizing, removing backgrounds, smart cropping, upscaling, reading or stripping metadata, and batch processing—without files ever leaving the device.MIT
TDQS
Scored across 1 tool
There is only one tool, so there is no risk of selecting the wrong tool. The internal action modes are clearly separated and described, making each use case easy to distinguish.
With a single tool, there is no naming inconsistency to penalize. 'vision_eyes' is a clear, snake_case, descriptive name that matches the server's purpose.
A single tool is on the low end of tool countsainer, but the tool is not trivial since it packs many actions into an action parameter. The unified design is reasonable, though splitting it into separate tools might improve clarity.
The single tool covers a wide range of local image needs: analysis, exact pixel lookup, cropping, grid overlays, image comparison, and classification. The main gap is that it relies on optional local-ai installation for classification and lacks some advanced image operations, but core 'eyes' functionality is well covered.