agent-vision
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No user-submitted related servers found.
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- FlicenseBqualityDmaintenanceA Python-based MCP server that adds image analysis capabilities to text-only LLMs via a single analyze_image tool, supporting local files, URLs, auto-scaling, and multiple OpenAI-compatible APIs.1-
- AlicenseAqualityDmaintenanceMCP server that provides visual question answering, image description, object detection, OCR, and image manipulation tools using OpenAI-compatible vision models.12405 npmGPL 2.0
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TDQS
Scored across 3 tools
The three tools target clearly distinct actions and modalities: image generation, image analysis, and video analysis. The analyze_image description also explicitly clarifies when not to use it, reducing misselection risk.
All tools follow a consistent verb_noun pattern: generate_image, analyze_image, analyze_video. The convention is predictable and directly reflects each tool's purpose.
Three tools are well-scoped for a focused vision server: generation, image understanding, and video understanding. Each tool has a clear reason to exist, with no redundant surface area.
The core lifecycle for vision tasks is covered: create images, inspect images, and inspect videos. Minor gaps exist, such as image editing/transformation or batch analysis, but agents can work around them for most stated use cases.