A
licenseA
qualityA
maintenanceEnables converting images (JPEG, PNG, GIF, WebP) into text descriptions using OpenAI-compatible vision models, with support for both local files and URLs.
2
17 npm
MIT
mcp-vision-server
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TDQS
A4.4/5.0
Scored across 3 tools
Disambiguation5/5
Each tool has a clearly distinct purpose: vision_analyze for understanding/explaining images, vision_ocr for verbatim text extraction, and image_generate for creating images. The descriptions explicitly cross-reference each other to prevent confusion, leaving no ambiguity.
Naming Consistency4/5
The naming is mostly consistent with a domain prefix and action (vision_analyze, vision_ocr), but image_generate deviates by using 'image_' instead of 'vision_'. This is a minor inconsistency that does not hinder readability, but it is a noticeable break from the established pattern.
Tool Count5/5
Three tools is a well-scoped count for a vision server, covering analysis, OCR, and generation. Each tool addresses a distinct core capability, and there are no redundant or missing tools that would suggest over- or under-engineering.
Completeness5/5
For the stated domain of vision tasks, the tool surface is complete: understanding (analyze), text extraction (OCR), and creation (generate). There are no obvious missing operations that would force an agent into a dead end; the tools cover the primary workflows one would expect from a vision server.
Maintenance
ActivitySlowing
ResponsivenessNo issues