A
licenseA
qualityA
maintenanceEnables text-only coding agents to analyze local images using a dedicated vision provider, returning markdown and structured JSON evidence for screenshots, diagrams, UI mockups, and error captures.
11
90 npm
11
MIT
mcp-vision
by mikesmullin
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TDQS
A3.6/5.0
Scored across 3 tools
Disambiguation3/5
image_ocr is clearly separate (text extraction), but image_describe and image_decide both reduce to 'ask a model a question about an image' and differ mainly by answer format and backend model (Liquid CPU vs H2O). The descriptions help, but an agent must parse subtle wording to choose between free-text description and constrained boolean/choice/score answers.
Naming Consistency4/5
All three tools share a clean snake_case `image_` prefix, which makes them obviously part of one family. Minor deviation: `image_ocr` uses an acronym-noun while `image_describe`/`image_decide` use verbs, so the action pattern isn't perfectly uniform.
Tool Count4/5
Three tools is on the thin side but each covers a genuinely different modality (OCR with regions, free-text description, constrained decision/scoring). Nothing feels redundant, though the surface is small for a general vision server.
Completeness3/5
Core read-only vision operations are covered, but there is no image metadata/info tool, no object/localization tool beyond OCR regions, no multi-image comparison, and no preprocessing (crop/resize) step. Agents can partially work around these via describe/decide, but several natural vision tasks are dead ends.
Maintenance
ActivityMaintained
ResponsivenessNo issues