A
licenseA
qualityB
maintenanceEnables non-multimodal models to see images by providing MCP tools for image understanding and OCR, backed by any OpenAI-compatible vision model.
2
MIT
GLM Vision MCP
by xiayuyang750
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TDQS
A4.5/5.0
Scored across 4 tools
Disambiguation4/5
Most tools have distinct purposes: see_image for Q&A, extract_text for OCR, analyze_chart for charts/diagrams, and describe_image for general descriptions. However, see_image and describe_image overlap somewhat, as see_image with a default question essentially generates a description. The descriptions help clarify intent, so the ambiguity is limited.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern in lowercase with underscores: see_image, extract_text, analyze_chart, describe_image. This makes the API predictable and easy to navigate.
Tool Count5/5
With 4 tools, the server is well-scoped for a vision MCP. Each tool covers a distinct core capability (Q&A, OCR, chart analysis, description) without unnecessary bloat. The count is appropriate for the domain.
Completeness4/5
The tool surface covers the major vision use cases: answering questions, extracting text, analyzing charts, and generating descriptions. Minor gaps exist, such as no explicit image comparison or object detection, but these are not core for a generic vision server. Overall, the coverage is solid with no dead ends.
Maintenance
ActivityStale
ResponsivenessNo issues