A
licenseA
qualityB
maintenanceEnables any MCP client to perform image understanding and OCR via any OpenAI-compatible vision-language model. Supports local, private inference without images leaving the machine.
2
40 npm
MIT
vision-bridge-mcp
by zgz518
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TDQS
A4.2/5.0
Scored across 2 tools
Disambiguation4/5
The two tools have clearly distinct primary purposes: look_at_image for general image understanding and extract_text_from_image for exact OCR transcription. There is a minor overlap when an image contains text, but the explicit OCR tool removes most ambiguity.
Naming Consistency5/5
Both tool names follow a consistent verb_noun pattern with lowercase snake_case (look_at_image, extract_text_from_image). The naming is predictable and clearly reflects each tool's function.
Tool Count3/5
With only two tools, the server feels minimally scoped. While the narrow focus on vision tasks is reasonable, the count is at the lower boundary and leaves the set feeling thin rather than comprehensive.
Completeness4/5
The server covers the two most essential vision bridge capabilities—image understanding and text extraction. However, other potentially useful operations like object detection or image comparison are absent, leaving minor gaps in the surface.
Maintenance
ActivitySlowing
ResponsivenessNo issues