A
licenseNot graded
qualityD
maintenanceA lightweight stdio MCP server that adds image understanding to AI coding assistants via a single tool that sends images to any OpenAI-compatible multimodal endpoint.
MIT
snipaya-mcp
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TDQS
A3.6/5.0
Scored across 28 tools
Disambiguation4/5
Most tools have clearly distinct purposes: annotation creation, selection, arrangement, export, and canvas inspection are separated well. A few boundaries are adjacent rather than ambiguous, such as render vs export/export_to, add_shape blur/noise vs redact, and delete_items vs undo. The descriptions generally resolve these, so an agent can choose correctly.
Naming Consistency4/5
All tools use the snipaya_ prefix with snake_case, which is highly consistent. However, naming is not a strict verb_noun pattern throughout: many annotation tools use add_, but there are also verb-only names like redact, render, select, arrange, undo, redo, export, and the noun-like tabs. Still, the convention is predictable and readable.
Tool Count3/5
The 28-tool surface is heavy, but the domain is feature-rich image annotation and covers many distinct annotation primitives. Each tool has a plausible place, yet the set could likely be consolidated with a more generic annotation tool rather than exposing every annotation type separately. The count is borderline for an MCP server but not chaotic.
Completeness4/5
The server covers the annotation lifecycle well: inspect canvas, add diverse annotation types, read/select/update/delete elements, undo/redo, manage tabs, and export/save. Minor gaps remain, notably no obvious open/load project tool despite save_project, and no destination-management tool beyond listing existing destinations. These are workable gaps rather than dead ends for core annotation workflows.
Maintenance
ActivityMaintained
ResponsivenessSyncing