A
licenseA
qualityC
maintenanceAn MCP server that generates and edits images using OpenAI's GPT Image model, allowing users to create images from text descriptions and edit existing images through natural language.
1
15 npm
MIT
MCP OpenAI Images
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TDQS
A4.2/5.0
Scored across 6 tools
Disambiguation5/5
Every tool targets a distinct operation: generation from prompt, variation from references, composition via crop/overlay, font installation, model listing, and expense summary. The two 'generar' tools are clearly differentiated by input type and purpose, so there's no ambiguity.
Naming Consistency4/5
Most tools follow a verb_noun pattern (generar_imagen, generar_variacion, componer_imagen, instalar_fuente_google, listar_modelos_imagen), but 'resumen_gasto' is a noun phrase rather than a verb. This single deviation prevents a perfect score.
Tool Count5/5
With 6 tools, the server is well-scoped for an image generation workflow. Each tool has a clear role, and the count feels neither sparse nor overwhelming — it's a tight, purposeful set.
Completeness5/5
The surface covers the core image lifecycle: creation, variation, editing, styling, model discovery, and cost tracking. There are no obvious dead ends or missing operations for the stated domain of OpenAI image generation.
Maintenance
ActivityMaintained
ResponsivenessNo issues