image-gen-mcp
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- AlicenseAqualityBmaintenanceGenerates and edits images using OpenAI GPT Image or Google Gemini models, saving every result to disk and returning local file paths so AI assistants can continue working with the images. It enables prompt-based image creation, editing, inpainting, multi-image composition, and model listing through MCP tools.17 npm1Apache 2.0
- AlicenseNot gradedqualityCmaintenanceExposes multiple image generation backends as independent MCP tools for generating images with configurable models and parameters.MIT
- AlicenseNot gradedqualityNot gradedmaintenanceEnables AI assistants to generate and edit images through OpenAI's DALL-E models via MCP tools. Supports text-to-image generation and image-to-image editing with configurable parameters for size, quality, and style.-
- AlicenseNot gradedqualityCmaintenanceProvides multimodal vision MCP tools for image analysis, OCR, object detection, text-to-image generation, and image similarity, integrating OpenAI, Qwen, and Gemini.25 npm1MIT
- FlicenseNot gradedqualityBmaintenanceProvides an MCP interface to a unified image generation gateway, enabling AI agents to generate images through multiple free and low-cost providers, list sessions and history, and manage provider configurations.-
- AlicenseNot gradedqualityCmaintenanceEnables MCP-capable agents to generate and edit images through Gemini or OpenAI, returning an absolute file path instead of image bytes to keep context windows clean.MIT
TDQS
Scored across 2 tools
The two tools have completely distinct purposes: one lists available image models, the other generates images. No overlap or confusion possible.
Both tools use a consistent verb_noun pattern in snake_case: 'list_image_models' and 'generate_image', making them predictable and easy to understand.
With only 2 tools, the server feels under-scoped for its stated support of multiple providers and model selection. While minimal, it may be acceptable for a focused image generation task, but lacks coverage for related operations.
The server covers basic listing and generation, but lacks tools for retrieving generated images (URLs expire), managing providers, or handling model customization beyond the generate call. Minor gaps exist that could limit agent autonomy.