codex-image-gen++
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- FlicenseAqualityCmaintenanceEnables generating and editing images through OpenAI image models, with configurable output as saved files or returned URLs.2-
- AlicenseNot gradedqualityBmaintenanceEnables image generation through any OpenAI-compatible images/generations endpoint, saving results to disk and returning them inline for the model.MIT
- AlicenseAqualityCmaintenanceEnables generating images through SmartAPI's image generation endpoint directly from Codex, saving files locally.1MIT
- FlicenseNot gradedqualityBmaintenanceEnables Codex to generate finite image batches using its built-in image tool, managing jobs, saving outputs, and supporting pause/resume.-
- FlicenseNot gradedqualityDmaintenanceEnables generating images from text prompts using OpenAI's GPT-Image-2 model within Claude Code and Codex conversations.1-
- FlicenseNot gradedqualityCmaintenanceEnables AI image generation, editing, upload, and local download through CloseAI's gpt-image-2 service, allowing MCP-compatible clients like Codex to manage images with configurable models, sizes, and quality.-
TDQS
Scored across 4 tools
Each tool has a clearly distinct purpose: list_models (discovery), generate_image (create), edit_image (modify), and get_job (poll). The descriptions explicitly disambiguate similar-sounding operations, e.g. generate_image vs. get_job and the warning that list_models doesn't prove generation permission.
All four tools follow a consistent verb_noun snake_case pattern (list_models, generate_image, edit_image, get_job). No mixing of conventions or vague verbs.
Four tools is a tight, well-scoped set for an image generation/editing server, with each tool earning its place. It's slightly lean, as there's no cancel or list-jobs operation.
The core lifecycle is covered: discover models, generate, poll job status, and edit images. Minor gaps remain around job management (no cancel_job or list_jobs), but agents can work around them.