mcp-image-gen
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Alternatives to mcp-image-gen
No user-submitted related servers found.
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- AlicenseAqualityAmaintenanceWraps OpenAI-compatible text-to-image APIs as MCP tools, enabling image generation directly from conversations in Claude Code, Codex, Cursor, or Claude Desktop using the user's own API key.61Apache 2.0
- AlicenseNot gradedqualityBmaintenanceEnables coding agents and other MCP clients to generate images from text prompts and edit, restyle, or extend existing images through an OpenAI-compatible /v1/images API. Results are returned both inline as image content blocks and as files saved to disk, so agents can view and reuse them within a normal task.25 npm1MIT
- AlicenseNot gradedqualityDmaintenanceEnables AI agents to generate images and videos through natural language by exposing ComfyUI workflows as parameter-configurable MCP tools.10MIT
- AlicenseNot gradedqualityCmaintenanceEnables MCP clients to generate images from text prompts and edit existing PNG/JPEG files with natural-language instructions by driving a local ComfyUI instance running Qwen Image models. Supports aspect ratios, exact pixel dimensions, batch counts, and reproducible seeds, with matching capabilities exposed through a Python CLI.13,471 npm1MIT
- AlicenseNot gradedqualityCmaintenanceEnables MCP clients to generate and edit images through any OpenAI-compatible image API, saving results as local files and returning absolute paths for immediate use.18 npmMIT
- AlicenseAqualityCmaintenanceExposes OpenAI's gpt-image-2 and gpt-image-1.5 to Claude Code as a single tool for generating, editing, or composing images with automatic model selection.138 PyPI2MIT
TDQS
Scored across 1 tool
With a single tool there is no possibility of misselection or overlap. An agent's only choice is whether to call it at all, and the description makes the trigger conditions (generate a PNG from a prompt, with automatic backend fallback) unambiguous.
The single name follows a clean verb_noun snake_case convention (generate_image) that would scale predictably if more tools were added. No style mixing is possible with one tool.
One tool is thin even for a narrowly scoped server; the rubric treats 1-2 tools as borderline. It earns its place, but the surface feels underbuilt for a server whose apparent remit is image generation and management.
Generation is well covered, including a fallback backend, but there is no way to list, inspect, delete, or re-run previously generated images, and no way to check backend/API status. These are notable gaps an agent would hit when managing outputs, though core generation works.