Image Gen MCP
Related Servers
Alternatives to Image Gen MCP
No user-submitted related servers found.
Related Servers
- AlicenseAqualityCmaintenanceAn MCP server that enables generating images via OpenAI and images/videos via Google Gemini (including Veo video generation), saving outputs to local asset folders. It integrates with Claude Code and any MCP client using your own API keys.3MIT
- FlicenseBqualityDmaintenanceEnables image generation and multi-turn editing sessions using the Gemini API within MCP-compatible environments. Users can create, modify, and configure images through natural language commands, supporting features like aspect ratio adjustments and session-based image transformations.5-
- AlicenseBqualityDmaintenanceMCP server for generating and editing images using OpenAI, and creating videos using OpenAI Sora and Google Veo. Enables fetching media from URLs or disk with smart output placement.41413 npm9MIT
- AlicenseAqualityAmaintenanceEnables any MCP client to generate and edit images through ChatGPT's Codex backend, saving them locally with no API key or per-image billing.566 npm4Apache 2.0
- FlicenseNot gradedqualityDmaintenanceAn MCP server for AI-powered image processing (generate, edit, vary, analyze) supporting OpenAI, Gemini, Ideogram, and custom relay endpoints.-
- AlicenseNot gradedqualityFmaintenanceAn MCP tool server that enables generating and editing images through OpenAI's image models, supporting text-to-image generation and advanced image editing (inpainting, outpainting) across various MCP-compatible clients.115MIT
TDQS
Scored across 2 tools
The two tools are clearly distinct: one generates images via Gemini, the other via OpenAI. Each has unique parameters (model lists, size formats, settings) that make selection unambiguous based on which provider the agent needs.
Both tools follow a consistent generate_image_{provider} pattern with snake_case naming. The verb 'generate' and noun 'image' are used uniformly, with the provider suffix distinguishing them clearly.
Two tools is on the thin side for a server, but for a focused image generation purpose, two tools (one per provider) is a reasonable and intentional scope. The slight deduction is for the low count.
The server covers image generation for two major providers, which covers the core generation workflow. However, there are no complementary operations like listing generated images, deleting them, or fetching generation history—the surface is purely one-directional (generate and save).