Schema | Image Gen MCP

Image Gen MCP

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Server Configuration

Describes the environment variables required to run the server.

Name	Required	Description	Default
No arguments

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

Capability	Details
`tools`	{ "listChanged": true }

Tools

Functions exposed to the LLM to take actions

Name	Description
generate_image_geminiA	Generate one or more images with Google Gemini (Nano Banana) via the Interactions API and save them to disk. Use this when the user (or your plan) needs Gemini-generated assets for a website or app. Pass the Gemini image model id (e.g. gemini-3.1-flash-image, gemini-3-pro-image, gemini-2.5-flash-image), a list of prompt + filename pairs, the required absolute_output_directory, and optional response_format settings: aspect_ratio, image_size, mime_type. Notes: aspect_ratio: 1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9, 1:8, 8:1, 1:4, 4:1. image_size: 512, 1K, 2K, or 4K (uppercase K required). mime_type: currently only image/jpeg is supported. Images are written only to absolute_output_directory. It must be an absolute path; relative paths are rejected. Each file is named: {filename}-gemini-{model}-{timestamp}.{ext}
generate_image_openaiA	Generate one or more images with OpenAI's Image API and save them to disk. Use this when the user (or your plan) needs OpenAI-generated assets for a website or app. Pass the OpenAI image model id (e.g. gpt-image-2, gpt-image-1.5, gpt-image-1, dall-e-3), a list of prompt + filename pairs, the required absolute_output_directory, and optional settings: size, quality, background, output_format. Notes: size: standard GPT sizes are 1024x1024, 1536x1024, 1024x1536, or auto; gpt-image-2 also allows arbitrary WIDTHxHEIGHT (divisible by 16). quality: low/medium/high/auto for GPT image models; standard/hd for dall-e-3. background: transparent/opaque/auto; transparent is unsupported on gpt-image-2 and requires png or webp. output_format: png, jpeg, or webp (GPT image models only). Images are written only to absolute_output_directory. It must be an absolute path; relative paths are rejected. Each file is named: {filename}-openai-{model}-{timestamp}.{ext}

Name

Description

generate_image_geminiA

Generate one or more images with Google Gemini (Nano Banana) via the Interactions API and save them to disk.

Use this when the user (or your plan) needs Gemini-generated assets for a website or app. Pass the Gemini image model id (e.g. gemini-3.1-flash-image, gemini-3-pro-image, gemini-2.5-flash-image), a list of prompt + filename pairs, the required absolute_output_directory, and optional response_format settings: aspect_ratio, image_size, mime_type.

Notes:

aspect_ratio: 1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9, 1:8, 8:1, 1:4, 4:1.
image_size: 512, 1K, 2K, or 4K (uppercase K required).
mime_type: currently only image/jpeg is supported.

Images are written only to absolute_output_directory. It must be an absolute path; relative paths are rejected. Each file is named: {filename}-gemini-{model}-{timestamp}.{ext}

generate_image_openaiA

Generate one or more images with OpenAI's Image API and save them to disk.

Use this when the user (or your plan) needs OpenAI-generated assets for a website or app. Pass the OpenAI image model id (e.g. gpt-image-2, gpt-image-1.5, gpt-image-1, dall-e-3), a list of prompt + filename pairs, the required absolute_output_directory, and optional settings: size, quality, background, output_format.

Notes:

size: standard GPT sizes are 1024x1024, 1536x1024, 1024x1536, or auto; gpt-image-2 also allows arbitrary WIDTHxHEIGHT (divisible by 16).
quality: low/medium/high/auto for GPT image models; standard/hd for dall-e-3.
background: transparent/opaque/auto; transparent is unsupported on gpt-image-2 and requires png or webp.
output_format: png, jpeg, or webp (GPT image models only).

Images are written only to absolute_output_directory. It must be an absolute path; relative paths are rejected. Each file is named: {filename}-openai-{model}-{timestamp}.{ext}

Prompts

Interactive templates invoked by user choice

Name	Description
No prompts

Resources

Contextual data attached and managed by the client

Name	Description
No resources

Deploy Server

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A4.2/5.0

Scored 2026-08-04 02:05 across 2 tools

Disambiguation5/5

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.

Naming Consistency5/5

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.

Tool Count4/5

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.

Completeness3/5

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).

Maintenance

ActivitySlowing

ResponsivenessNo issues

Resources

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