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Glama
someshwarpatil

gemini-image-mcp

by someshwarpatil
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
GOOGLE_CLOUD_PROJECTYesGCP project serving the Vertex image models. (auto-detected from ADC / gcloud)
GOOGLE_CLOUD_LOCATIONNoVertex location for the Gemini models. Leave as 'global'.global
GEMINI_IMAGE_LOG_LEVELNostderr log level for the server (DEBUG/INFO/WARNING/ERROR).INFO
GEMINI_IMAGE_OUTPUT_DIRNoDefault dir for saved PNGs when a call omits output_dir. Falls back to the server CWD.
GEMINI_IMAGE_IMAGEN_LOCATIONNoVertex location for the Imagen models.us-central1

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

CapabilityDetails
tools
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
generate_imageA

Generate image(s) from a text prompt.

Args:
    prompt: The text description of the image to generate.
    model: Friendly alias — nano-banana (default), nano-banana-pro, imagen-4,
        imagen-4-fast, imagen-4-ultra. Call list_models for details.
    aspect_ratio: e.g. "1:1", "16:9", "9:16". Allowed values depend on the model.
    n: Number of images (Gemini loops one per call; imagen-4-ultra supports 1 only).
    output_dir: Where to save the full-res PNG(s). Defaults to env
        GEMINI_IMAGE_OUTPUT_DIR, else the server's CWD.
    return_image: When True, append a downscaled preview of the first image.

Returns:
    A list of text lines (one per saved absolute path), optionally followed by a
    downscaled preview Image of the first result.
edit_imageA

Edit or fuse input image(s) with an instruction (Gemini aliases only).

One input image = edit; two or more = fusion. Imagen models are text-to-image only
and are rejected here.

Args:
    image_paths: Absolute paths to the input image(s).
    prompt: The editing / fusion instruction.
    model: nano-banana (default) or nano-banana-pro.
    output_dir: Where to save the full-res PNG. Defaults to env
        GEMINI_IMAGE_OUTPUT_DIR, else the server's CWD.
    return_image: When True, append a downscaled preview of the result.

Returns:
    A text line with the saved absolute path, optionally followed by a downscaled
    preview Image.
list_modelsA

List the friendly model aliases, their real Vertex ids, and usage notes.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

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

A4.4/5.0

Scored across 3 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: edit_image handles editing/fusion, generate_image handles generation from text, and list_models provides model information. No overlap or ambiguity.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern (edit_image, generate_image, list_models) using snake_case, making the set predictable and readable.

Tool Count4/5

With only 3 tools, the set is slightly underpopulated but reasonable for a focused image generation/editing server. The scope is narrow enough that each tool earns its place.

Completeness4/5

Core operations (generate, edit/fuse, list models) are covered. Minor gaps like delete or get metadata exist, but the surface is functional for the primary use cases.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources