Skip to main content
Glama
Pgarciapg

MCP Nano Banana

by Pgarciapg
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Hybrid

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
GEMINI_API_KEYYesYour Google Gemini API key
IMAGEN_OUTPUT_DIRNoDirectory for generated images./generated-images

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

Server capabilities have not been inspected yet.

Tools

Functions exposed to the LLM to take actions

NameDescription
generate_imageA

Generate an image from a text prompt using Google Gemini's image generation.

Models available:

  • nano-banana (gemini-2.5-flash-image): Fast, efficient, 1024px resolution. Best for high-volume tasks.

  • nano-banana-pro (gemini-3-pro-image-preview): Advanced, up to 4K resolution, with thinking mode. Best for professional assets.

Tips for better results:

  • Describe the scene narratively, don't just list keywords

  • Be specific about lighting, camera angles, and styles

  • Use photography terms for photorealistic images

  • Specify aspect ratio based on your use case

edit_imageA

Edit an existing image using text prompts. Supports:

  • Adding/removing elements

  • Style transfer

  • Inpainting (changing specific parts)

  • Combining multiple images

Provide the path to an existing image and describe the changes you want.

compose_imagesA

Combine multiple images into a new composition.

nano-banana supports up to 3 input images. nano-banana-pro supports up to 14 input images (up to 5 humans, 6 objects).

Great for:

  • Product mockups

  • Fashion photos (dress on model)

  • Creative collages

  • Style transfer from multiple references

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

A4.1/5.0

Scored across 3 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: compose_images combines multiple images into a composition, edit_image modifies an existing image with text prompts, and generate_image creates a new image from a text prompt. There is no overlap in functionality, making it easy for an agent to select the correct tool.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern (compose_images, edit_image, generate_image), using snake_case throughout. The naming is predictable and readable, with no deviations in style.

Tool Count5/5

With 3 tools, the server is well-scoped for image generation and editing tasks. Each tool serves a unique and essential function in the domain, making the count appropriate and efficient for the server's purpose.

Completeness4/5

The tool set covers core image manipulation workflows: generation, editing, and composition. However, there is a minor gap in operations like deleting or managing images, which might be needed for a full lifecycle, but agents can likely work around this given the server's focus on creation and modification.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources