Nano Banana MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| GEMINI_API_KEY | Yes | Your Google Gemini API key (from Google AI Studio), used to connect Claude to Nano Banana (Google's gemini-2.5-flash-image AI model). |
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 | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| generate_imageC | Generate an image using the Nano Banana (gemini-2.5-flash-image) model. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 1 tool
With only a single tool in the set, there is no possibility of confusion or misselection. The tool's purpose (image generation via a specific model) is unmistakable.
The lone tool follows a clear verb_noun snake_case convention (generate_image). There is nothing to be inconsistent with, so the naming is fully predictable.
One tool is a thin surface even for a focused image-generation wrapper; common needs like editing, variation, or configuration are not expressible. It is borderline rather than mismatched, since the server targets a single model.
Generation is covered, but an image-model server typically also supports editing/inpainting, variations, or parameter control (size, count, seed), none of which exist here. Agents can work with the single entry point but will hit dead ends for anything beyond plain generation.