NanoBanana 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 |
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 |
|---|---|
| gemini_generate_imageB | Generate an image from a text prompt using the Google Gemini Nano Banana image generation model. Args:
Returns:
Examples:
|
| gemini_edit_imageA | Edit or transform one or more images using a text instruction, powered by the Google Gemini Nano Banana image model. Supports single or multiple input images. Provide file paths and/or base64-encoded image data along with a text instruction. Args:
Returns:
Examples:
|
| gemini_upload_imageA | Upload one or more images to the Gemini Files API and return their file URIs. Use this to pre-upload reference images before calling gemini_batch_submit. Uploaded files persist for 48 hours on Google's servers. Pass the returned URIs to batch_submit via the file_uris field to avoid slow base64 encoding. Args:
Returns:
|
| gemini_batch_submitA | Submit a batch of image generation requests to the Gemini API at 50% reduced cost. Builds a JSONL file, uploads it to the Gemini Files API, and submits a batch job. The job processes asynchronously (usually completes within minutes). Returns the batch ID — the caller is responsible for tracking it (e.g. in Supabase). Args:
Returns:
|
| gemini_batch_statusA | Check the status of a batch image generation job. Args:
Returns:
|
| gemini_batch_resultsA | Download and save images from a completed batch job. Checks the batch status, retrieves the output JSONL from Gemini, decodes each image, and saves them to the specified output directory using the key as the filename. Args:
Returns:
|
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 6 tools
Each tool has a clearly distinct purpose: batch submission, status checking, result downloading, single image generation, single image editing, and image upload. No overlap or confusion possible.
All tools use the consistent pattern 'gemini_<verb>_<noun>' with snake_case (e.g., gemini_batch_submit, gemini_edit_image). No deviations or mixed conventions.
6 tools cover both single and batch image operations plus upload and editing, which is well-scoped for the server's purpose. Not too few or too many.
Core workflows (generate, edit, batch submit/status/results, upload) are covered. Minor gaps like deleting batches or listing all batches are missing but not critical for typical usage.