Nano-Banana-MCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| GEMINI_API_KEY | No | Your 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
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| configure_gemini_tokenA | Configure your Gemini API token for nano-banana image generation |
| generate_imageA | Generate a NEW image from text prompt. Use this ONLY when creating a completely new image, not when modifying an existing one. |
| edit_imageA | Edit a SPECIFIC existing image file, optionally using additional reference images. Use this when you have the exact file path of an image to modify. |
| get_configuration_statusA | Check if Gemini API token is configured |
| continue_editingA | Continue editing the LAST image that was generated or edited in this session, optionally using additional reference images. Use this for iterative improvements, modifications, or changes to the most recent image. This automatically uses the previous image without needing a file path. |
| get_last_image_infoA | Get information about the last generated/edited image in this session (file path, size, etc.). Use this to check what image is currently available for continue_editing. |
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 with no ambiguity. The descriptions explicitly differentiate between generating new images, editing specific files, continuing from the last image, and configuration tasks. The boundaries are well-defined, preventing misselection.
All tools follow a consistent verb_noun naming pattern (e.g., configure_gemini_token, generate_image, edit_image). The naming is uniform throughout, using snake_case and clear action-object pairs without any deviations.
With 6 tools, this server is well-scoped for image generation and editing. Each tool earns its place by covering essential operations like configuration, generation, editing, continuation, and status checks, without being overly sparse or bloated.
The tool set provides complete coverage for the nano-banana image generation domain. It includes configuration setup, new image generation, specific image editing, iterative editing, status checks, and session management, with no obvious gaps or dead ends for agents.