nanobanana-mcp-server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| LOG_LEVEL | No | Log level (DEBUG, INFO, WARNING, ERROR) | INFO |
| LOG_FORMAT | No | Log format (standard, json, detailed) | standard |
| GEMINI_API_KEY | Yes | Your Google Gemini API key (required) | |
| IMAGE_OUTPUT_DIR | No | Path to image directory | ~/nanobanana-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
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {
"tasks": {
"list": {},
"cancel": {},
"requests": {
"tools": {
"call": {}
},
"prompts": {
"get": {}
},
"resources": {
"read": {}
}
}
}
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| generate_imageA | Generate new images or edit existing images using natural language instructions. Supports multiple input modes:
Automatically detects mode based on parameters or can be explicitly controlled. Input images are read from the local filesystem to avoid massive token usage. Returns both MCP image content blocks and structured JSON with metadata. |
| upload_fileA | Upload a local file through the Gemini Files API and return its URI & metadata. Useful when the image is larger than 20MB or reused across prompts. |
| show_output_statsA | Show statistics about the output directory and recently generated images. |
| maintenanceB | Perform maintenance operations following workflows.md patterns. Available operations:
|
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| photorealistic_shot | Generate a prompt for high-quality photorealistic images. |
| logo_text | Generate a prompt for logo creation with accurate text rendering. |
| product_shot | Generate a prompt for studio product photography. |
| sticker_flat | Generate a prompt for flat/kawaii style stickers. |
| iterative_edit_instruction | Generate an instruction for precise image editing. |
| composition_and_style_transfer | Generate an instruction for style transfer and composition blending. |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| prompt_templates_catalog | A compact catalog of prompt templates (same schemas as the @mcp.prompt items). |
| list_operations | List all tracked operations. Returns: Dict with list of operations and summary statistics |
TDQS
Scored across 4 tools
The four tools have fairly distinct purposes: generate_image for creation/editing, upload_file for file management, show_output_stats for statistics, and maintenance for cleanup operations. There is a minor potential overlap between generate_image's file-based editing modes and upload_file, but the descriptions clarify when to use each.
Three tools follow a verb_noun pattern (generate_image, upload_file, show_output_stats), while 'maintenance' is a bare noun. This is a minor deviation, but the overall set remains readable and mostly consistent.
With only four tools, the server covers the core workflow of image generation, file uploading, output inspection, and system maintenance. Each tool clearly earns its place, and the count is well-suited to the server's focused purpose.
The toolset covers generation, editing, file upload, stats, and maintenance operations like cleanup and quota checks. Minor gaps include no dedicated tool to list or delete individual generated images, but the maintenance operations can handle cleanup indirectly.