mcp-alphabanana
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| GEMINI_API_KEY | Yes | The Google Gemini API key required for image generation. | |
| MCP_FALLBACK_OUTPUT | No | Optional: Set a custom fallback directory for write failures. |
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
} |
| logging | {} |
| completions | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| generate_imageA | Generate image assets using Gemini AI with optional transparency and reference images. [Claude Desktop Guidance]
[Model Guidance]
[Thinking] thinking_mode accepts minimal, medium, high (default: medium, matching NanoBanana2.1's model default). NanoBanana2.1 supports all three levels; Flash3.1 and Pro3 support minimal/high and fall back to their own default when given an unsupported level. [Resolutions] output_resolution supports 1K, 2K and 4K (0.5K was removed in v1.6.0). It is auto-selected from the requested pixel size in normal mode. [Aspect Ratios] Gemini supports the following aspect ratios (model-dependent):
Normal mode: provide outputWidth/outputHeight and the server will choose the closest Gemini aspect ratio and source resolution, then resize to the requested pixel size. No-resize mode: set noresize=true and provide aspectRatio plus output_resolution. The server will return Gemini's native pixel dimensions for that combination without post-generation resizing. If you intentionally want to control resizing/cropping in normal mode, use the 'resizeMode' parameter: 'crop' (default, center crop), 'letterbox' (fit with padding), 'contain' (trim transparent margins then fit), or 'stretch' (distort to fit). [IMPORTANT] Always preserve the user's prompt as-is, including language and nuance. Do not translate or summarize. |
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 a single tool there is no possibility of misselection; generate_image has one unambiguous purpose. The extensive guidance distinguishes modes and parameters rather than competing tools, so no disambiguation burden is placed on the agent.
generate_image follows a clear verb_noun snake_case pattern. There are no other names to conflict with, so consistency is trivially satisfied and readable.
A one-tool surface is thin for what is effectively a full image-generation service with multiple models, resolutions, reference handling, and resize modes. Much of that surface is expressed through parameters and documentation rather than discoverable tools, making the count borderline.
Core generation is well covered: model choice, resolution, aspect ratio, transparency, reference images, and resize behavior are all parameterized. Minor gaps exist around ancillary operations such as editing/upscaling existing assets or programmatically listing available models, which are only described in prose guidance.