Skip to main content
Glama
tasopen

mcp-alphabanana

by tasopen

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
GEMINI_API_KEYYesThe Google Gemini API key required for image generation.
MCP_FALLBACK_OUTPUTNoOptional: 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

CapabilityDetails
tools
{
  "listChanged": true
}
logging
{}
completions
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
generate_imageA

Generate image assets using Gemini AI with optional transparency and reference images.

[Claude Desktop Guidance]

  • Prefer outputType='file' for medium or large images. base64 and combine responses can exceed Claude Desktop's context limit.

  • On Claude Desktop for Windows, use the FileSystem extension to choose reference-image paths and a writable absolute outputPath before calling this tool.

  • Use base64 only for small previews or when the client explicitly needs inline image data.

[Model Guidance]

  • NanoBanana2.1 (default): Google Nano Banana 2.1 (gemini-nano-banana-2.1). Best overall quality, prompt adherence, character consistency, text rendering and reference-image handling. Supports 1K/2K/4K and up to 14 reference images, plus thinking and grounding.

  • Flash3.1 (deprecated): gemini-3.1-flash-image. Google shuts it down on October 29, 2026; requests are rejected from that date. Please migrate to NanoBanana2.1.

  • Lite3.1 (Nano Banana 2 Lite): Ultra-fast, cost-effective, 1K-only, no search grounding. Ideal for quick drafting and low-latency iteration.

  • Pro3: Higher fidelity, but more costly and slower.

  • Flash2.5: Legacy, maintained for compatibility. 1K only. Aliases: 'flash' resolves to NanoBanana2.1 (the default), 'pro' to Pro3.

[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):

  • Common to all models: 1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9

  • Flash3.1 only: 1:4, 4:1, 1:8, 8:1

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

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

A4.4/5.0

Scored across 1 tool

Disambiguation5/5

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.

Naming Consistency5/5

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.

Tool Count3/5

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.

Completeness4/5

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.

Maintenance

ActivityMaintained
ResponsivenessUnresponsive