Skip to main content
Glama
tasopen

mcp-alphabanana

by tasopen

mcp-alphabanana

npm version License: MIT

English | 日本語

mcp-alphabanana is a Model Context Protocol (MCP) server for generating image assets with Google Gemini. It is built for MCP-compatible clients and agent workflows that need fast image generation, transparent outputs, reference-image guidance, and flexible delivery formats.

Keywords: MCP server, Model Context Protocol, Gemini AI, image generation, FastMCP

Key capabilities:

  • Ultra-fast Gemini image generation across Lite, Flash, and Pro tiers

  • Transparent PNG/WebP asset output for web and game pipelines

  • Multi-image style guidance with local reference image files

  • Flexible file, base64, or combined outputs for agent workflows

alphabanana demo

Quick Start

Run the MCP server with npx:

npx -y @tasopen/mcp-alphabanana

Or add it to your MCP configuration:

{
  "mcp": {
    "servers": {
      "mcp-alphabanana": {
        "command": "npx",
        "args": ["-y", "@tasopen/mcp-alphabanana"],
        "env": {
          "GEMINI_API_KEY": "${env:GEMINI_API_KEY}"
        }
      }
    }
  }
}

Set GEMINI_API_KEY before starting the server.

For Claude Desktop, Download mcp-alphabanana-latest.mcpb, then add it as Extension from Claude Desktop Settings. For Windows, Recommend add 'FileSystem' extension for better local file handling.
Download MCPB

Related MCP server: nano-banana-claude

Claude Registry

The Claude registry / MCPB package metadata is defined in manifest.json and ships with the static 512x512 icon at images/mcp-alphabanana.png.

Native sharp runtime packages are declared as optional dependencies so .mcpb installs can resolve the correct prebuilt binary on each supported platform without relying on postinstall hooks.

  • Stable MCPB URL: https://github.com/tasopen/mcp-alphabanana/releases/latest/download/mcp-alphabanana-latest.mcpb

  • Versioned MCPB URL pattern: https://github.com/tasopen/mcp-alphabanana/releases/download/vVERSION/mcp-alphabanana-VERSION.mcpb

  • Support: GitHub Issues

MCP Server

This repository provides an MCP server that enables AI agents to generate images using Google Gemini.

It can be used with MCP-compatible clients such as:

  • Claude Desktop

  • VS Code MCP

  • Cursor

Built with FastMCP 3 for a simplified codebase and flexible output options.

Glama MCP Server badge:

Available Tools

generate_image

Generates images using Google Gemini with optional transparency, local reference images, grounding, and reasoning metadata.

For Claude Desktop, prefer outputType=file for medium or large images. base64 and combine responses consume Claude context and can hit the client's size limit. On Windows, use the FileSystem extension to choose a writable absolute outputPath and any local referenceImages paths.

Key parameters:

  • prompt (string): description of the image to generate

  • model: Flash3.1, Lite3.1, Flash2.5, Pro3, flash, pro

  • outputWidth and outputHeight: requested final image size in pixels in normal mode

  • noresize + aspectRatio + output_resolution: return Gemini native size without resizing

  • output_resolution: 0.5K, 1K, 2K, 4K

  • output_format: png, jpg, webp

  • outputType: file, base64, combine

  • outputPath: required when outputType is file or combine

  • transparent: enable transparent PNG/WebP post-processing

  • referenceImages: optional array of local reference image files

  • grounding_type and thinking_mode: advanced Gemini 3.1 controls

Model Selection

Input Model ID

Internal Model ID

Description

Flash3.1

gemini-3.1-flash-image

Ultra-fast, supports Thinking/Grounding.

Lite3.1

gemini-3.1-flash-lite-image

Ultra-fast, cost-effective 1K-only model. No Search Grounding.

Flash2.5

gemini-2.5-flash-image

Legacy Flash. High stability. Low cost.

Pro3

gemini-3-pro-image

High-fidelity Pro model.

flash

gemini-3.1-flash-image

Alias for backward compatibility.

pro

gemini-3-pro-image

Alias for backward compatibility.

Parameters

Full parameter reference for the generate_image tool.

Parameter

Type

Default

Description

prompt

string

required

Description of the image to generate

outputFileName

string

required

Output filename (extension auto-added if missing)

outputType

enum

combine

file, base64, or combine

model

enum

Flash3.1

Model: Flash3.1, Lite3.1, Flash2.5, Pro3, flash, pro

output_resolution

enum

auto

0.5K, 1K, 2K, 4K; required when noresize=true

noresize

boolean

false

Skip post-generation resize and return Gemini native dimensions

aspectRatio

enum

optional

Required when noresize=true; e.g. 1:1, 16:9, 4:5

outputWidth

integer

required unless noresize=true

Final output width in pixels

outputHeight

integer

required unless noresize=true

Final output height in pixels

output_format

enum

png

png, jpg, webp

outputPath

string

required for file / combine

Absolute output directory path

transparent

boolean

false

Transparent background (PNG/WebP only)

transparentColor

string or null

null

Color key override for transparency extraction

colorTolerance

integer

30

Transparency color matching tolerance

fringeMode

enum

auto

auto, crisp, hd

resizeMode

enum

crop

crop, stretch, letterbox, contain

grounding_type

enum

none

none, text, image, both (Flash3.1 only)

thinking_mode

enum

minimal

minimal, high (Flash3.1 only)

include_thoughts

boolean

false

Return model reasoning fields when metadata is enabled

include_metadata

boolean

false

Include grounding and reasoning metadata in JSON output

referenceImages

array

[]

Up to 14 local reference files (Flash3.1/Pro3/Lite3.1), 3 for Flash2.5

debug

boolean

false

Save intermediate debug artifacts

Why alphabanana?

  • Zero Watermarks: API-native clean images.

  • Thinking/Grounding Support: Higher prompt adherence and search-backed accuracy.

  • Production Ready: Supports transparent WebP and exact aspect ratios for web and game assets.

Features

  • Ultra-fast image generation (Gemini 3.1 Flash, 0.5K/1K/2K/4K)

  • Nano Banana 2 Lite (Lite3.1): ultra-fast, cost-effective 1K-only model for quick drafting and low-latency iteration

  • Advanced multi-image reasoning (up to 14 reference images)

  • Thinking/Grounding support (Flash3.1 only)

  • Transparent PNG/WebP output (color-key post-processing, despill)

  • Multiple output formats: file, base64, or both

  • Flexible resize modes: crop, stretch, letterbox, contain

  • Multiple model tiers: Flash3.1, Lite3.1, Flash2.5, Pro3, legacy aliases

Example Outputs

These sample outputs were generated with mcp-alphabanana and stored in images/examples.

Pixel art asset

Reference-image game scene

Photorealistic generation

Pixel art treasure chest

Reference-image dungeon loot scene

Photorealistic travel poster

Configuration

Configure the GEMINI_API_KEY in your MCP configuration (for example, mcp.json).

Examples:

  • Reference an OS environment variable from mcp.json:

{
  "env": {
    "GEMINI_API_KEY": "${env:GEMINI_API_KEY}"
  }
}
  • Provide the key directly in mcp.json:

{
  "env": {
    "GEMINI_API_KEY": "your_api_key_here"
  }
}

VS Code Integration

Add to your VS Code settings (.vscode/settings.json or user settings), configuring the server env in mcp.json or via the VS Code MCP settings.

{
  "mcp": {
    "servers": {
      "mcp-alphabanana": {
        "command": "npx",
        "args": ["-y", "@tasopen/mcp-alphabanana"],
        "env": {
          "GEMINI_API_KEY": "${env:GEMINI_API_KEY}"
        }
      }
    }
  }
}

Optional: Set a custom fallback directory for write failures by adding MCP_FALLBACK_OUTPUT to the env object.

Usage Examples

Basic Generation

{
  "prompt": "A pixel art treasure chest, golden trim, wooden texture",
  "model": "Flash3.1",
  "outputFileName": "chest",
  "outputType": "base64",
  "outputWidth": 64,
  "outputHeight": 64,
  "transparent": true
}

Native Size Without Resize

{
  "prompt": "A clean app icon with a banana mascot, flat graphic design",
  "model": "Flash3.1",
  "outputFileName": "banana-icon-native",
  "outputType": "base64",
  "noresize": true,
  "aspectRatio": "1:1",
  "output_resolution": "0.5K",
  "output_format": "png"
}

This mode returns the Gemini native pixel size for the requested ratio and resolution. For example, 1:1 + 0.5K returns 512x512 without any resize pass.

Advanced (Vertical poster and thinking)

{
  "prompt": "A vertical, photorealistic travel poster advertising Magical Wings Day Tours. A joyful young couple flies high above a breathtaking European countryside at golden hour, holding hands as they soar through a partly cloudy sky. Below them are vineyards, villages, forests, a winding river, and a hilltop medieval castle. The poster uses large, elegant typography with the headline FLY THE COUNTRYSIDE at the top and Magical Wings Day Tours branding near the bottom.",
  "model": "Flash3.1",
  "output_resolution": "1K",
  "outputFileName": "photoreal-travel-poster",
  "outputType": "file",
  "outputPath": "/path/to/output",
  "outputWidth": 848,
  "outputHeight": 1264,
  "output_format": "jpg",
  "thinking_mode": "high",
  "include_metadata": true
}

Grounding Sample (Search-backed)

{
  "prompt": "A modern travel poster featuring today's weather and skyline highlights in Kuala Lumpur",
  "model": "Flash3.1",
  "outputFileName": "kl_travel_poster",
  "outputType": "base64",
  "outputWidth": 1024,
  "outputHeight": 1024,
  "grounding_type": "text",
  "thinking_mode": "high",
  "include_metadata": true,
  "include_thoughts": true
}

This sample enables Google Search grounding and returns grounding and reasoning metadata in JSON.

With Reference Images

{
  "prompt": "Use the reference image to create a game screen showing an opened treasure chest filled with coins and treasure, 8-bit dungeon crawler style, after-battle reward scene, dungeon corridor background, four-party status UI at the bottom",
  "model": "Flash3.1",
  "output_resolution": "0.5K",
  "outputFileName": "reference-image-dungeon-loot",
  "outputType": "file",
  "outputPath": "/path/to/output",
  "outputWidth": 600,
  "outputHeight": 448,
  "output_format": "webp",
  "transparent": false,
  "referenceImages": [
    {
      "description": "Treasure chest style reference",
      "filePath": "/path/to/references/pixel-art-treasure-chest.png"
    }
  ]
}

Transparency & Output Formats

  • PNG: Full alpha, color-key + despill

  • WebP: Full alpha, better compression (Flash3.1+)

  • JPEG: No transparency (falls back to solid background)

Development

# Development mode with MCP CLI
npm run dev

# MCP Inspector (Web UI)
npm run inspect

# Build for production
npm run build

License

MIT

Available Tools

1 tool
generate_imageA
Destructive

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]

  • Flash3.1 (recommended): High quality, very fast, supports grounding and advanced features.

  • 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. Does not support 0.5K, 2K, or 4K resolutions.

[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.

ParametersJSON Schema
NameRequiredDescriptionDefault
debugNoDebug mode: output intermediate processing images and prompt
modelNoModel tier to use for generation (see tool description for details; "flash" and "pro" are aliases for Flash2.5 and Pro3; "Lite3.1" is the low-latency Nano Banana 2 Lite model, 1K-only, no grounding)Flash3.1
promptYesUser-provided image prompt. Preserve the original wording and detail; do not summarize or translate. Only append transparency-related hints if needed.
noresizeNoSkip post-generation resizing and return Gemini native dimensions directly. When true, provide aspectRatio and output_resolution instead of outputWidth/outputHeight.
fringeModeNoFringe reduction mode: auto (size-based), crisp (binary alpha), hd (force-clear 1px boundary for large images).auto
outputPathNoOutput directory path (MUST be an absolute path when outputType is file or combine). In Claude Desktop on Windows, use the FileSystem extension to choose or prepare a writable absolute path such as C:\temp.
outputTypeNoOutput format: file=file only, base64=base64 only, combine=both. In Claude Desktop, prefer file for medium or large images to avoid context-size limits; use base64 only for small previews.combine
resizeModeNoResize mode: crop=center crop, stretch=distort, letterbox=fit with padding, contain=trim transparent margins then fitcrop
aspectRatioNoGemini aspect ratio to use directly when noresize=true. Ignored in normal resize mode.
outputWidthNoOutput image width in pixels. Required unless noresize=true. In normal mode, the image will be generated using the closest supported Gemini aspect ratio and resolution, then resized to this width.
transparentNoRequest transparent background (PNG or WebP only). Background color is selected by histogram analysis.
outputHeightNoOutput image height in pixels. Required unless noresize=true. In normal mode, the image will be generated using the closest supported Gemini aspect ratio and resolution, then resized to this height.
output_formatNoOutput formatpng
thinking_modeNoThinking mode (3.1 only)minimal
colorToleranceNoTolerance for color matching (0-255). Higher values are more permissive for transparent color selection and keying.
grounding_typeNoGrounding tool usage (3.1 only)none
outputFileNameYesOutput filename (extension auto-added if missing)
referenceImagesNoReference images for style guidance (Flash2.5: max 3, others: max 14)
include_metadataNoInclude grounding and reasoning metadata in JSON output (optional, may increase payload size).
include_thoughtsNoOptional (default: false). Request thought fields from Gemini (3.1 only). Thought content is returned in MCP response only when include_metadata=true.
transparentColorNoColor to make transparent. Hex (e.g. #FF00FF). null defaults to #FF00FF when transparent=true.
output_resolutionNoGemini generation source resolution (optional in normal mode, required when noresize=true). In normal mode, the final image is resized to the requested pixel size after generation.

TDQS

A4.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description discloses key behaviors beyond annotations: it explains that the tool generates files on disk (outputPath), handles resizing and cropping, supports transparency, and has model-dependent features. Annotations already indicate destructiveHint=true and openWorldHint=true, so the description adds context about what gets created and modified. However, it does not explicitly warn about overwriting existing files, which would have earned a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long but well-structured with sections (Claude Desktop Guidance, Model Guidance, Aspect Ratios, IMPORTANT) and uses bullet points for readability. It front-loads the main purpose and then provides detailed guidance. While every sentence contributes value, some redundancy with schema descriptions could be trimmed slightly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (22 parameters, multiple modes, platform specifics), the description is quite comprehensive. It covers purpose, usage guidelines, model comparisons, resize behavior, output types, and important notes. However, it lacks explicit details about error responses or rate limits, and there is no output schema, but the description compensates well for the tool's generative nature.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so parameters are already documented. The description adds value by grouping parameters logically (e.g., model selection, aspect ratios, resize modes) and providing context for platform-specific usage (e.g., referenceImages filePath on Windows). It explains the interaction between parameters like outputWidth/outputHeight and noresize, which goes beyond individual parameter descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with 'Generate image assets using Gemini AI with optional transparency and reference images,' clearly stating the action, resource, and technology. It differentiates between different usage contexts (Claude Desktop, Windows, etc.) and provides model recommendations, ensuring the agent understands what the tool does and when to use which option.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description includes explicit guidance on when to use different output types ('Prefer outputType='file' for medium or large images'), when to use noresize mode vs normal mode, and when to choose each model (Flash3.1 recommended, Lite3.1 for quick drafting, etc.). It also provides platform-specific usage instructions for Claude Desktop and Windows, giving clear context for tool selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

TDQS

A4.6/5.0
Disambiguation5/5

With only one tool, there is no potential for confusion between tools. The single tool's purpose is clearly defined as generating images.

Naming Consistency5/5

There is only one tool, so naming consistency is not applicable. The tool name 'generate_image' follows a clear verb_noun convention.

Tool Count4/5

The server has a single tool, which is slightly thin but acceptable given the tool's complexity and the server's focused purpose of image generation. The tool includes many parameters and guidance, making it substantial.

Completeness5/5

The tool provides comprehensive image generation capabilities with support for multiple AI models, aspect ratios, output formats, and advanced options like no-resize and resize modes. It covers the full scope of image generation for the server's domain.

Maintenance

ActivitySlowing
ResponsivenessUnresponsive

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Related MCP Connectors

Related MCP Servers

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/tasopen/mcp-alphabanana'

If you have feedback or need assistance with the MCP directory API, please join our Discord server