mcp-imagenate
Generate images from text prompts using multiple AI providers (Google Gemini: nano-banana-2 and nano-banana-pro; OpenAI: gpt-image-2; BFL FLUX: flux-2-klein, flux-2-pro, flux-2-max; Reve: reve-image). Control output resolution (1K, 2K, 4K) and aspect ratio (1:1, 2:3, 3:2, 3:4, 4:3, 9:16, 16:9, 21:9). Optionally include reference images for editing (Google, OpenAI, Reve). For Google models, choose to return images only or with descriptions, and enable model thinking (auto/none). Save generated images to a specified directory with path sandboxing via NANO_BANANA_OUTPUT_DIR. Validate input images (format/size). Prompts support up to 32,000 characters. Returns saved file paths and the model used.
Enables image generation using Google Gemini models (nano-banana-2 and nano-banana-pro) for fast or high-quality outputs.
Enables image generation using OpenAI's gpt-image-2 model.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@mcp-imagenateGenerate a photo of a cat wearing a wizard hat"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
mcp-imagenate
An MCP server for image generation using multiple providers: Google Gemini, OpenAI (gpt-image), BFL FLUX, and Reve.
Providers & Models
Google Gemini (Nano Banana)
Name | Model ID | Best for |
|
| Fast, high-volume generation |
|
| Highest quality output |
OpenAI
Name | Model ID | Best for |
|
| Latest generation, improved detail |
BFL FLUX
Name | Model ID | Best for |
|
| Fast, lightweight generation |
|
| Balanced quality and speed |
|
| Maximum quality |
Reve
Name | Version | Best for |
|
| Typography and layout fidelity |
This provider calls Reve's v2/image/create endpoint. latest is the only version
alias v2 exposes, and it is what the response reports back, so there is no dated
build to pin to. Do not confuse it with the v1 endpoints, which still serve the
older reve-create@20250915 model.
Things worth knowing before sending Reve a prompt written for another provider:
resolutionis ignored — Reve has no size parameter and returns its own large output. Exact dimensions vary between requests:16:9came back as both 5408x3072 and 5376x3072, and3:4as 3456x4800.Prompts are capped at 4,000 characters, and this provider rejects longer ones before spending a request.
inputImagesbecome v2references. Reve accepts at most eight; a longer list is rejected before any of the files are read.The saved file's extension follows the format Reve actually returned (PNG, JPEG or WebP), which is detected from the bytes rather than assumed.
A generation costs 150 credits (about $0.20) and typically takes 40-80 seconds. Give any proxy or job runner in front of it a timeout of at least 120 seconds.
Related MCP server: Imagen Tools MCP Server
Requirements
Node.js 20+
At least one provider API key
Installation
npx mcp-imagenateOr install globally:
npm install -g mcp-imagenateSetup
Set API keys for the providers you want to use:
# Google Gemini (at least one)
export GEMINI_API_KEY=your_key_here
# or
export NANO_BANANA_API_KEY=your_key_here
# OpenAI (at least one)
export OPENAI_API_KEY=your_key_here
# or
export GPT_IMAGE_API_KEY=your_key_here
# BFL FLUX
export BFL_API_KEY=your_key_here
# Reve (at least one)
export REVE_API_KEY=your_key_here
# or
export REVE_API_TOKEN=your_key_hereClaude Desktop
Add to your claude_desktop_config.json:
{
"mcpServers": {
"mcp-imagenate": {
"command": "npx",
"args": ["mcp-imagenate"],
"env": {
"GEMINI_API_KEY": "your_key_here",
"NANO_BANANA_OUTPUT_DIR": "/path/to/image/output"
}
}
}
}Environment Variables
Variable | Required | Description |
| * | Google AI Studio API key |
| * | Alternative to |
| * | OpenAI API key |
| * | Alternative to |
| * | BFL FLUX API key |
| * | Reve partner API token (from the API console at api.reve.com) |
| * | Alternative to |
| No | Base directory for saved images. When set, all output and input paths are sandboxed within this directory. Recommended for production. |
* At least one provider API key must be set.
Tool: generate_image
Parameters
Parameter | Type | Default | Description |
|
| - | Text prompt describing the image |
| see Models above |
| Model to use (available models depend on configured API keys) |
|
|
| Output image resolution |
| see below |
| Aspect ratio of the image |
|
|
| Return image only, or image with description (Google models only) |
|
|
| Controls model thinking (Google models only) |
|
|
| Directory where images will be saved |
|
| - | File paths of images to send alongside the prompt (Google models, OpenAI gpt-image models via the images.edit endpoint, and Reve via v2 |
Supported aspect ratios
1:1, 2:3, 3:2, 3:4, 4:3, 9:16, 16:9, 21:9
Response
Returns a JSON object:
{
"model": "gemini-3.1-flash-image-preview",
"savedFiles": ["/path/to/image-1.png"],
"settings": {
"resolution": "1K",
"aspectRatio": "9:16",
"mode": "image"
},
"description": "..."
}
descriptionis only present whenmodeis"image_and_text".
Use as a library
Besides the standalone MCP server, this package can be embedded in another host — an app, or another MCP server that wants to expose image generation as its own tool.
import { createRegistry, generateImageToDisk } from "mcp-imagenate";
// Keys are passed in explicitly; nothing here reads process.env.
const registry = createRegistry({ openai: myOpenAIKey, google: myGoogleKey });
if (registry.models.length === 0) {
throw new Error("No image provider is configured");
}
const outcome = await generateImageToDisk({
registry,
prompt: "a calico cat asleep on a warm keyboard",
model: registry.defaultModel!,
aspectRatio: "16:9",
outputDir: "/somewhere/to/write",
// outputBaseDir defaults to null, meaning no path sandboxing. Set it to a
// directory to confine both output and input paths within that directory.
});
console.log(outcome.savedFiles);The library entry point never reads process.env, writes to stdio, or exits the
process. To read keys from the conventional environment variables anyway, use the
keysFromEnv() helper. The standalone server is available at mcp-imagenate/server.
Export | Purpose |
| Build a registry of the models available for the given keys |
| Read provider keys from environment variables |
| Generate images and write them to disk |
| Path sandboxing helpers (opt-in) |
Security
Path sandboxing: When
NANO_BANANA_OUTPUT_DIRis set, both output and input image paths are sandboxed within this directory. Symlinks that resolve outside the sandbox are rejected. For library embedders this is opt-in viaoutputBaseDir, since the host usually controls which paths reach the call.Input validation: Input images are validated for format (PNG/JPEG/WEBP/GIF) and size (max 20 MB).
API key validation: The server exits immediately if no API keys are configured. The library reports this as an empty registry instead, leaving the decision to the host.
License
MIT
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Tools
Related MCP Servers
- AlicenseAqualityDmaintenanceMCP server for Google Gemini image generation with configurable model support, enabling text-to-image generation, image editing, and iterative refinement.639MIT
- Alicense-qualityBmaintenanceAn MCP server for generating and editing images using Google Gemini Imagen via Vertex AI. Supports multiple resolutions and aspect ratios.MIT
- FlicenseAqualityDmaintenanceMCP server for AI image generation supporting text-to-image and image-to-image editing via any OpenAI-compatible service, with configurable models, aspect ratios, and sizes.2
- Alicense-qualityDmaintenanceAn MCP server that provides AI image generation using Google Gemini models with intelligent model selection, aspect ratio control, and support for high-quality outputs up to 4K.MIT
Related MCP Connectors
MCP server for Flux AI image generation
MCP server for Midjourney AI image generation and editing
MCP server for Google Veo AI video generation
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
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/mimo-3/mcp-imagenate'
If you have feedback or need assistance with the MCP directory API, please join our Discord server