mcp-imagenate

mcp-imagenate

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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 | | ----------------- | -------------------------------- | ---------------------------- | | nano-banana-2 | gemini-3.1-flash-image-preview | Fast, high-volume generation | | nano-banana-pro | gemini-3-pro-image-preview | Highest quality output |

OpenAI

| Name | Model ID | Best for | | ------------- | ------------- | ---------------------------------- | | gpt-image-2 | gpt-image-2 | Latest generation, improved detail |

BFL FLUX

| Name | Model ID | Best for | | --------------- | ------------- | -------------------------------- | | flux-2-klein | klein-4b | Fast, lightweight generation | | flux-2-pro | pro-preview | Balanced quality and speed | | flux-2-max | max | Maximum quality |

Reve

| Name | Version | Best for | | ------------ | -------- | ------------------------------ | | reve-image | latest | 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:

• resolution is ignored — Reve has no size parameter and returns its own large

output. Exact dimensions vary between requests: 16:9 came back as both 5408x3072 and 5376x3072, and 3:4 as 3456x4800.

• Prompts are capped at 4,000 characters, and this provider rejects longer ones

before spending a request.

• inputImages become v2 references. 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.

Requirements

• Node.js 20+
• At least one provider API key

Installation

npx mcp-imagenate

Or install globally:

npm install -g mcp-imagenate

Setup

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_here

Claude 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 | | ------------------------- | -------- | ------------------------------------------------------------------------------------------------------------- | | GEMINI_API_KEY | \ | Google AI Studio API key | | NANO_BANANA_API_KEY | \ | Alternative to GEMINI_API_KEY (takes precedence) | | OPENAI_API_KEY | \ | OpenAI API key | | GPT_IMAGE_API_KEY | \ | Alternative to OPENAI_API_KEY (takes precedence) | | BFL_API_KEY | \ | BFL FLUX API key | | REVE_API_KEY | \ | Reve partner API token (from the API console at api.reve.com) | | REVE_API_TOKEN | \* | Alternative to REVE_API_KEY (REVE_API_KEY takes precedence) | | NANO_BANANA_OUTPUT_DIR | 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 | | -------------- | ------------------------------------------------------ | ----------------- | ----------------------------------------------------------------------------- | | prompt | string (1-32,000 chars) | - | Text prompt describing the image | | model | see Models above | "gpt-image-2" | Model to use (available models depend on configured API keys) | | resolution | "1K" \| "2K" \| "4K" | "1K" | Output image resolution | | aspectRatio | see below | "1:1" | Aspect ratio of the image | | mode | "image" \| "image_and_text" | "image" | Return image only, or image with description (Google models only) | | thinking | "none" \| "auto" | "auto" | Controls model thinking (Google models only) | | outputDir | string | "." | Directory where images will be saved | | inputImages | string[] | - | File paths of images to send alongside the prompt (Google models, OpenAI gpt-image models via the images.edit endpoint, and Reve via v2 references) |

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": "..."
}

description is only present when mode is "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 | | --- | --- | | createRegistry(keys) | Build a registry of the models available for the given keys | | keysFromEnv(env?) | Read provider keys from environment variables | | generateImageToDisk(options) | Generate images and write them to disk | | resolveOutputDir / resolveInputImagePath | Path sandboxing helpers (opt-in) |

Security

• Path sandboxing: When NANO_BANANA_OUTPUT_DIR is 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 via outputBaseDir, 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