Image Generation MCP Server

Name: Image Generation MCP Server
Author: dfeirstein

@dfeirstein

Image Generation MCP Server について

Model Context Protocol (MCP) server enabling AI clients (Cline, Claude Desktop) to generate images using OpenAI (DALL-E 3, gpt-image-1) and save them directly to the user's project directory.

基本情報

カテゴリ

メディアとデザイン

ランタイム

node

トランスポート

stdio

公開者

dfeirstein

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "image-creator-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "@dfeirstein/image-server@latest"
      ]
    }
  }
}

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Image Generation MCP Server?

An MCP server that allows compatible clients (like Cline, Claude Desktop) to generate images using OpenAI's API (gpt-image-1, dall-e-3, dall-e-2). It provides a create_image tool that takes a text prompt and other parameters, generates the image, and saves it to a specified project’s public directory.

How to use Image Generation MCP Server?

Install via NPX (npx -y @dfeirstein/image-server@latest) or clone the repository and run node dist/index.js. Configure your MCP client’s settings file (e.g., claude_desktop_config.json) with the server command and your OpenAI API key. The server exposes the create_image tool and serves documentation as MCP resources at docs/prompt-recipes and docs/readme.

Key features of Image Generation MCP Server

Generates images from text prompts using OpenAI models.
Edits and combines existing images via reference images.
Supports optional branding guidelines via brandSignature.
Allows specifying image size, quality, and background type.
Supports consistent visual styling through styleDefinitionJSON.
Saves images to a target project’s public directory.

Use cases of Image Generation MCP Server

Create logos, icons, or marketing assets with transparent backgrounds.
Generate themed image collections with a unified style definition.
Edit existing project images by applying effects or combining visuals.
Automate image creation inside an LLM-assisted development workflow.

FAQ from Image Generation MCP Server

What OpenAI models are supported?

The server supports gpt-image-1, dall-e-3, and dall-e-2. Image editing operations automatically use gpt-image-1.

What are the runtime requirements?

Node.js 18 or higher and npm are required. An OpenAI API key is mandatory; gpt-image-1 usage may need API Organization Verification.

How does the server save images?

Generated images are saved to the public folder of a target project directory specified by the LLM client. The server returns a relative path to the saved file.

Can I auto‑approve tools without confirmation?

Yes. In the client’s MCP settings, the autoApprove array can list tool names (e.g., ["create_image"]) to skip manual approval.

What transport and authentication does the server use?

The server uses stdio transport by default when launched by an MCP client. Authentication is via the OPENAI_API_KEY environment variable. A standalone HTTP server on port 5050 is available for testing.