Claude Image Gen

Gemini Image Generation - Claude Skill + MCP

AI-powered image generation using Google Gemini, integrated with Claude Code.

Features

• Generate images from text prompts using Gemini AI
• Proactive Claude skill suggests images for websites, presentations, and more
• Two execution modes: CLI script (skill-only) or MCP server (protocol-based)
• Configurable aspect ratios (1:1, 16:9, 9:16, etc.)
• Multiple model support (quality vs speed)
• Images saved to disk with file paths returned

Prerequisites

• Google Gemini API key (Get one here)
• Node.js 18+ (only for manual installation)

Installation

Quick Install (Claude Code Plugin)

The plugin installs skill + CLI + MCP server in one step—no separate configuration needed.

# Add the marketplace
/plugin marketplace add guinacio/claude-image-gen

# Install the plugin
/plugin install media-pipeline@media-pipeline-marketplace

Or install directly from GitHub:

/plugin install guinacio/claude-image-gen

Once installed:

• Skill uses the bundled CLI script (no MCP overhead)
• MCP server is also available for direct tool calls

> Tip: Since the skill runs the CLI directly, you can disable the MCP server in Claude Code's MCP list to reduce startup overhead. The skill will continue to work without it.

---

Quick Install (Claude Desktop Extension)

For Claude Desktop users, install the pre-built extension:

1. Download media-pipeline.mcpb from Releases
2. Open Claude Desktop
3. Go to Settings → Extensions → Advanced settings
4. Click Install Extension and select the .mcpb file
5. Enter your Gemini API key when prompted

---

Manual Installation

For developers who want to customize or build from source:

1. Build the MCP Server

cd mcp-server
npm install
npm run bundle

2. Use the Standalone CLI

cd mcp-server
GEMINI_API_KEY=your-api-key-here node build/cli.bundle.js \
  --prompt "Landing page hero image for a fintech startup" \
  --aspect-ratio "16:9"

The CLI runs directly against Gemini and returns structured JSON on stdout. It does not require the MCP server layer.

3. Add to Claude Code

Option A: Using MCP server

claude mcp add --transport stdio media-pipeline \
  --env GEMINI_API_KEY=your-api-key-here \
  -- node /path/to/claude-image-gen/mcp-server/build/bundle.js

The -- separates Claude CLI flags from the server command.

Option B: Manual config

Add to your Claude Code config (~/.claude.json):

{
  "mcpServers": {
    "media-pipeline": {
      "command": "node",
      "args": ["/path/to/claude-image-gen/mcp-server/build/bundle.js"],
      "env": {
        "GEMINI_API_KEY": "${GEMINI_API_KEY}",
        "GEMINI_DEFAULT_MODEL": "${GEMINI_DEFAULT_MODEL:-gemini-3-pro-image-preview}",
        "IMAGE_OUTPUT_DIR": "${IMAGE_OUTPUT_DIR:-./generated-images}",
        "GEMINI_REQUEST_TIMEOUT_MS": "${GEMINI_REQUEST_TIMEOUT_MS:-60000}",
        "MEDIA_PIPELINE_LOG_LEVEL": "${MEDIA_PIPELINE_LOG_LEVEL:-info}"
      }
    }
  }
}

The ${VAR:-default} syntax uses environment variables with fallback defaults.

4. Install Skill Manually (Optional)

If not using the plugin:

cp -r skills/image-generation ~/.claude/skills/

4. Build Extension from Source (Optional)

To create your own .mcpb extension for Claude Desktop:

cd mcp-server
npm install -g @anthropic-ai/mcpb
npm run pack:mcpb

This creates mcp-server/media-pipeline.mcpb using bundled runtime entry points for both the MCP server and the standalone CLI.

Usage

Direct Tool Usage

Use create_asset to create a hero image for a tech startup website

With the Skill

The skill will proactively suggest image generation when:

• Building websites with hero sections
• Creating presentations
• Working with placeholder images
• Developing marketing materials

Configuration

Environment Variables

| Variable | Required | Default | Description | |----------|----------|---------|-------------| | GEMINI_API_KEY | Yes | - | Your Gemini API key | | GEMINI_DEFAULT_MODEL | No | gemini-3-pro-image-preview | Default model to use | | IMAGE_OUTPUT_DIR | No | ./generated-images | Where to save images | | GEMINI_REQUEST_TIMEOUT_MS | No | 60000 | Timeout for Gemini requests | | MEDIA_PIPELINE_LOG_LEVEL | No | info | Stderr logging level |

Models

Available image models are fetched dynamically from the Gemini API at runtime. The CLI and MCP tool validate model choices against the current image-capable model list, and GEMINI_DEFAULT_MODEL is used when available.

Aspect Ratios

| Ratio | Best For | |-------|----------| | 1:1 | Social media, thumbnails | | 16:9 | Hero images, presentations | | 9:16 | Mobile stories, vertical banners | | 4:3 | Blog posts, general web | | 3:2 | Photography-style images |

Prompt Tips

Use this formula for effective prompts:

[Style] [Subject] [Composition] [Context/Atmosphere]

Example:

Minimalist 3D illustration of abstract geometric shapes floating in space,
soft gradient background from deep purple to electric blue, subtle glow effects,
modern professional aesthetic, wide composition for website header

See [skills/image-generation/references/prompt-crafting.md](skills/image-generation/references/prompt-crafting.md) for advanced techniques.

Architecture

Two Execution Modes

CLI Mode (Default) - Used by the skill:

Claude → Skill → Bash → bundled CLI → Gemini API

• No MCP protocol overhead
• Skill runs bundled CLI directly
• All dependencies bundled in a single file

MCP Mode (Optional) - For direct tool calls:

Claude → MCP Tool → bundled MCP server → Gemini API

• Standard MCP protocol
• Useful for non-skill workflows
• Extension package only needs bundled entry points

Abstract MCP Naming

The MCP server uses intentionally abstract naming (media-pipeline / create_asset) rather than image-specific names (gemini-image-gen / generate_image).

Why? When tool names directly match intent (e.g., "I need to generate an image" → generate_image), AI assistants tend to call the MCP tool directly, bypassing the skill layer. By using generic names:

• The skill (image-generation) becomes the semantically obvious choice for image tasks
• The MCP tool doesn't immediately register as the solution
• The skill's prompt optimization and aspect ratio selection are properly utilized

This is a form of prompt engineering for tool selection—making the abstraction layer the natural choice while the underlying implementation has a name that doesn't invite direct use.

Project Structure

claude-image-gen/
├── .claude-plugin/       # Plugin configuration
│   ├── plugin.json       # Plugin manifest
│   └── marketplace.json  # Marketplace distribution
├── mcp-server/           # Server and CLI implementation
│   ├── src/
│   │   ├── index.ts      # MCP server entry point
│   │   ├── cli.ts        # CLI entry point (skill uses this)
│   │   ├── gemini-client.ts
│   │   ├── image-storage.ts
│   │   └── types.ts
│   ├── build/
│   │   ├── bundle.js     # Bundled MCP server
│   │   └── cli.bundle.js # Bundled CLI (all deps included)
│   ├── .mcpbignore       # Package only the runtime files needed by the bundle
│   ├── manifest.json     # MCPB extension manifest
│   ├── icon.png          # Extension icon
│   ├── package.json
│   └── tsconfig.json
├── skills/               # Claude skills
│   └── image-generation/
│       ├── SKILL.md      # Skill instructions (uses CLI)
│       └── references/
├── .mcp.json            # MCP configuration
└── README.md

License

MIT

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: guinacio
• Source: guinacio/claude-image-gen
• License: MIT

Install and usage instructions live in the source repository linked above.