gemini-image-mcp

A simple, focused MCP server for Google Gemini's native image generation — the "Nano Banana" models. Generate, edit, and locally process images from Claude Code, Claude Desktop, or any stdio-based MCP client. Two tools, no bloat.

Built for agents: a single call returns a saved image — or, with one-call background removal, a ready-to-use transparent PNG — without streaming image data through your agent's context. Uses Gemini's generateContent API (not the deprecated Imagen API).

Install

npm install -g @jimothy-snicket/gemini-image-mcp

Or use directly with npx:

npx -y @jimothy-snicket/gemini-image-mcp

Claude Code (one command):

claude mcp add gemini-image -- npx -y @jimothy-snicket/gemini-image-mcp

Requires a GEMINI_API_KEY environment variable — see Setup for details.

Set up a config file (optional):

npx @jimothy-snicket/gemini-image-mcp --init

Creates ~/.gemini-image-mcp.json with commented defaults. For project-specific overrides:

npx @jimothy-snicket/gemini-image-mcp --init --local

Features

generate_image — AI-powered

• Text-to-image — describe what you want, get an image
• Image editing — provide reference images and an editing instruction
• Video-to-image — the model watches a video and synthesizes a new image from what it understood: YouTube thumbnails, posters from footage, summary infographics, style-transferred stills. See Advanced Features
• Thinking depth control — thinkingLevel: "HIGH" for renders that depend on reasoning (infographics, diagrams, dense typography); cheap MINIMAL default otherwise
• Transparent assets in one call — removeBackground returns a clean transparent PNG: a local AI matte (works on any subject; optional add-on, see below) by default, or built-in green-screen / white-threshold keying. No extra API cost
• Multi-turn edits — pass a sessionId to refine an image across calls, with prior turns kept as context
• Multi-image input — reference images for editing and character/style consistency (per-model limits; the API enforces)
• Cost reporting — every response includes token counts, estimated USD cost, and session totals
• Rate limiting — configurable per-hour caps on requests and cost to prevent runaway agents
• Auto model discovery — detects available image models from your API key at startup
• Seed — reproducible generation with integer seeds
• Search grounding — ground renders in live Google Search results; "web+image" also pulls image-search results for mood boards and trend references, with sources returned for attribution. See Advanced Features

process_image — Local (free, no API calls)

• Crop — pixel-exact, aspect ratio (center), or focal point (attention/entropy)
• Resize — to width, height, or both (maintains aspect ratio)
• Background removal — threshold-based (white backgrounds) or chroma key (green screen, any solid colour)
• Chroma key pipeline — HSV keying with smoothstep feather, spill suppression, and edge anti-aliasing
• Trim — auto-remove whitespace borders
• Format conversion — PNG, JPEG, WebP with quality control

Both tools

• Output organization — meaningful filenames with auto-versioning, subfolders
• Generation manifest — generations.jsonl logs every generation with prompt, params, cost
• Full aspect ratio support — 1:1, 16:9, 9:16, 3:2, 2:3, 4:3, 3:4, 21:9
• Resolution control — 1K, 2K, 4K

Setup

1. Get a Gemini API Key

Go to Google AI Studio and create an API key.

Billing required: image generation has no free tier — free-tier keys get 429 RESOURCE_EXHAUSTED (quota limit 0) on every image model. Enable pay-as-you-go billing on the key's Google Cloud project (usage & billing). Images cost ~$0.03–$0.24 each

... View full README on GitHub