@houtini/gemini-mcp

@houtini/gemini-mcp

I've been running this MCP server in my Claude Desktop setup for months. It's one of the few I leave on permanently — not because Gemini replaces Claude, but because grounded search, image generation, SVG diagrams, and video are things Gemini does genuinely well. Having them as tools inside Claude beats switching browser tabs.

Thirteen tools. One npx command.

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Quick Navigation

Get started | What it does | SVG generation | Image output | Configuration | Tools | Models | Requirements

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What it looks like

Generated images, SVGs, and videos render inline in Claude Desktop with zoom controls, file paths, and prompt context:

Image generation	SVG / diagram generation

Image embed	SVG embed	Video embed

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Get started in two minutes

Step 1: Get a Gemini API key

Go to Google AI Studio and create one. The free tier covers most development use — you'll hit rate limits on deep research if you're hammering it, but for day-to-day work it's fine.

Step 2: Add to your Claude Desktop config

Config file locations:

• Windows: C:\Users\{username}\AppData\Roaming\Claude\claude_desktop_config.json
• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "gemini": {
      "command": "npx",
      "args": ["@houtini/gemini-mcp"],
      "env": {
        "GEMINI_API_KEY": "your-api-key-here"
      }
    }
  }
}

Step 3: Restart Claude Desktop

That's it. Tools show up automatically. npx pulls the package on first run — no separate install needed.

Local build instead

For development, or if you'd rather not rely on npx:

git clone https://github.com/houtini-ai/gemini-mcp
cd gemini-mcp
npm install --include=dev
npm run build

Then point your config at the local build:

{
  "mcpServers": {
    "gemini": {
      "command": "node",
      "args": ["C:/path/to/gemini-mcp/dist/index.js"],
      "env": {
        "GEMINI_API_KEY": "your-api-key-here"
      }
    }
  }
}

Claude Code (CLI)

Claude Code uses a different registration mechanism — it doesn't read claude_desktop_config.json. Use claude mcp add instead:

claude mcp add -e GEMINI_API_KEY=your-api-key-here -s user gemini -- npx -y @houtini/gemini-mcp

With optional image output directory:

claude mcp add \
  -e GEMINI_API_KEY=your-api-key-here \
  -e GEMINI_IMAGE_OUTPUT_DIR=/path/to/output \
  -s user \
  gemini -- npx -y @houtini/gemini-mcp

Verify with claude mcp get gemini — you should see Status: Connected.

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What it does

Chat with Google Search grounding

Use gemini:gemini_chat to ask: "What changed in the MCP spec in the last month?"

Grounding is on by default. Gemini searches Google before answering, so you get current information rather than training cutoff answers. Sources come back as markdown links. For questions where you want pure reasoning — "explain this code" or similar — set grounding: false.

Supports thinking_level on Gemini 3 models: high for maximum reasoning depth, low to keep it fast, medium/minimal on Gemini 3 Flash only.

Deep research

Use gemini:gemini_deep_research with:
  research_question="What are the current approaches to AI agent memory management?"
  max_iterations=5

Runs multiple grounded search iterations then synthesises a full report. Takes 2-5 minutes depending on complexity — worth it for anything needing comprehensive coverage rather than a quick answer.

Set max_iterations to 3-4 in Claude Desktop (4-minute tool timeout). In IDEs (Cursor, Windsurf, VS Code) or agent frameworks, 7-10 iterations produces noticeably better synthesis. Pass focus_areas as an array to steer toward specific angles.

Image generation with search grounding

Use gemini:generate_image with:
  prompt="Stock price chart showing Apple (AAPL) closing prices for the last 5 trading days"
  use_search=true
  aspectRatio="16:9"

Default model is gemini-3-pro-image-preview (Nano Banana Pro). Also supports gemini-2.5-flash-image for faster generation.

When use_search=true, Gemini searches Google for current data before generating. Financial and news queries work reliably. The full-resolution image saves to disk automatically — the inline preview is resized for transport but the original is untouched.

Video generation with Veo 3.1

Use gemini:generate_video with:
  prompt="A close-up shot of a futuristic coffee machine brewing a glowing blue espresso, steam rising dramatically. Cinematic lighting."
  resolution="1080p"
  durationSeconds=8

Uses Google's Veo 3.1 model. Generates 4-8 second videos at up to 4K with native synchronised audio. Processing takes 2-5 minutes — the tool polls automatically until ready.

Options worth knowing:

• aspectRatio — 16:9 landscape or 9:16 portrait/vertical
• generateAudio — on by default, produces dialogue and sound effects matching the prompt
• sampleCount — generate up to 4 variations in one call
• seed — deterministic output across runs
• generateThumbnail — extracts a frame via ffmpeg (needs ffmpeg in PATH)
• firstFrameImage — animate from a starting image (image-to-video)

SVG generation

This is the one people underestimate. SVG output isn't just diagrams — it's production-ready vector graphics you can drop straight into a codebase, a presentation, or a web page. Clean, scalable, no raster artefacts.

Use gemini:generate_svg with:
  prompt="Architecture diagram showing a microservices system with API gateway, three services, and a shared database"
  style="technical"
  width=1000
  height=600

Four styles:

Style	Best for
technical	Architecture diagrams, flowcharts, system maps
artistic	Illustrations, decorative graphics, icons
minimal	Clean data visualisations, simple charts
data-viz	Complex charts, dashboards, infographics

The output is actual SVG code — edit it, animate it, embed it in HTML, commit it to a repo. No rasterising, no export steps, no Figma required.

Image editing and analysis

Conversational editing — Gemini 3 Pro Image maintains context across editing turns. Pass thought signatures back on subsequent edit_image calls for full continuity:

Use gemini:edit_image with:
  prompt="Change the colour scheme to blue and green"
  images=[{data: imageBase64, mimeType: "image/png", thoughtSignature: "fromPreviousCall"}]

Analysis — two tools for different purposes:

• describe_image — Fast general descriptions using Gemini 3 Flash
• analyze_image — Structured extraction and detailed reasoning using Gemini 3.1 Pro

Load local files:

Use gemini:load_image_from_path with filePath="C:/screenshots/error.png"

Media resolution control

Reduce token usage by up to 75% whilst maintaining quality for the task:

Level	Tokens	Savings	Best for
MEDIA_RESOLUTION_LOW	280	75%	Simple tasks, bulk operations
MEDIA_RESOLUTION_MEDIUM	560	50%	PDFs/documents (OCR saturates here)
MEDIA_RESOLUTION_HIGH	1120	default	Detailed analysis
MEDIA_RESOLUTION_ULTRA_HIGH	2000+	per-image only	Maximum detail

For PDF OCR, MEDIUM gives identical text extraction quality to HIGH at half the tokens.

Landing page generation

Use gemini:generate_landing_page with:
  brief="A SaaS tool that helps developers monitor API latency"
  companyName="PingWatch"
  primaryColour="#6366F1"
  style="startup"
  sections=["hero", "features", "pricing", "cta"]

Returns a self-contained HTML file — inline CSS and vanilla JS, no external dependencies. Styles: minimal, bold, corporate, startup.

Professional chart design systems

gemini_prompt_assistant includes 9 professional chart design systems:

System	Inspiration	Best for
storytelling	Cole Nussbaumer Knaflic	Executive presentations
financial	Financial Times	Editorial journalism — FT Pink, serif titles
terminal	Bloomberg / Fintech	High-density dark mode with neon
modernist	W.E.B. Du Bois	Bold geometric blocks, stark contrasts
professional	IBM Carbon / Tailwind	Enterprise dashboards
editorial	FiveThirtyEight / Economist	Data journalism
scientific	Nature / Science	Academic rigour
minimal	Edward Tufte	Maximum data-ink ratio
dark	Observable	Modern dark mode

Help system

Use gemini:gemini_help with topic="overview"

Full documentation without leaving Claude. Topics: overview, image_generation, image_editing, image_analysis, chat, deep_research, grounding, media_resolution, models, all.

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Image output and storage

By default, images return as inline previews rendered directly in Claude. Set GEMINI_IMAGE_OUTPUT_DIR to auto-save everything:

"env": {
  "GEMINI_API_KEY": "your-api-key-here",
  "GEMINI_IMAGE_OUTPUT_DIR": "C:/Users/username/Pictures/gemini-output"
}

The server uses a two-tier approach to handle the MCP protocol's 1MB JSON-RPC limit whilst preserving full-resolution files:

Tier	Purpose
Full-res	Saved to disk immediately, untouched
Preview	Resized JPEG for inline transport — dynamically sized to fit under the cap

Gemini returns 2-5MB images. The resize is smart — it measures the non-image overhead in each response and calculates the exact binary budget available, stepping down dimensions (800→600→400→300→200px) until it fits. The full image is always there on disk.

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Configuration reference

Variable	Required	Default	Description
GEMINI_API_KEY	Yes	—	Google AI API key from AI Studio
GEMINI_DEFAULT_MODEL	No	gemini-3.1-pro-preview	Default model for gemini_chat and analyze_image
GEMINI_DEFAULT_GROUNDING	No	true	Enable Google Search grounding by default
GEMINI_IMAGE_OUTPUT_DIR	No	—	Auto-save directory for generated images and videos
GEMINI_ALLOW_EXPERIMENTAL	No	false	Include experimental/preview models in auto-discovery
GEMINI_MCP_LOG_FILE	No	false	Write logs to ~/.gemini-mcp/logs/
DEBUG_MCP	No	false	Log to stderr for debugging tool calls

Tools reference

Tool	Description
gemini_chat	Chat with Gemini 3.1 Pro. Google Search grounding on by default. Supports thinking_level
gemini_deep_research	Multi-step iterative research with Google Search. Synthesises comprehensive reports
gemini_list_models	Lists available models from the Gemini API
gemini_help	Documentation for all features without leaving Claude
gemini_prompt_assistant	Expert guidance for image generation with 9 chart design systems
generate_image	Image generation with optional search grounding. Full-res saved to disk
edit_image	Edit images with natural-language instructions. Multi-turn continuity via thought signatures
describe_image	Fast image descriptions using Gemini 3 Flash
analyze_image	Structured extraction and analysis using Gemini 3.1 Pro
load_image_from_path	Read a local image file and return base64 for any image tool
generate_video	Video generation with Veo 3.1 — 4-8 seconds at up to 4K with native audio
generate_svg	Production-ready SVG: diagrams, illustrations, icons, data visualisations
generate_landing_page	Self-contained HTML landing pages with inline CSS/JS

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Model reference

Model	Used by	Notes
gemini-3.1-pro-preview	gemini_chat, analyze_image	Default. Advanced reasoning
gemini-3-pro-image-preview	generate_image, edit_image	Nano Banana Pro — highest quality image generation
gemini-2.5-flash-image	generate_image (optional)	Faster generation, higher volume
gemini-3-flash-preview	describe_image	Fast general descriptions
veo-3.1-generate-preview	generate_video	Veo 3.1 — 4K video with native audio

Gemini 3 notes: Temperature is forced to 1.0 on Gemini 3 models (Google's requirement — lower values cause looping). Thinking level only applies to gemini_chat.

Token budgets: max_tokens defaults to each model's full output ceiling as reported live by the models API (65,536 on current Gemini 3 text models — the 1M figure is input context). It's a cap, not consumption: unused headroom costs nothing. Values below 4,096 are ignored (Gemini 3 thinking burns tiny budgets before any visible output, which looks like a timeout) and values above the model's real limit are clamped.

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Requirements

• Node.js 18+
• A Gemini API key from Google AI Studio
• ffmpeg (optional, for video thumbnail extraction)

Licence

Apache-2.0