Google Gemini MCP Server

@houtini/gemini-mcp

I've been running this MCP server in my Claude Desktop setup for several months, and it's one of the few I leave enabled permanently. Not because Gemini replaces Claude -- it doesn't -- but because grounded search, deep research, image generation, and video are things Gemini does well. Having them as tools inside Claude beats switching between browser tabs.

Thirteen tools. One npx command.

MCP App previews

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

Image generation	SVG / diagram generation

Quick Navigation

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

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. The tools show up automatically. npx pulls the package on first run -- no separate install.

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.

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 data cutoff answers. Sources come back as markdown links.

For questions where you want reasoning over live search -- "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 where you need 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 with longer timeout tolerance, 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 mod