Model Context Protocol server for Google Gemini AI with chat, research, and grounding
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"gemini": {
"env": {
"GEMINI_API_KEY": "your-api-key-here"
},
"args": [
"@houtini/gemini-mcp"
],
"command": "npx"
}
}
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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.
Run this in your terminal to verify the server starts. Then let us know if it worked — your result helps other developers.
npx -y '@houtini/gemini-mcp' 2>&1 | head -1 && echo "✓ Server started successfully"
After testing, let us know if it worked:
Five weighted categories — click any category to see the underlying evidence.
No known CVEs.
Checked @houtini/gemini-mcp against OSV.dev.
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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.
Quick Navigation
Get started | What it does | SVG generation | Image output | Configuration | Tools | Models | Requirements
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 |
|---|---|---|
![]() | ![]() | ![]() |
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:
C:\Users\{username}\AppData\Roaming\Claude\claude_desktop_config.json~/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.
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 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.
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: `hig