Provides Google Search functionality using Gemini's built-in Grounding with Google Search feature, delivering real-time web search results with source citations.
Supports Vertex AI integration for Google Cloud users as an alternative to Google AI Studio, allowing use of Google Cloud's Gemini models through Vertex AI.
MCP Gemini Google Search
A Model Context Protocol (MCP) server that provides Google Search functionality using Gemini's built-in Grounding with Google Search feature.
This project is inspired by the GoogleSearch tool from gemini-cli.
Features
Uses Gemini's built-in Grounding with Google Search feature
Provides real-time web search results with source citations
Compliant with MCP standard protocol
Supports stdio transport
Supports both Google AI Studio and Vertex AI
Requirements
Node.js 18 or later
Google AI Studio API key (Get one here) or Google Cloud Project with Vertex AI enabled
Installation
Usage
Environment Variables
Claude Code Configuration
You can set up this MCP server in Claude Code using the CLI:
For Google AI Studio
For Vertex AI
Windows Users
On Windows, wrap the npx command with cmd /c
:
Available Tools
google_search
Search Google for information.
Parameters:
query
(string, required): Search query
Example:
Development
To contribute to this project:
Debugging with MCP Inspector
Running npm run inspect
will open the MCP Inspector in your browser. This allows you to:
View available tools
Execute tools and see responses
Debug in real-time
License
Apache License 2.0
Tools
Provides Google Search functionality for AI models using Gemini's built-in Grounding with Google Search feature, returning real-time web search results with source citations.
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