Integrates Google Search functionality into Model Context Protocol (MCP) environments utilizing Gemini's built-in search capabilities.
This tool functions as a Model Context Protocol (MCP) server, enabling applications to perform Google searches by leveraging Gemini's native Grounding with Google Search feature. It provides real-time web search results complete with source citations, adhering to the MCP standard protocol. Compatible with both Google AI Studio and Vertex AI, it supports stdio transport for versatile integration into various development workflows.
Key Features
01Supports both Google AI Studio and Vertex AI
02Provides real-time web search results with source citations
03Utilizes Gemini's built-in Grounding with Google Search feature
04Compliant with MCP standard protocol
05Supports stdio transport
0617 GitHub stars
Use Cases
01Integrating dynamic search capabilities into MCP-compliant applications
02Enhancing AI models with real-time web information retrieval
03Providing factual grounding for large language models (LLMs)
