Gemini Google Search
Integrates Google Search functionality into Model Context Protocol (MCP) environments utilizing Gemini's built-in search capabilities.
About
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
- Supports both Google AI Studio and Vertex AI
- Provides real-time web search results with source citations
- Utilizes Gemini's built-in Grounding with Google Search feature
- Compliant with MCP standard protocol
- Supports stdio transport
- 17 GitHub stars
Use Cases
- Integrating dynamic search capabilities into MCP-compliant applications
- Enhancing AI models with real-time web information retrieval
- Providing factual grounding for large language models (LLMs)
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