MCP Gemini Google Search
M

MCP Gemini Google Search

A server based on the MCP protocol that utilizes the built-in Google Search function of Gemini to provide real-time web search services, supporting two access methods, Google AI Studio and Vertex AI.
2.5 points
8.3K

What is MCP Gemini Google Search?

MCP Gemini Google Search is a Model Context Protocol (MCP) server that utilizes the built-in Google Search function of Gemini to provide users with real-time web search results and citation sources. It complies with the MCP standard protocol and supports multiple transmission methods.

How to use MCP Gemini Google Search?

Configure the API key or project information by setting environment variables, and then start the server. Users can call the search function through the command line or integrated tools to obtain real-time web information.

Applicable scenarios

Suitable for scenarios that require real-time web information queries, academic research, news summaries, etc. Particularly suitable for research and development work that requires citation sources.

Main features

Built-in Google Search function
Directly utilize the Google Search capabilities of Gemini without additional configuration of a search engine.
Real-time search and citation
Provide real-time web search results with source citations to ensure the traceability of information.
MCP protocol compatibility
Fully comply with the Model Context Protocol (MCP) standard to ensure compatibility with other systems.
Multi-platform support
Support stdio transmission and can run in various environments, including local development and cloud deployment.
Two API modes
Support two API modes, Google AI Studio and Vertex AI, to meet different needs.
Advantages
Provide real-time web search results to ensure the timeliness of information.
Built-in Google Search function without additional configuration.
Support multiple API modes to adapt to different usage scenarios.
Comply with the MCP standard protocol and are easy to integrate into existing systems.
Provide clear citation sources to enhance the credibility of information.
Limitations
Dependent on Google Search services and may be subject to API restrictions.
Require a valid API key or project configuration, and initial use may require some setup.
Support for certain regions or languages may be limited.
Performance may need to be optimized under high concurrency.
Search results for non-English content may not meet expectations.

How to use

Installation
Install the MCP Gemini Google Search server using npm.
Configure environment variables
Set the necessary environment variables according to the API type used (Google AI Studio or Vertex AI).
Start the server
Run the command to start the MCP Gemini Google Search server.
Call the search function
Call the search function through the command line or integrated tools and enter the query term to get the results.

Usage examples

Find the latest TypeScript features
Users want to learn about the latest TypeScript updates, including new features and improvements.
Search for artificial intelligence research papers
Researchers need to find recent research papers related to artificial intelligence.

Frequently Asked Questions

What prerequisites are required for MCP Gemini Google Search?
How to choose between Google AI Studio and Vertex AI?
Does MCP Gemini Google Search support Chinese?
How to debug MCP Gemini Google Search?

Related resources

GitHub repository
Project source code and documentation
Model Context Protocol (MCP)
Official documentation of the MCP protocol
Gemini API documentation
Explanation of the Google Search function of the Gemini API
Claude Code guide
Claude Code usage guide

Installation

Copy the following command to your Client for configuration
Note: Your key is sensitive information, do not share it with anyone.

Alternatives

A
Airweave
Airweave is an open - source context retrieval layer for AI agents and RAG systems. It connects and synchronizes data from various applications, tools, and databases, and provides relevant, real - time, multi - source contextual information to AI agents through a unified search interface.
Python
15.2K
5 points
V
Vestige
Vestige is an AI memory engine based on cognitive science. By implementing 29 neuroscience modules such as prediction error gating, FSRS - 6 spaced repetition, and memory dreaming, it provides long - term memory capabilities for AI. It includes a 3D visualization dashboard and 21 MCP tools, runs completely locally, and does not require the cloud.
Rust
9.6K
4.5 points
M
Moltbrain
MoltBrain is a long-term memory layer plugin designed for OpenClaw, MoltBook, and Claude Code, capable of automatically learning and recalling project context, providing intelligent search, observation recording, analysis statistics, and persistent storage functions.
TypeScript
10.2K
4.5 points
B
Bm.md
A feature-rich Markdown typesetting tool that supports multiple style themes and platform adaptation, providing real-time editing preview, image export, and API integration capabilities
TypeScript
14.9K
5 points
S
Security Detections MCP
Security Detections MCP is a server based on the Model Context Protocol that allows LLMs to query a unified security detection rule database covering Sigma, Splunk ESCU, Elastic, and KQL formats. The latest version 3.0 is upgraded to an autonomous detection engineering platform that can automatically extract TTPs from threat intelligence, analyze coverage gaps, generate SIEM-native format detection rules, run tests, and verify. The project includes over 71 tools, 11 pre-built workflow prompts, and a knowledge graph system, supporting multiple SIEM platforms.
TypeScript
8.8K
4 points
P
Paperbanana
Python
9.0K
5 points
B
Better Icons
An MCP server and CLI tool that provides search and retrieval of over 200,000 icons, supports more than 150 icon libraries, and helps AI assistants and developers quickly obtain and use icons.
TypeScript
9.7K
4.5 points
A
Assistant Ui
assistant - ui is an open - source TypeScript/React library for quickly building production - grade AI chat interfaces, providing composable UI components, streaming responses, accessibility, etc., and supporting multiple AI backends and models.
TypeScript
10.0K
5 points
M
Markdownify MCP
Markdownify is a multi-functional file conversion service that supports converting multiple formats such as PDFs, images, audio, and web page content into Markdown format.
TypeScript
38.2K
5 points
G
Gitlab MCP Server
Certified
The GitLab MCP server is a project based on the Model Context Protocol that provides a comprehensive toolset for interacting with GitLab accounts, including code review, merge request management, CI/CD configuration, and other functions.
TypeScript
27.5K
4.3 points
D
Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
81.9K
4.3 points
N
Notion Api MCP
Certified
A Python-based MCP Server that provides advanced to-do list management and content organization functions through the Notion API, enabling seamless integration between AI models and Notion.
Python
25.0K
4.5 points
F
Figma Context MCP
Framelink Figma MCP Server is a server that provides access to Figma design data for AI programming tools (such as Cursor). By simplifying the Figma API response, it helps AI more accurately achieve one - click conversion from design to code.
TypeScript
70.8K
4.5 points
U
Unity
Certified
UnityMCP is a Unity editor plugin that implements the Model Context Protocol (MCP), providing seamless integration between Unity and AI assistants, including real - time state monitoring, remote command execution, and log functions.
C#
37.5K
5 points
C
Context7
Context7 MCP is a service that provides real-time, version-specific documentation and code examples for AI programming assistants. It is directly integrated into prompts through the Model Context Protocol to solve the problem of LLMs using outdated information.
TypeScript
106.4K
4.7 points
M
Minimax MCP Server
The MiniMax Model Context Protocol (MCP) is an official server that supports interaction with powerful text-to-speech, video/image generation APIs, and is suitable for various client tools such as Claude Desktop and Cursor.
Python
55.5K
4.8 points
AIBase
Zhiqi Future, Your AI Solution Think Tank
© 2026AIBase