Skip to main content
Glama

MCP Gemini Google Search

by yukukotani
Apache 2.0
4

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

npm install -g mcp-gemini-google-search

Usage

Environment Variables

# For Google AI Studio (default) export GEMINI_API_KEY="your-api-key-here" export GEMINI_MODEL="gemini-2.5-flash" # Optional (default: gemini-2.5-flash) # For Vertex AI export GEMINI_PROVIDER="vertex" export VERTEX_PROJECT_ID="your-gcp-project-id" export VERTEX_LOCATION="us-central1" # Optional (default: us-central1) export GEMINI_MODEL="gemini-2.5-flash" # Optional (default: gemini-2.5-flash)

Claude Code Configuration

Add the following to your Claude Code settings:

For Google AI Studio
{ "mcpServers": { "gemini-google-search": { "command": "npx", "args": ["mcp-gemini-google-search"], "env": { "GEMINI_API_KEY": "your-api-key-here", "GEMINI_MODEL": "gemini-2.5-flash" } } } }
For Vertex AI
{ "mcpServers": { "gemini-google-search": { "command": "npx", "args": ["mcp-gemini-google-search"], "env": { "GEMINI_PROVIDER": "vertex", "VERTEX_PROJECT_ID": "your-gcp-project-id", "VERTEX_LOCATION": "us-central1", "GEMINI_MODEL": "gemini-2.5-flash" } } } }

Available Tools

Search Google for information.

Parameters:

  • query (string, required): Search query

Example:

latest TypeScript features
It appears you're asking about the latest features in TypeScript. Here's a summary of recent updates and key features, based on the provided search results: **Key Features in Recent TypeScript Updates:** * **Satisfies Operator:** This operator lets you specify that a value conforms to a specific type without fully enforcing it.[1,2] * **Const Type Parameters:** Using `const` with type parameters provides more precision with function generics, helping specify literal types and prevent unwanted transformations.[2] This ensures arrays are treated as immutable, maintaining their literal types.[2] * **Improved Enum Types:** Enums are more robust, especially `const enum`, which optimizes enums by inlining their values at compile time.[2] From version 5.0, all enums are treated as a type union, even with calculated values.[1] * **Template Literal Types:** Template literal types are more expressive, allowing you to create types that build on literals, similar to JavaScript template strings.[2] * **Unions and Intersections with Discriminated Unions:** TypeScript offers better handling for union and intersection types, which are frequently used to build flexible types.[2] Discriminated unions allow you to create complex structures with ease and clear type guards.[2] * **New ECMAScript Set Methods:** Support for new methods like `union`, `intersection`, and `difference` for more powerful set operations.[3] **TypeScript 5.8 Highlights (March 2025):** * **Module Node18 Flag:** Provides a stable reference point for users fixed on Node.js 18, without incorporating certain behaviors of `--module nodenext`.[4] * **Optimizations:** Introduces optimizations that improve the time to build up a program and update it based on file changes, especially in `--watch` mode or editor scenarios.[4] This includes avoiding array allocations during path normalization.[4] * **Import Assertions:** `--module nodenext` in TypeScript 5.8 will issue an error if it encounters an import assertion, as Node.js 22 no longer accepts them using the `assert` syntax, recommending `with` instead.[4] **Other Notable Features & Improvements:** * **Inferred Type Predicates:** Improved type inference, especially with arrays and filtering.[3] * **Control Flow Narrowing for Constant Indexed Accesses:** Better type narrowing for accessing object properties.[3] * **Regular Expression Syntax Checking:** Basic syntax checks are performed on regular expressions, flagging errors like unclosed parentheses.[3] * **Array filter Fixes:** Properly filters the type of arrays when you use the filter function. * **Object Key Inference Fixes:** Improves type inference. **Performance Enhancements:** * **Go Rewrite:** A full rewrite of TypeScript in Go has been promised for version 7.0, which has demonstrated significant speed improvements (up to 10x-15x in some cases).[5] This will affect the compiler (`tsc`) and IDE performance (loading, hovers, errors, etc.).[5] The team chose Go for its structural similarity to the current JavaScript implementation.[5] * **TypeScript 5.0:** This update aimed to accelerate coding processes and simplify development by refining code, data structures, and streamlining import/export operations.[6] In summary, TypeScript is continuously evolving with new features and improvements aimed at enhancing developer productivity, code quality, and performance.[6] Sources: [1] edicomgroup.com (https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFILdgh_4-Yh0OuwzDOqwCfvLGHdhm_PGhdAIzMK_DFwW38X9qK8b3Tj_ws2VZ2VLxWW_NJtuzot8B_wYYH4rOHBY_1HYZ7PyCHOCR3GzQpwQUi71ufAf6izU13O3W6GzjQAQnVjnheeRLLLf4mD7uueIS-g0yeivFo2XWZKJF4wtRtDfdTYjtHvRYmB7rY6Q==) [2] dev.to (https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFFMJOcmJDu8TUJsc6cKjVMDTR7ggjQMUc1aMAIVKRhbTq7Zjzh5f_h-UpZn6LE6xB-nTqUmQwHCiUmhvAZ_uYmzXIzNmJvtoDUjDcB9hJDw_aPPvJjd411APwVfiNvd3yhlrB7MFsnxH25-hxNetmoZJrriZ0mGm6ZaYbm0yMeiruDqC5mnqXJwuyGLMdrg-M3LpRAGrxVAT9b1veE) [3] dev.to (https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFfDcb-2QNwLZ0TpjSkNCWCvh-dvslYtllEMyyTXCSu-3jbOBD4vvq0j5Hqyuw8BcmEpKjBBeBZS83E-GCKax48hg5Oc1Fam6GQy296DxQkEQOfg7pvmnRhE3tdDbDCBqXKdYPonoR_AVLBAlGdKg==) [4] microsoft.com (https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEWKA9uZsB7lcOGcnOLveyjImsqVwNItCj3n3QiCrCkyL6iY4rA16Wp37FecAoKgX58lcDcBOuXye97fgw5SAbLwDkl3M-vCUK0I0HxtCx8qMaBVM42sxyFEQjn1iz4Qgzud3P7pDlc4frHf6Wkgs8nNcoIlMriePVOb0l9vmY=) [5] totaltypescript.com (https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFysE6zFlg_XiXfGqAiDapTIj2bsVWlkuq3Trpfacjd1a7gMDrUh35MKW-No9qdSKti68W3M2b1j6VqlnZ7v_yBOjE8hK_3d57U7UePyjMOUDdbBBGRK8CZeUug3hBOFsZjbnQoDdoL446oZL1R38gJrc9JvGmlWQno) [6] rabitsolutions.com (https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEY1brKmgxI5YOA1HrB89SnHNPyhm3Dlz-zumJMoi-wBegLSOjto360JJrA29TwVB8A02qHWZBtwua0QHn8NxAjWUCCkLxD7lZa_xW4Mtp8diiAXl1ppIWEHq6T7B1Mm6_dMs3lWoOKOJSjCUrk6-P4ao40V-nYULfPtA==)

Development

To contribute to this project:

# Clone the repository git clone https://github.com/yukukotani/mcp-gemini-google-search.git cd mcp-gemini-google-search # Install dependencies npm install # Development mode (watch for file changes) npm run dev # Build npm run build # Run locally npm run start # Debug with MCP Inspector npm run inspect

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

MIT

Install Server
A
security – no known vulnerabilities
A
license - permissive license
A
quality - confirmed to work

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.

  1. Features
    1. Requirements
      1. Installation
        1. Usage
          1. Environment Variables
          2. Claude Code Configuration
          3. Available Tools
        2. Development
          1. Debugging with MCP Inspector
        3. License

          Related MCP Servers

          • A
            security
            A
            license
            A
            quality
            Provides web search capabilities using Google Custom Search API, enabling users to perform searches through a Model Context Protocol server.
            Last updated -
            2
            1,030
            23
            JavaScript
            MIT License
            • Apple
          • -
            security
            A
            license
            -
            quality
            A server that enables document searching using Vertex AI with Gemini grounding, improving search results by grounding responses in private data stored in Vertex AI Datastore.
            Last updated -
            18
            Python
            Apache 2.0
          • -
            security
            F
            license
            -
            quality
            A server that provides access to Google Gemini AI capabilities including text generation, image analysis, YouTube video analysis, and web search functionality through the MCP protocol.
            Last updated -
            2
            TypeScript
            • Apple
          • -
            security
            A
            license
            -
            quality
            Provides web search functionality for the Gemini Terminal Agent, handling concurrent requests and content extraction to deliver real-time information from the web.
            Last updated -
            Python
            Apache 2.0

          View all related MCP servers

          MCP directory API

          We provide all the information about MCP servers via our MCP API.

          curl -X GET 'https://glama.ai/api/mcp/v1/servers/yukukotani/mcp-gemini-google-search'

          If you have feedback or need assistance with the MCP directory API, please join our Discord server