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Google Search (Gemini)▌

by yukukotani

Access Google Search via Gemini's native API for reliable info and automatic MLA citations. Ideal for developers and ref

Provides Google Search functionality through Gemini's native grounding capabilities, delivering search results with automatic source citations and grounding metadata for reliable information retrieval.

github stars

★ 76

GitHubnpm
Built-in source citationsUses Gemini's native groundingSupports both AI Studio and Vertex AI

best for

  • / Researchers needing cited web information
  • / AI applications requiring real-time search
  • / Content creators verifying current information
  • / Developers building search-enabled assistants

capabilities

  • / Search Google using Gemini's grounding feature
  • / Retrieve real-time web search results
  • / Provide automatic source citations
  • / Access grounding metadata for results
  • / Connect via Google AI Studio or Vertex AI

what it does

Provides Google Search functionality through Gemini's grounding capabilities with automatic source citations and metadata for reliable information retrieval.

about

Google Search (Gemini) is a community-built MCP server published by yukukotani that provides AI assistants with tools and capabilities via the Model Context Protocol. Access Google Search via Gemini's native API for reliable info and automatic MLA citations. Ideal for developers and ref It is categorized under search web.

how to install

You can install Google Search (Gemini) in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

Apache-2.0

Google Search (Gemini) is released under the Apache-2.0 license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

MCP Gemini Google Search

日本語

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

You can set up this MCP server in Claude Code using the CLI:

For Google AI Studio

# Add to user scope (available across all projects)
claude mcp add gemini-google-search \
  -s user \
  -e GEMINI_API_KEY="your-api-key-here" \
  -e GEMINI_MODEL="gemini-2.5-flash" \
  -- npx mcp-gemini-google-search

# Or add to project scope to share with your team
claude mcp add gemini-google-search \
  -s project \
  -e GEMINI_API_KEY="your-api-key-here" \
  -e GEMINI_MODEL="gemini-2.5-flash" \
  -- npx mcp-gemini-google-search

For Vertex AI

# Add to user scope (available across all projects)
claude mcp add gemini-google-search \
  -s user \
  -e GEMINI_PROVIDER="vertex" \
  -e VERTEX_PROJECT_ID="your-gcp-project-id" \
  -e VERTEX_LOCATION="us-central1" \
  -e GEMINI_MODEL="gemini-2.5-flash" \
  -- npx mcp-gemini-google-search

# Or add to project scope to share with your team
claude mcp add gemini-google-search \
  -s project \
  -e GEMINI_PROVIDER="vertex" \
  -e VERTEX_PROJECT_ID="your-gcp-project-id" \
  -e VERTEX_LOCATION="us-central1" \
  -e GEMINI_MODEL="gemini-2.5-flash" \
  -- npx mcp-gemini-google-search

Windows Users

On Windows, wrap the npx command with cmd /c:

claude mcp add gemini-google-search \
  -e GEMINI_API_KEY="your-api-key-here" \
  -- cmd /c npx mcp-gemini-google-search

Available Tools

google_search

Search Google for information.

Parameters:

  • query (string, required): Search query

Example:

latest TypeScript features
<details> <summary>Example Response</summary> 
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==)
</details>

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

Apache License 2.0