Gemini Search MCP Server
Generates responses based on the latest information using the Gemini API and Google Search. Provides a search tool that takes a query and returns Gemini's response along with relevant search results.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Gemini Search MCP ServerWhat are the best practices for sustainable farming in 2025?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Gemini Search MCP Server
An MCP server that generates responses based on the latest information using the Gemini API and Google Search.
Note: This MCP server does not work standalone. It needs to be used in combination with AI assistants like Cline. The Gemini search functionality becomes available when you load this project into an AI assistant.
Gemini APIとGoogle検索を使用して、最新の情報に基づいた回答を生成するMCPサーバーです。
注意: このMCPサーバーは単体では動作しません。ClineなどのAIアシスタントと組み合わせて使用する必要があります。AIアシスタントにこのプロジェクトを読み込ませることで、Gemini検索機能が利用可能になります。
Features
Tools
search- Generate answers using Gemini 2.0 and Google SearchTakes a query as input and returns Gemini's response along with relevant search results
Related MCP server: gemini-grounded-search
機能
Tools
search- Gemini 2.0とGoogle検索を使用して質問に回答クエリを入力として受け取り、Geminiの回答と関連する検索結果を返します
Setup
Install dependencies:
npm installBuild:
npm run buildSet environment variables: Create a
.envfile in the project root with the following content:
GEMINI_API_KEY=your_api_key_hereNote: You can get your Gemini API key from Google AI Studio.
Development
For automatic builds during development:
npm run watchInstallation
To use with Claude Desktop, add the following configuration:
Windows: %APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"gemini": {
"command": "node",
"args": ["path/to/gemini-search-server/build/index.js"],
"env": {
"GEMINI_API_KEY": "your_api_key_here"
}
}
}
}Debugging
Since MCP servers communicate via stdio, we recommend using MCP Inspector for debugging:
npm run inspectorThe Inspector provides a URL to access debugging tools in your browser.
License
The code in this project is released under the MIT License. However, please note that this project uses the Google Gemini API, which is subject to Google's Terms of Service. When using this MCP server, you must comply with both the MIT License for our code and Google's terms for the Gemini API.
セットアップ
依存関係のインストール:
npm installビルド:
npm run build環境変数の設定:
.envファイルをプロジェクトのルートに作成し、以下の内容を設定してください:
GEMINI_API_KEY=your_api_key_here※ Gemini APIキーはGoogle AI Studioから取得できます。
開発
開発時の自動ビルド:
npm run watchインストール
Claude Desktopで使用するには、以下の設定を追加してください:
Windows: %APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"gemini": {
"command": "node",
"args": ["path/to/gemini-search-server/build/index.js"],
"env": {
"GEMINI_API_KEY": "your_api_key_here"
}
}
}
}デバッグ
MCPサーバーはstdioを介して通信するため、デバッグにはMCP Inspectorの使用を推奨します:
npm run inspectorInspectorはブラウザでデバッグツールにアクセスするためのURLを提供します。
ライセンス
このプロジェクトのコードはMIT Licenseの下で公開されています。 ただし、このプロジェクトはGoogle Gemini APIを使用しているため、Googleの利用規約も適用されます。このMCPサーバーを使用する際は、コードのMITライセンスとGemini APIの利用規約の両方に従う必要があります。
Available Tools
1 toolsearchB
Gemini 2.0とGoogle検索を使用して、最新の情報に基づいた回答を生成
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | 検索クエリ |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It mentions the tools used (Gemini 2.0 and Google search) which implies a read-only operation, but it does not disclose any limitations, side effects, or behavioral traits such as response format, rate limits, or source citation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that is front-loaded with the tool's core function. It contains no unnecessary words or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity (1 parameter, no output schema, no annotations), the description is moderately complete but lacks details about the return value or answer format. An agent would not know what to expect from the tool's output, making it insufficient for full invocation context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100% for the single 'query' parameter, and the description adds no additional parameter semantics. The baseline of 3 applies since the schema already documents the parameter adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: generating answers based on the latest information using Gemini 2.0 and Google search. It is specific about the resource and method, but does not differentiate from siblings since none exist.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for queries requiring up-to-date information, but it does not explicitly state when to use or not use this tool. Since there are no sibling tools, the guidance is limited but the context is reasonably implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
1 tool update
v0.1.0- First observed
search
TDQS
Only one tool exists, so there is no possibility of ambiguous selection. An agent will always know the purpose of the only tool.
The single tool 'search' uses a clear, simple verb name. With only one tool, there are no naming pattern inconsistencies to evaluate.
With just one tool, the server feels very thin. While the narrow purpose of search may justify a minimal surface, it is at the borderline of being too few tools for a coherent toolkit, so a score of 3 is appropriate.
The server's stated purpose is to generate answers using Gemini and Google search. The single 'search' tool fully covers this operation; there are no obvious missing functions within the given scope.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
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