G-Search MCP

Name: G-Search MCP
Author: jae-jae

@jae-jae

リポジトリホームページ

G-Search MCP について

A powerful MCP server for Google search that enables parallel searching with multiple keywords simultaneously.

#g-search #google-search #parallel-searching

基本情報

カテゴリ

検索

ライセンス

MIT

ランタイム

node

トランスポート

stdio

公開者

jae-jae

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "g-search": {
      "command": "npx",
      "args": [
        "-y",
        "g-search-mcp"
      ]
    }
  }
}

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is G-Search MCP?

G-Search MCP is a Model Context Protocol server that enables parallel Google searches with multiple keywords simultaneously using Playwright. It is designed for users of AI assistants like Claude Desktop who need structured search results.

How to use G-Search MCP?

Install Playwright browser with npx playwright install chromium. Run directly with npx -y g-search-mcp. Configure as an MCP server in Claude Desktop by adding the command to the mcpServers configuration. Use the search tool with parameters queries, limit, timeout, locale, and debug to perform searches.

Key features of G-Search MCP

Parallel searching with multiple keywords simultaneously
Opens multiple tabs in a single browser instance
Automatic CAPTCHA detection with visible browser mode
Simulates real user browsing behavior to reduce detection
Returns structured JSON search results
Configurable parameters (limit, timeout, locale, debug)

Use cases of G-Search MCP

Research multiple topics in parallel without manual switching
Automate competitive analysis by searching several queries at once
Gather structured data for data scraping or analysis projects
Use with AI assistants to fetch current search results dynamically

FAQ from G-Search MCP

What is the main advantage over standard Google search?

G-Search MCP supports parallel searching with multiple keywords, opens multiple tabs in a single browser, and automatically handles CAPTCHA while simulating real user behavior.