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G-Search MCP

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jae-jae

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

Publisherjae-jae
Repositoryg-search-mcp
LanguageTypeScript
Forks
36
Stars
265
Available tools
1
Transport typestdio
Categories
LicenseMIT
Links
  • Connect tools to AI workflows

    G-Search MCP exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 1 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    265 stars and 36 forks from the linked repository.

G-Search MCP

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

This project is modified from google-search.

🌟 Recommended: OllaMan - Powerful Ollama AI Model Manager.

Advantages

  • Parallel Searching: Supports searching with multiple keywords on Google simultaneously, improving search efficiency
  • Browser Optimization: Opens multiple tabs in a single browser instance for efficient parallel searching
  • Automatic Verification Handling: Intelligently detects CAPTCHA and enables visible browser mode for user verification when needed
  • User Behavior Simulation: Simulates real user browsing patterns to reduce the possibility of detection by search engines
  • Structured Data: Returns structured search results in JSON format for easy processing and analysis
  • Configurable Parameters: Supports various parameter configurations such as search result limits, timeout settings, locale settings, etc.

Quick Start

Run directly with npx:

bash
npx -y g-search-mcp

First time setup - install the required browser by running the following command in your terminal:

bash
npx playwright install chromium

Debug Mode

Use the --debug option to run in debug mode (showing browser window):

bash
npx -y g-search-mcp --debug

Configure MCP

Configure this MCP server in Claude Desktop:

MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%/Claude/claude_desktop_config.json

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

Features

  • search - Execute Google searches with multiple keywords and return results
    • Uses Playwright browser to perform searches
    • Supports the following parameters:
      • queries: Array of search queries to execute (required parameter)
      • limit: Maximum number of results to return per query, default is 10
      • timeout: Page loading timeout in milliseconds, default is 60000 (60 seconds)
      • noSaveState: Whether to avoid saving browser state, default is false
      • locale: Locale setting for search results, default is en-US
      • debug: Whether to enable debug mode (showing browser window), overrides the --debug flag in command line

Example usage:

Use the search tool to search for "machine learning" and "artificial intelligence" on Google

Example response:

json
{
  "searches": [
    {
      "query": "machine learning",
      "results": [
        {
          "title": "What is Machine Learning? | IBM",
          "link": "https://www.ibm.com/topics/machine-learning",
          "snippet": "Machine learning is a branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy."
        },
        ...
      ]
    },
    {
      "query": "artificial intelligence",
      "results": [
        {
          "title": "What is Artificial Intelligence (AI)? | IBM",
          "link": "https://www.ibm.com/topics/artificial-intelligence",
          "snippet": "Artificial intelligence leverages computers and machines to mimic the problem-solving and decision-making capabilities of the human mind."
        },
        ...
      ]
    }
  ]
}

Usage Tips

Handling Special Website Scenarios

Adjusting Search Parameters

  • Search Result Quantity: For more search results:

    Please return the top 20 search results for each keyword

    This will set the limit: 20 parameter.

  • Increase Timeout Duration: For slow loading situations:

    Please set the page loading timeout to 120 seconds

    This will adjust the timeout parameter to 120000 milliseconds.

Locale Settings Adjustment

  • Change Search Region: Specify a different locale setting:
    Please use Chinese locale (zh-CN) for searching
    This will set the locale: "zh-CN" parameter.

Debugging and Troubleshooting

Enable Debug Mode

  • Dynamic Debug Activation: To display the browser window during a specific search operation:
    Please enable debug mode for this search operation
    This sets debug: true even if the server was started without the --debug flag.

Installation

Prerequisites

  • Node.js 18 or higher
  • NPM or Yarn

Install from Source

  1. Clone the repository:
bash
git clone https://github.com/jae-jae/g-search-mcp.git
cd g-search-mcp
  1. Install dependencies:
bash
npm install
  1. Install Playwright browser:
bash
npm run install-browser
  1. Build the server:
bash
npm run build

Development

Auto Rebuild (Development Mode)

bash
npm run watch

Using MCP Inspector for Debugging

bash
npm run inspector

Related Projects

  • fetcher-mcp: A powerful MCP server for fetching web page content using Playwright headless browser. Features intelligent content extraction, parallel processing, resource optimization, and more, making it an ideal tool for web content scraping.

License

Licensed under the MIT License

Installation

TypingMind
Prerequisites:

Node.js 18+

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

Use G-Search MCP MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once G-Search MCP is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add G-Search MCP as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the G-Search MCP MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "jae-jae-g-search-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "g-search-mcp"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the G-Search MCP MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the G-Search MCP MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use G-Search MCP to help me with this task?
G-Search MCP
Sure. I read it.
Here is what I found using G-Search MCP.

Frequently asked questions

What is the G-Search MCP MCP server used for?

G-Search MCP is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use G-Search MCP MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use G-Search MCP with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use G-Search MCP MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With G-Search MCP connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect G-Search MCP MCP to TypingMind?

G-Search MCP runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does G-Search MCP MCP provide in TypingMind?

G-Search MCP exposes 1 MCP tools that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use G-Search MCP MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If G-Search MCP requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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