MCP ExplorerExplorer

Mcp Google Custom Search Server

@alexatnordneton a year ago
24 MIT
FreeCommunity
AI Systems
An mcp server for searching against google custom search api

Overview

What is Mcp Google Custom Search Server

mcp-google-custom-search-server is an MCP server that enables web search capabilities through Google’s Custom Search API, allowing Language Learning Models (LLMs) to perform searches using a standardized interface.

Use cases

Use cases include enhancing educational tools with web search capabilities, integrating search functionalities in chatbots, and developing applications that require real-time information retrieval from the web.

How to use

To use mcp-google-custom-search-server, clone the repository, install dependencies, create a .env file with your Google API key and Search Engine ID, build the server, and start it using npm commands.

Key features

Key features include seamless integration with Google Custom Search API, compliance with Model Context Protocol (MCP), type-safe implementation using TypeScript, configurable search results, input validation, and error handling.

Where to use

mcp-google-custom-search-server can be used in various fields such as education, research, and any application requiring web search capabilities integrated with Language Learning Models.

Content

MCP Google Custom Search Server

A Model Context Protocol (MCP) server that provides web search capabilities through Google’s Custom Search API. This server enables Language Learning Models (LLMs) to perform web searches using a standardized interface.

🌟 Features

  • Seamless integration with Google Custom Search API
  • Model Context Protocol (MCP) compliant server implementation
  • Type-safe implementation using TypeScript
  • Environment variable configuration
  • Input validation using Zod
  • Configurable search results (up to 10 per query)
  • Formatted search results including titles, URLs, and descriptions
  • Error handling and validation
  • Compatible with Claude Desktop and other MCP clients

📋 Prerequisites

Before you begin, ensure you have:

  1. A Google Cloud Project with Custom Search API enabled

  2. A Custom Search Engine ID

  3. Local development requirements:

    • Node.js (v18 or higher)
    • npm (comes with Node.js)

🚀 Quick Start

  1. Clone the repository:

    git clone https://github.com/limklister/mcp-google-custom-search-server.git
    cd mcp-google-custom-search-server
    
  2. Install dependencies:

    npm install
    
  3. Create a .env file:

    GOOGLE_API_KEY=your-api-key
    GOOGLE_SEARCH_ENGINE_ID=your-search-engine-id
    
  4. Build the server:

    npm run build
    
  5. Start the server:

    npm start
    

🔧 Configuration

Environment Variables

Variable Description Required
GOOGLE_API_KEY Your Google Custom Search API key Yes
GOOGLE_SEARCH_ENGINE_ID Your Custom Search Engine ID Yes

Claude Desktop Integration

Add this configuration to your Claude Desktop config file (typically located at ~/Library/Application Support/Claude/claude_desktop_config.json):

{
  "mcpServers": {
    "google-search": {
      "command": "node",
      "args": [
        "/absolute/path/to/mcp-google-custom-search-server/build/index.js"
      ],
      "env": {
        "GOOGLE_API_KEY": "your-api-key",
        "GOOGLE_SEARCH_ENGINE_ID": "your-search-engine-id"
      }
    }
  }
}

📖 API Reference

Available Tools

search

Performs a web search using Google Custom Search API.

Parameters:

  • query (string, required): The search query to execute
  • numResults (number, optional): Number of results to return
    • Default: 5
    • Maximum: 10

Example Response:

Result 1:
Title: Example Search Result
URL: https://example.com
Description: This is an example search result description
---

Result 2:
...

🛠️ Development

Project Structure

mcp-google-custom-search-server/
├── src/
│   └── index.ts          # Main server implementation
├── build/                # Compiled JavaScript output
├── .env                  # Environment variables
├── package.json          # Project dependencies and scripts
├── tsconfig.json         # TypeScript configuration
└── README.md            # Project documentation

Available Scripts

  • npm run build: Compile TypeScript to JavaScript
  • npm start: Start the MCP server
  • npm run dev: Watch mode for development

Testing

  1. Using MCP Inspector:

    npx @modelcontextprotocol/inspector node build/index.js
    
  2. Manual testing with example queries:

    # After starting the server
    {"jsonrpc":"2.0","id":1,"method":"callTool","params":{"name":"search","arguments":{"query":"example search"}}}
    
Google Custom Search Server MCP server

MseeP.ai Security Assessment Badge

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

  • Built with Model Context Protocol (MCP)
  • Uses Google’s Custom Search API
  • Inspired by the need for better search capabilities in LLM applications

Tools

No tools

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