What is Alexatnordnet Mcp Google Custom Search Server

alexatnordnet_mcp-google-custom-search-server is a Model Context Protocol (MCP) server that utilizes Google’s Custom Search API to provide web search capabilities. It allows Language Learning Models (LLMs) to perform web searches through a standardized interface.

Use cases

Use cases include enhancing language learning tools with real-time web search capabilities, developing research assistants that pull information from the web, and integrating search functionalities into chatbots or virtual assistants.

How to use

To use alexatnordnet_mcp-google-custom-search-server, clone the repository, install the necessary dependencies, configure your Google API credentials in a .env file, build the server, and then start it. Ensure you have a Google Cloud Project with the Custom Search API enabled and a Custom Search Engine ID.

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 (up to 10 per query), formatted search results with titles, URLs, and descriptions, and robust error handling.

Where to use

This server can be used in various fields such as education for language learning applications, research for retrieving web-based information, and any application requiring web search capabilities integrated with LLMs.

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

   • Visit Google Cloud Console
   • Enable the Custom Search API
   • Create API credentials

2. A Custom Search Engine ID

   • Visit Programmable Search Engine
   • Create a new search engine
   • Get your 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/yourusername/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

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"}}}
   

📝 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