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mcp-google-custom-search-server

MCP.Pizza Chef: limklister

The mcp-google-custom-search-server is a Model Context Protocol (MCP) server that integrates with Google's Custom Search API to provide web search capabilities for Language Learning Models (LLMs). It offers a type-safe TypeScript implementation with input validation using Zod, environment variable configuration, and configurable search result limits. The server returns formatted search results including titles, URLs, and descriptions, ensuring error handling and validation. Compatible with MCP clients like Claude Desktop, it standardizes web search access for LLMs, enabling them to retrieve real-time, relevant web data securely and efficiently.

Use This MCP server To

Enable LLMs to perform real-time web searches Retrieve formatted search results for query analysis Integrate Google Custom Search into AI workflows Provide web data context to language models Validate and sanitize search inputs automatically Configure search result limits for optimized responses Support multi-step reasoning with live web data Enhance AI assistants with external web knowledge

README

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/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

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"}}}

📝 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

mcp-google-custom-search-server FAQ

How do I configure the Google API credentials for this server?
You must set environment variables with your Google Cloud Project API key and Custom Search Engine ID as specified in the documentation.
Can this server handle multiple search queries concurrently?
Yes, the server is designed to handle concurrent requests efficiently while maintaining input validation and error handling.
What kind of search result formatting does the server provide?
The server returns search results with titles, URLs, and descriptions formatted for easy consumption by LLMs.
Is input validation enforced on search queries?
Yes, input validation is implemented using Zod to ensure queries meet required formats and prevent errors.
How many search results can be returned per query?
The number of results is configurable up to a maximum of 10 per query.
Does this server support integration with MCP clients other than Claude Desktop?
Yes, it is compatible with any MCP-compliant client, enabling broad integration possibilities.
What happens if the Google Custom Search API returns an error?
The server includes error handling to gracefully manage API errors and provide meaningful feedback to the client.
Is the server implementation type-safe?
Yes, it is implemented in TypeScript with strict typing to ensure reliability and maintainability.