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MCP Google Custom Search Server: Tailored, Lightning-Fast Search - MCP Implementation

MCP Google Custom Search Server: Tailored, Lightning-Fast Search

Mirror your search excellence with MCP Google Custom Server—tailored, lightning-fast results that adapt to your world. Effortlessly find your 'why' in every query.

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About MCP Google Custom Search Server

What is MCP Google Custom Search Server: Tailored, Lightning-Fast Search?

This server acts as a bridge between Language Learning Models (LLMs) and Google's Custom Search API, enabling seamless web search capabilities through the Model Context Protocol (MCP). Built with TypeScript for robust type safety, it provides a standardized interface for LLMs to access real-time search results quickly and efficiently. Whether you're developing conversational AI or enterprise tools, this server delivers precise, configurable search outcomes tailored to your needs.

How to Use MCP Google Custom Search Server: Tailored, Lightning-Fast Search?

Deployment is straightforward: first, secure Google API credentials via the Cloud Console and create a Programmable Search Engine. Configure the server with environment variables specifying your API key and search engine ID, then compile and run the TypeScript codebase. Integration with platforms like Claude Desktop requires minimal setup—simply map the server endpoint to your application’s search workflow using the provided configuration examples. Real-time results are returned in under a second, ensuring smooth user experiences.

MCP Google Custom Search Server Features

Key Features of MCP Google Custom Search Server: Tailored, Lightning-Fast Search?

  • Adaptive Query Handling: Processes natural language queries into optimized search parameters using built-in sanitization and parameter tuning
  • Granular Control: Adjust result count (1-10), filtering options, and response formatting via intuitive API parameters
  • Enterprise-Ready Security: Implements rate limiting, IP whitelisting, and OAuth2 authentication by default
  • Performance Optimization: Caches frequently accessed queries while maintaining freshness through Google's real-time indexing
  • Cross-Platform Compatibility: Works with Python, JavaScript, and Java clients through standardized JSON responses

Use Cases of MCP Google Custom Search Server: Tailored, Lightning-Fast Search?

Power chatbots with instant knowledge updates by connecting to Google's live index, or create internal enterprise search portals that blend public web results with private data sources. The server excels in:

  • Customer service bots needing up-to-date product info
  • Research platforms requiring academic article previews
  • Travel agencies curating real-time flight/hotel data
  • Education tools for plagiarism detection and reference verification

MCP Google Custom Search Server FAQ

FAQ from MCP Google Custom Search Server: Tailored, Lightning-Fast Search?

Q: How do I handle API rate limits?
The server automatically implements exponential backoff strategies and provides retry mechanisms through the Retry-After header.

Q: Can I customize search regions?
Yes, specify gl parameters to prioritize results from particular countries or languages.

Q: What's the maximum query length?
Supports up to 256 characters, with automatic truncation warnings for excessively long inputs.

Q: Does it support HTTPS?
Fully encrypted by default, with certificate validation enforced on all API requests.

Q: How do I monitor performance?
Built-in metrics endpoint (/debug/metrics) provides latency histograms and error rates in Prometheus format.

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
* Visit [Google Cloud Console](https://console.cloud.google.com)
* Enable the Custom Search API
* Create API credentials
  1. A Custom Search Engine ID
* Visit [Programmable Search Engine](https://programmablesearchengine.google.com/)
* Create a new search engine
* Get your Search Engine ID
  1. 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
  1. Install dependencies:

    npm install

  2. Create a .env file:

    GOOGLE_API_KEY=your-api-key

GOOGLE_SEARCH_ENGINE_ID=your-search-engine-id
  1. Build the server:

    npm run build

  2. 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

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