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Google Search MCP Server

by mixelpixx

An MCP server that provides Google search capabilities and webpage content analysis tools. This server enables AI models to perform Google searches and analyze webpage content programmatically.

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What is Google Search MCP Server?

The Google Search MCP Server is a tool that allows AI models to programmatically perform Google searches and analyze webpage content. It acts as a bridge between AI assistants and the Google search engine, providing structured access to search results and extracted webpage data.

How to use Google Search MCP Server?

To use the server, you need to install the necessary dependencies (Node.js, Python, Google API client), configure your Google API credentials, and set up the MCP server configuration for your AI assistant (Cline or Claude). Then, you can use the provided tools (google_search, extract_webpage_content, extract_multiple_webpages) with appropriate arguments to perform searches and extract content.

Key features of Google Search MCP Server

  • Advanced Google Search with filtering options

  • Detailed webpage content extraction and analysis

  • Batch webpage analysis for comparing multiple sources

  • Environment variable support for API credentials

  • Comprehensive error handling and user feedback

  • MCP-compliant interface for seamless integration with AI assistants

Use cases of Google Search MCP Server

  • AI assistants performing research tasks

  • Automated content analysis and comparison

  • Gathering information from multiple sources

  • Providing AI models with real-time information

  • Enhancing AI model capabilities with web search functionality

FAQ from Google Search MCP Server

What are the prerequisites for running this server?

You need Node.js (v16 or higher), Python (v3.8 or higher), a Google Cloud Platform account, a Custom Search Engine ID, and a Google API Key.

How do I configure the Google API credentials?

You can provide the credentials either through environment variables (GOOGLE_API_KEY and GOOGLE_SEARCH_ENGINE_ID) or by creating an api-keys.json file in the root directory.

What is MCP?

MCP stands for Model Context Protocol. It's an interface that allows AI assistants to interact with external tools and services.

How do I extract content from multiple webpages?

Use the extract_multiple_webpages tool and provide an array of URLs in the 'urls' argument.

What kind of error handling is provided?

The server provides detailed error messages for missing API credentials, failed search requests, invalid URLs, and network connectivity issues.