Google Search MCP Server
by mixelpixx
An MCP server providing Google search and webpage content analysis for AI models. It enables programmatic Google searches and webpage analysis.
Last updated: N/A
What is Google Search MCP Server?
The Google Search MCP Server is a tool that allows AI models to perform Google searches and analyze webpage content programmatically, integrating seamlessly with AI assistants via the Model Context Protocol (MCP). It consists of a TypeScript MCP server and a Python Flask server for handling Google API interactions and webpage content analysis.
How to use Google Search MCP Server?
To use the server, you need to clone the repository, install the necessary Node.js and Python dependencies, configure API credentials (either via environment variables or an api-keys.json file), and then configure your MCP settings in Cline or Claude Desktop App. You can then run the server using either the recommended method of starting the Python servers separately and configuring the MCP settings to run only the Node.js server, or by using the all-in-one script. Available tools include google_search, extract_webpage_content, and extract_multiple_webpages, each with specific arguments for customization.
Key features of Google Search MCP Server
Advanced Google Search with filtering
Detailed webpage content extraction
Batch webpage analysis
Environment variable support for API credentials
Comprehensive error handling
MCP-compliant interface
Use cases of Google Search MCP Server
Searching for information on specific topics
Extracting content from webpages for analysis
Comparing information across multiple sources
Gathering comprehensive information on a topic
Providing AI assistants with real-time search capabilities
FAQ from Google Search MCP Server
What are the prerequisites for running this server?
What are the prerequisites for running this server?
Node.js (v16 or higher), Python (v3.8 or higher), Google Cloud Platform account, Custom Search Engine ID, and Google API Key.
How do I configure the Google API credentials?
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?
What is MCP?
MCP stands for Model Context Protocol, which allows seamless integration with AI assistants.
What are the available tools?
What are the available tools?
The available tools are google_search, extract_webpage_content, and extract_multiple_webpages.
How do I handle errors?
How do I handle errors?
The server provides detailed error messages for missing API credentials, failed search requests, invalid URLs, and network issues.