What prerequisites are needed?
Node.js v16 or higher, a Google Cloud Platform account, a Custom Search Engine ID, and a Google API Key.
@MCP-Mirror
基本信息
Mirror of
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当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
An MCP (Model Context Protocol) server that provides Google search capabilities and webpage content analysis tools. It enables AI models to perform Google searches, extract webpage content, and analyze results programmatically.
Install Node.js dependencies, build TypeScript, and configure your Google API credentials (GOOGLE_API_KEY, GOOGLE_SEARCH_ENGINE_ID) in the MCP settings file. Start the server with npm run start. Invoke tools like google_search, extract_webpage_content, or extract_multiple_webpages via any MCP client.
Node.js v16 or higher, a Google Cloud Platform account, a Custom Search Engine ID, and a Google API Key.
Set environment variables `GOOGLE_API_KEY` and `GOOGLE_SEARCH_ENGINE_ID`, then add the server configuration to your MCP settings file (e.g., `cline_mcp_settings.json`) with the `stdio` transport type.
Three tools: `google_search` (with optional filters and pagination), `extract_webpage_content` (single URL), and `extract_multiple_webpages` (batch URLs). All support auto-approval in MCP settings.
The server returns detailed error messages for missing or invalid API credentials, failed search requests, invalid URLs, and network connectivity issues.
Search results and webpage content are fetched live from Google and the target websites. The server caches responses locally to reduce API calls, but no data is stored permanently.
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