This MCP server, developed by Kevin Watt, integrates SearXNG's meta-search capabilities into AI workflows. Built with TypeScript and leveraging the Model Context Protocol SDK, it provides a privacy-focused search interface that combines results from multiple engines. The implementation offers features like multi-category searches, language filtering, time range selection, and adjustable safe search levels. By connecting AI models with SearXNG's robust search functionality, this server enables sophisticated information retrieval scenarios such as multi-source research, trend analysis, and content aggregation. It's particularly valuable for applications requiring privacy-conscious, diverse, and customizable search results, making it ideal for research tools, content curation systems, and privacy-oriented AI assistants.
Execute meta searches across multiple engines. Inputs: query (string): Search terms, page (number, optional): Page number (default: 1), language (string, optional): Language code (e.g., 'en', 'all', default: 'all'), categories (array, optional): Search categories (default: ['general']), time_range (string, optional): Time filter (day/week/month/year), safesearch (number, optional): Safe search level (0: None, 1: Moderate, 2: Strict, default: 1)
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