This Kagi MCP server, developed by Aleksey Pridachin, integrates the Kagi search API into the Model Context Protocol ecosystem. Built with Python using libraries like httpx and mcp, it provides tools for web search, news retrieval, and fast GPT-powered question answering. The server implements environment-based configuration for API key management and offers a streamlined interface to Kagi's advanced search capabilities. By abstracting Kagi API operations into a standardized MCP format, it enables AI systems to easily access high-quality web search results and enriched content. This implementation is particularly valuable for applications requiring up-to-date information retrieval, facilitating use cases such as research assistance, fact-checking, and content enrichment across various domains.
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Highlight AISearch the web and find an answer.
Enrich model context with web content.
Enrich model context with the latest news.