Yavy transforms websites into AI-searchable knowledge bases by acting as a bridge between content and large language models. The platform crawls websites, extracts meaningful content from every page, and creates searchable indexes that AI assistants can query through the Model Context Protocol (MCP) standard.

Key features include semantic search using AI-powered vector embeddings that finds relevant content based on meaning rather than just keywords. The platform provides live syncing with updates propagating in milliseconds, automatic URL discovery and indexing with zero configuration required, and support for both public sources and private sources using OAuth 2.1 authentication. Yavy handles smart content extraction and returns data in clean JSON format optimized for LLM consumption.

The platform works through a four-step process: users provide their website URL, Yavy crawls and extracts meaningful content from every page, transforms the content into a searchable knowledge base, and serves it via the MCP standard. This allows AI assistants to query content directly and receive structured, reliable responses.

Benefits include eliminating AI hallucinations by providing real answers from actual content, enabling AI tools to access up-to-date information automatically as websites change, and requiring zero maintenance once configured. Use cases include building AI knowledge bases with clean structured content, powering customer support bots with entire manuals that stay current, and monitoring competitor websites for updates and changes.

The product targets builders creating chatbots or knowledge systems, developers working with AI tools like Claude and Cursor, and businesses needing to provide accurate information to AI assistants. It integrates with MCP-compatible clients and supports various content sources including documentation sites, blogs, knowledge bases, and any website with a sitemap.xml.