Yavy transforms websites into AI-searchable knowledge bases by converting web content into structured data accessible through the Model Context Protocol (MCP). The platform eliminates AI hallucinations by providing real answers from actual content rather than generating made-up information.

Key features include semantic search using AI-powered vector embeddings that find relevant content based on meaning rather than just keywords. The platform offers live syncing with updates propagating in milliseconds, automatic URL discovery and indexing with zero configuration required, and OAuth 2.1 authentication for secure access. Yavy provides reliable, structured JSON responses optimized for LLM consumption and supports both public sources and private content with flexible access controls.

The platform works through a four-step process: users input 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 through semantic search capabilities that understand concepts rather than just matching keywords.

Benefits include eliminating the need for copy-pasting documentation into chat interfaces, providing accurate and up-to-date information to AI tools, and enabling real-time content monitoring. Use cases include building AI knowledge bases with clean structured content, powering customer support bots with entire manuals that stay current automatically, and monitoring competitor websites for updates and changes.

The product targets developers building chatbots or knowledge systems, businesses needing to provide accurate information to AI assistants, and teams requiring AI-searchable documentation. It integrates with MCP-compatible AI tools including Claude, Cursor, OpenAI, and Windsurf, with planned integrations for GitHub, GitLab, Notion, Confluence, Slack, Discord, and Microsoft Teams.