Enables crawling and extracting clean content from documentation websites with optional LLM-powered analysis for intelligent summaries, code example extraction, and content classification.
Auto-discovers llms.txt documentation from project dependencies and exposes it to AI coding agents via MCP, enabling agents to read first-party docs without scraping or guessing.
Enables AI agents to search, fetch, and clean live documentation from LangChain, LlamaIndex, and OpenAI via Model Context Protocol, with token-optimized extraction.
Enables AI agents to check whether a public website is crawlable, understandable, and ready for AI search workflows through local-only audits of robots.txt, sitemaps, metadata, and llms.txt.
Enables AI agents to scan any website for agent-readiness and generate the necessary artifacts (llms.txt, WebMCP scaffold, structured data) to make it agent-ready.