Enables AI assistants to access and search MkDocs documentation through tools for full-text search, page navigation, and code block extraction. It serves documentation pages as readable resources and provides structural outlines to help LLMs navigate documentation content.
Enables searching, reading, and navigating MkDocs documentation sites through MCP tools for keyword, semantic, or hybrid search, document browsing, and project metadata.
Enables Claude and other LLMs to search through any published MkDocs documentation site using the Lunr.js search engine, allowing the AI to find and summarize relevant documentation for users.
Enables interaction with MkDocs documentation through the MCP protocol, allowing AI assistants to read, search, and retrieve documentation content from MkDocs projects.
Enables AI agents to interact with MkDocs documentation through intelligent search (keyword, vector, and hybrid), document retrieval, and automatic indexing. Automatically detects and launches MkDocs projects for seamless documentation querying.
Provides AI assistants access to live Material Design 3 documentation including Foundations, Styles, and Components, returning official content as Markdown.
