Enables searching, reading, and navigating MkDocs documentation sites through MCP tools for keyword, semantic, or hybrid search, document browsing, and project metadata.
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 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.
Enables MCP-compatible clients to search and read local markdown documentation, allowing agents to retrieve relevant doc snippets or full files by path.
Provides tools for AI agents to search, browse, and retrieve the full documentation for the mcp-framework. It enables agents to access documentation sections and page content directly within MCP-compatible environments like Claude Code and Cursor.