Enables searching, reading, and navigating MkDocs documentation sites through MCP tools for keyword, semantic, or hybrid search, document browsing, and project metadata.
Provides RAG (Retrieval Augmented Generation) access to technical documentation through MCP, enabling LLMs to search and retrieve relevant documentation on-demand.
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.
Enables MCP clients to retrieve authoritative AI Square documentation, API references, SDK examples, guides, and troubleshooting information through citation-safe hybrid search and static resources.