Provides 13 MCP tools for codebase analysis, wiki generation, and knowledge mapping, enabling AI assistants to understand project structure and context efficiently.
Provides AI assistants with a structured, token-efficient map of a codebase's symbols, dependencies, and relationships via MCP tools like overview, query, and impact analysis.
Provides structural code intelligence via 26 MCP tools, enabling AI assistants to query code symbols, dependencies, and call graphs accurately without file-pasting.
Provides AI-powered architecture analysis and visualization of codebases, exposing 17 MCP tools for querying components, dependencies, and generating interactive diagrams.
Enables LLMs to explore codebases structurally via MCP tools for outlines, function sources, imports, complexity, git changes, and dead code detection, reducing token usage by avoiding raw file ingestion.