Provides structural code intelligence via 26 MCP tools, enabling AI assistants to query code symbols, dependencies, and call graphs accurately without file-pasting.
Enables LLM agents to query a codebase's structural knowledge (symbols, imports, call graphs, etc.) via MCP, reducing tokens and improving correctness compared to raw file access.
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.
Generates a comprehensive context map of your codebase to reduce token usage for AI coding assistants. Provides 12 MCP tools for exploring project structure, dependencies, and generating wiki knowledge bases.