Enables AI coding assistants to semantically search and retrieve relevant code patterns, documentation, and implementations from a codebase via MCP tools.
Enables AI agents to access a codebase context, select relevant files, and route queries to the appropriate AI model based on complexity, all through an MCP interface.
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.
Enables AI agents to search code by meaning, explore codebase structure, store and query knowledge with temporal facts, and read source code through a set of MCP tools.