Enables AI agents to query and analyze code across multiple repositories through a unified knowledge graph, with tools for symbol search, impact analysis, and graph algorithms.
Enables AI coding agents to query a pre-built semantic knowledge graph of code, reducing token usage and tool calls. Supports 16 tools for code exploration, analysis, and context building.
Provides semantic codebase understanding via a graph, enabling AI agents to search, explore, and plan changes with whole-repo context in a single tool call.
Enables AI agents to perform hybrid code search, get explanations, analyze relations and impacts, retrieve context packs, and generate documentation across ~45 languages via 17 MCP tools, all powered by a local vector database and LLM.