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.
Enables AI coding agents to perform surgical code analysis, semantic memory, and quality enforcement via 18 specialized MCP tools, with a real-time analytics dashboard.
Provides AI coding agents with five intelligence layers (dependency graph, git history, documentation, architectural decisions, code health) via nine MCP tools, enabling deep codebase understanding and reducing exploration cost.
Provides 13 MCP tools for codebase analysis, wiki generation, and knowledge mapping, enabling AI assistants to understand project structure and context efficiently.
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.