Code graph context engine that parses codebases with tree-sitter (170+ languages), builds structural dependency graphs, and provides 24 MCP tools for code intelligence. One prepare_context call gives your AI agent the right files for any task. Includes focus, blast radius, hotspots, dead code detection, and hybrid search.
Provides code intelligence for AI coding agents by indexing repositories into a hybrid knowledge graph, enabling agents to query dependencies, impact, and context through 28 MCP tools.
Local-first codebase context engine that parses code into a ranked dependency graph and serves it to AI tools via MCP for deep structural understanding.
Enterprise-grade (40m+ lines) codebase intelligence in a zero-setup, private and local MCP: managed indexing, hybrid semantic search, polyglot code dependency graphs, and DB/API/infra knowledge. Benchmark: 61% less tokens, 84% fewer calls, 37x faster than standard AI grep.
