Provides persistent architectural memory and structural cognition for AI coding agents, enabling efficient orientation, graph-aware context, and drift detection across codebase evolution.
Provides AI coding assistants with deep, semantic understanding of local codebases via AST-aware chunking, cross-repo symbol graphs, and architectural memory, enabling context-aware code search and dependency tracing.
Provides AI coding agents with persistent architectural memory of codebases, enabling impact analysis, test generation, and code generation with reduced token usage.
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.
Turn any codebase into an AI-readable neural map — with proof. Every claim linked to code anchors (line + SHA-256 hash), every context window optimized with greedy token budgeting, every session protected by drift detection. Tree-sitter indexing across 11 languages, cross-session learning, AI enrichment, and 28 MCP tools. Zero config — just connect and your AI agent remembers everything.