Enables LLM agents to efficiently understand and navigate a codebase by providing semantic search over symbols and a reference graph, replacing expensive grep/glob calls with structured tools like definition lookup, caller/callee queries, and change-impact analysis.
Enables semantic code search across multiple repositories using natural language queries. Provides intelligent code discovery, symbol lookups, and cross-repo dependency analysis for AI coding agents.
Enables token-efficient semantic search and analysis over any directory of files through hybrid search, directory overview, structural analysis, and dependency graphs.
Enables semantic code search across multiple repositories using AST-aware chunking and relationship tracking. Supports local LLM embeddings, real-time indexing, and cross-codebase dependency analysis through vector and graph databases.
Enables fast code analysis and navigation through hybrid semantic search, graph-based relationship tracking, and structure exploration across multiple programming languages with optimized indexing for large codebases.
