Enables code intelligence through semantic, structural, graph, and text search across indexed repositories, allowing AI agents to quickly locate the exact code they need.
Enables AI coding agents to search, route, and read code across multiple repositories through a central semantic index, without needing to clone repositories locally.
Enables AI coding agents to query a semantic cross-repository code graph for symbols, references, callers, dependencies, and change impact across registered repositories.
Enables AI agents to semantically search and navigate code repositories using natural language, with support for multiple repos, incremental indexing, and no local install needed.
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 AST-aware chunking and relationship tracking. Supports local LLM embeddings, real-time indexing, and cross-codebase dependency analysis through vector and graph databases.