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.
Supercharges AI coding agents with a pre-indexed semantic code graph, enabling instant symbol relationships, impact analysis, and context retrieval across 20+ languages.
Indexes a codebase into a symbol-level graph and exposes tools for finding symbols, querying relationships, and assessing impact, letting AI coding agents answer structural questions in a single call within a token budget.
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.
Provides codebase indexing and retrieval tools that give AI agents token-efficient, query-relevant context packages (symbols, imports, and dependencies) instead of scanning entire repositories.
