Provides efficient code navigation and graph-based analysis for AI agents, enabling symbol resolution, callers, implementations, and type schemas with minimal token usage.
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.
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.
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 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.