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.
Provides semantic code search and retrieval capabilities for AI agents, enabling them to query codebases using natural language with automatic learning, hybrid search, and intelligent chunking of functions and classes.
Enables AI agents and IDEs to ingest and search code repositories using hybrid retrieval (dense + sparse) with exact line-level citations for precise code analysis.
Semantic search over local source repositories and forum archives, exposing tools to list sources, search code, read code, and search forum discussions.
Enables code intelligence through semantic, structural, graph, and text search across indexed repositories, allowing AI agents to quickly locate the exact code they need.
Gives coding agents a memory of codebases by searching repositories using semantic similarity and structural call/import graphs, enabling reuse of proven patterns and reducing token usage.