Enables AI agents to query and analyze code across multiple repositories through a unified knowledge graph, with tools for symbol search, impact analysis, and graph algorithms.
Enables querying and analyzing code relationships by building a lightweight graph of TypeScript and Python symbols. Supports symbol lookup, reference tracking, impact analysis from diffs, and code snippet retrieval through natural language.
Provides semantic code search and code insights via a knowledge graph, enabling AI to understand, navigate, and modify complex projects with deep dependency and architecture analysis.
Enables building and querying code knowledge graphs for project analysis, with tools for exploring code relationships, managing workflows, and automating development tasks. Integrates with Git and GitHub for branch management and pull request creation.
A graph-powered code intelligence engine that indexes codebases into a structural knowledge graph to provide AI agents with deep context on function calls, types, and execution flows. It offers local, zero-dependency tools for hybrid search, impact analysis, and dead code detection across Python, JavaScript, and TypeScript projects.
Combines a knowledge graph with RAG (Retrieval-Augmented Generation) capabilities for semantic code indexing and search. Enables creating entity relationships, managing observations, and performing semantic searches across indexed codebases.