Indexes local Python code into a Neo4j graph database to provide AI assistants with deep code understanding and relationship analysis. Enables querying code structure, dependencies, and impact analysis through natural language interactions.
Enables querying a Neo4j knowledge graph built from Git repositories and relational database schemas via MCP, with tools for schema inspection, Cypher queries, and searching code and database entities.
Provides a graph-based code analysis to coding agents, enabling tools to trace call dependencies, assess change impact, and identify hotspots using tree-sitter and Neo4j.
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.
Generates and queries a graph representation of a codebase to identify entities and their relationships, such as function calls and inheritance. It supports multiple languages including Python, JavaScript, and Rust to help users navigate and understand complex code structures.
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.
