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.
Transforms code repositories and development documentation into a queryable Neo4j knowledge graph, enabling AI assistants to perform intelligent code analysis, dependency mapping, impact assessment, and automated documentation generation across 15+ programming languages.
Provides a dependency graph of any local repository with tools for change impact, transitive dependents, health audits, and more, enabling AI coding agents to see structure and refactor safely.
Provides efficient code navigation and graph-based analysis for AI agents, enabling symbol resolution, callers, implementations, and type schemas with minimal token usage.
Enables AI coding agents to query a pre-built semantic knowledge graph of code, reducing token usage and tool calls. Supports 16 tools for code exploration, analysis, and context building.