Java/Kotlin Source Graph RAG

Example Use Cases

• 1

  Query and understand Java/Kotlin codebases at both compiled and source code levels.

• 2

  Generate hierarchical, dependency-aware summaries of code components using LLMs.

• 3

  Interact with a Neo4j graph representing software structure and semantics via natural language.

Description

This MCP server transforms a jQAssistant-generated Neo4j graph of Java/Kotlin compiled artifacts into a semantically rich knowledge graph by linking compiled code to source code and generating hierarchical, context-aware summaries using LLMs. It enables AI agents and developers to query and gain deep insights into software architecture, behavior, and design. The server provides tools to interact with the enriched graph via natural language, supporting advanced code analysis and AI-driven workflows.