CodeGraphContext

Indexes codebases into a Neo4j graph database to enable sophisticated code analysis including function call relationships, class hierarchies, dead code detection, and dependency tracking through real-time file monitoring and direct Cypher queries.

This MCP server provides AI-powered code analysis by indexing local Python codebases into a Neo4j graph database, enabling sophisticated relationship queries and context discovery for development workflows. Built by Shashank Shekhar Singh using Python with Neo4j, watchdog for file monitoring, and Typer for CLI interaction, it offers 12 specialized tools including code indexing with background job processing, real-time file watching for active projects, function call relationship analysis, class hierarchy exploration, dead code detection, and direct Cypher query execution. The implementation features cyclomatic complexity calculation, full-text search across code elements, import dependency tracking, and an interactive setup wizard that supports both local Neo4j installations and hosted AuraDB connections, making it valuable for developers who need programmatic access to code structure and relationships for refactoring, impact analysis, and codebase understanding tasks.