CodeGraphContext: Indexing Codebases into Graphs for AI-Powered Development

CodeGraphContext is an innovative MCP server and CLI toolkit designed to transform local code repositories into queryable graph databases. This enables AI assistants and developers to gain deep contextual understanding of codebases, facilitating advanced code analysis and navigation.

The tool supports two primary modes of operation:

1. CLI Toolkit Mode: Allows developers to index, analyze, and visualize codebases directly from the command line. Features include querying function callers and callees, detecting dead code, analyzing complexity, and generating interactive visualizations.

2. MCP Server Mode: Integrates with AI IDEs and assistants (like VS Code, Claude, Cursor, and others) to provide AI-powered natural language querying of code. This mode supports automatic code understanding, relationship analysis, and live updates.

CodeGraphContext supports 14 programming languages including Python, JavaScript, Java, C/C++, Rust, and more. It builds a comprehensive code graph by parsing functions, classes, methods, inheritance, and call relationships.

Multiple graph database backends are supported, including KùzuDB (default on Windows), FalkorDB Lite (typical on Unix), and Neo4j (for scalable enterprise use).

Key features: - Fast indexing using tree-sitter parsers - Live file watching for real-time graph updates - Pre-indexed bundles for popular repositories - Interactive, premium web-based graph visualizations - Natural language interaction examples for querying code structure and dependencies

This tool is valuable for static code analysis, impact analysis, debugging, and AI-assisted development workflows.

For developers and teams looking to enhance their code comprehension and AI integration, CodeGraphContext offers a powerful, flexible solution.

Learn more and get started at the official GitHub repository: https://github.com/CodeGraphContext/CodeGraphContext