What is Coderag

CodeRAG is an MCP Server designed for Neo4J-based Graph Retrieval-Augmented Generation (GraphRAG) specifically for code projects. It transforms codebases into intelligent knowledge graphs, enabling AI assistants to gain deeper insights into the code structure.

Use cases

Use cases for CodeRAG include enhancing code reviews with AI assistance, helping new developers understand complex projects, identifying code smells during refactoring, generating insights for documentation, and mapping complex inherited code structures.

How to use

To use CodeRAG, clone the repository from GitHub, install the necessary dependencies, and set up a Neo4J database. Follow the quick start guide for detailed instructions on installation and setup.

Key features

Key features of CodeRAG include smart code scanning to analyze codebases, quality insights through industry-standard metrics, seamless AI integration via the Model Context Protocol (MCP), and architecture analysis for visualizing complex code relationships.

Where to use

CodeRAG is ideal for software development environments, particularly in code reviews, onboarding new team members, refactoring existing code, generating documentation, and analyzing legacy codebases.

CodeRAG - Enterprise Code Intelligence Platform

Advanced graph-based code analysis for AI-assisted software development

CodeRAG is a professional code intelligence platform that transforms complex software projects into searchable knowledge graphs. By mapping code structures, dependencies, and relationships, it enables AI development tools to provide contextually accurate assistance for enterprise-scale codebases.

What CodeRAG Does

CodeRAG creates a comprehensive graph database representation of your codebase using Neo4J, enabling sophisticated analysis and AI-powered insights:

• Automated Code Analysis - Scans and maps classes, methods, interfaces, dependencies, and architectural relationships across multiple programming languages
• Remote Repository Analysis - Directly analyze any GitHub, GitLab, or Bitbucket repository without local cloning, supporting both public and private repositories with secure authentication
• Intelligent Language Detection - Automatically identifies project languages, frameworks, and build configurations from metadata and build files
• Quality Assessment - Calculates industry-standard software metrics (CK metrics, package coupling, architectural patterns) to identify technical debt and improvement opportunities
• Semantic Code Search - Enables natural language queries to find code by functionality rather than syntax
• Multi-Project Management - Supports enterprise environments with multiple codebases, providing unified analysis and cross-project insights

Who Should Use CodeRAG

Enterprise Development Teams

• Large-scale projects with complex architectures requiring deep code understanding
• Legacy system maintenance where comprehensive codebase mapping is essential
• Code quality initiatives needing objective metrics and architectural analysis

AI-Assisted Development

• Development teams using AI coding assistants (Claude Code, GitHub Copilot, Cursor, Windsurf) who need enhanced contextual awareness
• Code review processes requiring comprehensive understanding of change impacts
• Architectural decision-making supported by data-driven insights

Software Engineering Leadership

• Technical leads managing code quality and architectural compliance
• Engineering managers tracking technical debt and team productivity
• Architects designing and maintaining system boundaries and dependencies

Key Use Cases

Code Review Enhancement

Provide AI assistants with comprehensive codebase context, enabling more accurate suggestions and impact analysis during code reviews.

Onboarding Acceleration

Help new team members quickly understand complex codebases through interactive exploration and relationship mapping.

Technical Debt Management

Identify architectural issues, code smells, and coupling problems with objective metrics and actionable insights.

Legacy System Modernization

Map existing system architectures and dependencies to inform refactoring strategies and modernization planning.

Architectural Compliance

Monitor adherence to architectural principles and detect violations or degradation over time.

Supported Technologies

Programming Languages

• TypeScript and JavaScript - Full ES6+ support with framework detection
• Java - Comprehensive analysis including Spring Boot ecosystem
• Python - Complete support with framework identification
• C# (planned) - .NET ecosystem support in development

Enterprise Frameworks

• Spring Boot, Spring Framework - Java enterprise applications
• React, Angular, Vue.js - Modern frontend frameworks
• NestJS, Express - Node.js backend frameworks
• Django, FastAPI - Python web frameworks

Getting Started

Ready to enhance your development workflow with intelligent code analysis? Our comprehensive User Guide provides everything you need to set up and integrate CodeRAG with your development environment.

Enterprise Features

Multi-Project Management

• Project Isolation - Separate analysis for different codebases with unified management
• Cross-Project Analysis - Compare metrics and patterns across multiple projects
• Remote Repository Support - Scan public and private repositories from GitHub, GitLab, and Bitbucket directly
• Bulk Operations - Efficient scanning and analysis of multiple repositories

Quality Metrics

• CK Metrics Suite - Weighted Methods per Class, Coupling Between Objects, Response for Class
• Package Metrics - Afferent/Efferent Coupling, Instability, Abstractness
• Architectural Analysis - Circular dependency detection, design pattern identification

Advanced Search Capabilities

• Semantic Search - Natural language queries powered by AI embeddings
• Relationship Mapping - Trace dependencies, inheritance hierarchies, and method calls
• Pattern Detection - Identify design patterns and architectural structures

Documentation

Getting Started

• Installation & Setup Guide - Comprehensive setup instructions
• AI Integration Guide - Connect to Claude Code, Cursor, Windsurf, and other AI tools
• User Guide - Complete feature overview and workflows

Advanced Usage

• Scanner Usage - Detailed scanning options and project analysis
• Quality Metrics - Understanding and interpreting code quality measurements
• Multi-Project Management - Enterprise-scale project organization
• Semantic Search - Natural language code discovery

Reference

• Available Tools - Complete API reference for all 23 analysis tools
• Troubleshooting - Common issues and solutions

Professional Support

CodeRAG is designed for professional software development environments. The platform provides:

• Comprehensive Documentation - Detailed guides for setup, integration, and advanced usage
• Enterprise Architecture - Scalable design supporting large codebases and multiple projects
• Quality Assurance - Extensive test suite with 402+ tests ensuring reliability
• Open Source - MIT licensed with transparent development and community contributions

Contributing

We welcome contributions from the software development community. Please review our contributing guidelines and submit pull requests to help improve CodeRAG’s capabilities.

License

MIT License - see LICENSE for complete terms.

Ready to enhance your AI-assisted development workflow? Start with our Installation & Setup Guide to begin analyzing your codebase in minutes.