Provides containerized deployment of Neo4j database for easier setup and configuration
Clones repositories for code analysis and scanning
Parses JavaScript projects to extract code structure, relationships, and metrics for analysis
Builds a comprehensive graph database of code structure, enabling storage and analysis of classes, methods, relationships, and dependencies
Parses Python projects to extract code structure, relationships, and metrics for analysis
Parses TypeScript projects to extract code structure, relationships, and metrics for analysis
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.
This server cannot be installed
hybrid server
The server is able to function both locally and remotely, depending on the configuration or use case.
An MCP server that transforms codebases into knowledge graphs using Neo4J, enabling AI assistants to understand code structure, relationships, and metrics for more context-aware assistance.
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