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The context engine for AI coding agents - reduce tokens by 50-70%

Project description

CodeNexus AI

The context engine for AI coding agents

License: MIT Python 3.10+ PyPI

English | 한국어


What is CodeNexus?

CodeNexus is a local-first context engine that helps AI coding agents understand your codebase better. It builds a live dependency graph of your code and serves only the relevant context to AI agents, reducing token usage by 50-70% while improving code quality.

Key Features

  • Local-first: Your code never leaves your machine
  • Token reduction: Save 50-70% on AI API costs
  • Multi-language: Python, JavaScript, TypeScript support
  • MCP compatible: Works with Claude Code, Cursor, and other AI agents
  • Fast indexing: SQLite-based dependency graph

Quick Start

Installation

pip install codenexus-ai

Basic Usage

# Index your project
codenexus index

# Search for context
codenexus search "authentication middleware"

# Run context pipeline
codenexus pipeline "fix login bug"

# Check index status
codenexus status

How It Works

Your Codebase
     ↓
[CodeNexus Indexer]
     ↓
┌─────────────────────────────────────┐
│  Dependency Graph (SQLite + FTS5)   │
│  - Functions, Classes, Imports      │
│  - Call relationships               │
│  - Type information                 │
└─────────────────────────────────────┘
     ↓
[Context Capsule Generator]
     ↓
┌─────────────────────────────────────┐
│  Optimized Context for AI Agent     │
│  - Pivot files: Full source         │
│  - Supporting: Skeleton only        │
│  - Token budget: Respected          │
└─────────────────────────────────────┘
     ↓
AI Agent (Claude Code, Cursor, etc.)

Claude Code Integration

Add to your ~/.claude.json:

{
  "mcpServers": {
    "codenexus": {
      "command": "codenexus",
      "args": ["serve", "-w", "/path/to/your/project"]
    }
  }
}

Supported Languages

Language Status
Python ✅ Full support
JavaScript ✅ Full support
TypeScript ✅ Full support
Go ✅ Full support
Rust ✅ Full support
Java ✅ Full support
C# ✅ Full support

Token Savings Example

Before CodeNexus:

8,247 tokens per query

After CodeNexus:

2,140 tokens per query (74% reduction)

Roadmap

  • Tree-sitter integration for better parsing
  • Graph centrality (PageRank) for better ranking
  • Local LLM support for additional savings
  • Multi-repo workspace support
  • VS Code extension

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

  1. Fork the repository
  2. Create your feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.


Acknowledgments

  • Inspired by vexp - The original context engine
  • Built with Python, SQLite, and MCP
  • Thanks to all contributors

Support

If you find CodeNexus useful, consider supporting the project:

Ko-fi GitHub Sponsors


Connect your code. Empower your AI.

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