codenexus-ai 1.0.0

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

CodeNexus

The context engine for AI coding agents

English | 한국어

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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

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Quick Start

Installation

pip install codenexus

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

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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.)

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Claude Code Integration

Add to your ~/.claude.json:

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

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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

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Token Savings Example

Before CodeNexus:

8,247 tokens per query

After CodeNexus:

2,140 tokens per query (74% reduction)

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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

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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

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License

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

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Acknowledgments

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

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Support

If you find CodeNexus useful, consider supporting the project:

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Connect your code. Empower your AI.