The context engine for AI coding agents - reduce tokens by 50-70%
Project description
CodeNexus AI
The context engine for AI coding agents
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.
- Fork the repository
- Create your feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - 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:
Connect your code. Empower your AI.
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