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Transforming AI Coding: Achieving 58% Cost Savings by Replacing File Reads with Dependency Graphs

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🔍 Revolutionizing AI Code Interaction! 🔍

Are you tired of watching AI tools process unnecessary code? I created an MCP server that pre-computes a dependency graph using tree-sitter, delivering only the essential code nodes to your AI agent. Here’s what I discovered:

  • Significant Improvements:

    • Cost per Task: Reduced from $0.78 to $0.33 (-58%)
    • Execution Duration: Cut from 170s to 132s (-22%)
    • Output Tokens: Decreased from 504 to 189 (-63%)
  • Task-Specific Savings:

    • Code Understanding: -57%
    • New Features: -53%
    • Refactoring: -48%
    • Bug Fixes: -29%

The innovative graph enhances performance by minimizing unnecessary context calls. It’s lightweight, local, and efficient—everything you need to optimize AI-driven coding!

💬 Curious about the tech behind this? Let’s connect and explore! Share your thoughts and experiences below!

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