CodeGraph 31K⭐ — The AI Coding Assistant That Cuts Your Token Costs by Half

TL;DR: CodeGraph pre-indexes your codebase into a knowledge graph, so your AI coding agent gets exactly what it needs in one tool call instead of scanning 100 files. Average result: 52% cost reduction, 78% fewer tokens, 46% faster.

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The Problem

You're using Claude Code, Cursor, or Codex CLI. You ask it to fix a bug.

What happens next:

1. Agent reads the directory structure (1 call)
2. Agent opens your main file (1 call)
3. Agent reads imports, follows dependencies (5-10 calls)
4. Agent opens related files one by one (15-30 calls)
5. Only then does it understand the context enough to write code

That's 20-50 tool calls per task. On a 10,000-file codebase like VS Code, this is painfully slow and expensive.

That's where CodeGraph steps in.

What CodeGraph Does

Before your agent starts, CodeGraph pre-indexes your entire codebase into a SQLite-backed knowledge graph.

When the agent asks "what's related to this function?", CodeGraph returns:

• The entry point and all exported symbols
• Related code snippets
• Caller/caller relationships (influence analysis)

All in one single tool call. Not 20. Not 50. One.

The Numbers (Real Benchmarks)

Codebase	Files	Cost Saved	Token Saved	Speed
VS Code	10,000	26%	78%	52% faster
Excalidraw	640	52%	90%	73% faster
Alamofire	110	47%	89%	65% faster

Quick Start

# Install
npm install -g @colbymchenry/codegraph

# Init in your project folder
cd your-project
codegraph init -i

# Your AI agent now uses it automatically

Why I Like This Project

• 🎯 Does one thing (knowledge graph indexing)
• ✅ Does it well (proven 52-78% cost reduction)
• 🔌 Composable (works with any MCP-compatible agent)
• U0001fab6 Lightweight (SQLite, runs in background)

Final Thought

If you're using any AI coding agent on a codebase larger than 100 files, try CodeGraph. The ROI is instant — reduce token costs by 50%+ starting from your first task.