Graphify: Instant Knowledge Graph for Claude Code/Antigravity (FREE)

Description

Claude Code / Antigravity + Graphify = Instant Knowledge Graph For business enquiries: [email protected] 🔗 My Resources: Use the below link and coupon code 'FUTURMINDS ' to get 10% DISCOUNT. Hostinger VPS : Start creating n8n workflows: ----------- Claude Code rebuilds your entire project understanding from scratch every session — re-reading the same files, burning tokens, and starting blind every time you open a new chat. Graphify fixes this: it maps your project once into a knowledge graph, and Claude reads that graph automatically at the start of every session instead of re-reading your files. In this tutorial, I break down exactly how Graphify works (three passes — zero tokens for code, one-time cost for docs), run a real 10-question test in two identical Claude Code sessions to measure the actual token savings, and walk through the full setup from scratch. I also break down what the "71.5x fewer tokens" benchmark actually measures — and when the savings are real for your project. ⏰ Timestamps: 0:00 Why Claude Code Reads Your Files Every Session 1:14 What Graphify Does for Claude Code 1:59 Graphify Architecture: 3 Passes Explained 3:37 Real Token Savings Test: 10 Questions 5:06 How to Install Graphify Step by Step 6:24 Graph Output and How to Update It 7:59 Real-World Impact + 71x Claim Debunked 9:36 Graphify for Research, Content, and Business Folders 🔑 Key Takeaways: • Run pip install graphifyy — double y (the single-y package on PyPI is a completely different tool) • Pass 1 (code parsing) runs entirely on your machine with zero token cost — only Pass 3 touches Claude's API, and only once • Graph overhead means the first 2-3 questions cost slightly more; savings compound after the crossover point • The 71.5x benchmark compares against pasting all files into context at once — a workflow almost nobody uses in real Claude Code sessions ❓ FAQ: Q: Does Graphify actually save tokens in Claude Code? A: Yes, but not 71x in a typical session. In a real 10-question Claude Code session on the browser-use project, Graphify used 113,000 tokens vs 120,000 without — about 7-8% savings. Savings compound with session length, project size, and mixed code+docs projects. Q: How do I install Graphify for Claude Code? A: Run pip install graphifyy (double y — the single-y package is a different tool), then graphify install to register the always-on hook, then /graphify inside your Claude Code session to build the graph. Full walkthrough at 5:06. Q: What is a knowledge graph in the context of Graphify? A: Graphify's knowledge graph is a map of nodes (functions, classes, documents, concepts) and edges (relationships like calls, imports, references), organized into neighborhoods. Claude reads a summary of this graph at the start of every session via a PreToolUse hook — replacing dozens of file reads with a single structured map. Q: Does Graphify work on non-code projects? A: Yes. Graphify works on any folder — research papers, meeting recordings, strategy documents, content vaults. Pass 1 (code parsing) is skipped on text-only projects, but Pass 3 still extracts concepts and builds a navigable graph from markdown, PDFs, and documents. 🔗 Resources & Links: - [LINK: Graphify GitHub Repository — install instructions and documentation] - [LINK: browser-use GitHub — the project used in this demo] - [LINK: FuturMinds Claude Code Tutorials Playlist] 📢 Subscribe to FuturMinds for weekly AI tool tutorials and automation guides — helping non-dev builders master AI systems. Whether you're looking for a complete Graphify setup guide, trying to reduce Claude Code token usage on a growing project, or want to understand how knowledge graphs improve AI coding sessions, this walkthrough covers everything from install to real benchmark analysis.