How to Build a Local 3D Codebase Knowledge Graph and Sync LLM Context Offline

A developer introduced Graphify Companion, an open-source tool that builds a local 3D codebase knowledge graph and syncs LLM context offline. The tool combines Node.js for MCP Server Transport and Python for AST/graph parsing, enabling AI assistants to understand structural code relationships like function calls and imports. The project is available on GitHub and works with LM Studio's local server.

Introduction: Why context windows are expensive and why static folder indexing fails to capture structural relationships like function calls or imports . The Solution: Introducing Graphify Companion. How the Architecture Works: Detail the combination of Node.js for the MCP Server Transport and Python for AST/graph parsing. Step-by-Step Setup: Cloning the repo https://github.com/sreekanthap89/Graphify-Companion1 https://github.com/sreekanthap89/Graphify-Companion1 . Running install.ps1 to configure Python .venv and Git Hooks. Starting LM Studio's local server. Copy-pasting the JSON configuration into LM Studio. Prompting Guide: Teach readers how to write prompts that force the AI to use graph tools query graph vs. read file . Conclusion & Source: Invite readers to star the GitHub repository.