Understand-Anything

Understand-Anything turns any codebase, knowledge base, or set of docs into an interactive knowledge graph you can search, click through, and ask questions about. It maps out components, relationships, and data flows so you can actually see how a system fits together instead of grep-ing your way through it.

It runs as a multi-agent pipeline on top of your AI coding setup. Tree-sitter handles the deterministic parsing, then LLMs do the semantic analysis. Built primarily for Claude Code, it also works with Cursor, VS Code with Copilot, Codex and more than a dozen other agent harnesses. MIT licensed, nothing to host. Graphs commit to your repo as JSON, and a standalone viewer lets teammates open them with just Node, no LLM or API key.

Solo devs onboarding to a messy codebase get the biggest win. Small teams use it to document tribal knowledge that lives in someone's head. Large teams probably already have wikis and ADRs, but the graph can still surface dependencies the docs missed.

The catch: graph quality tracks codebase quality. Spaghetti in produces spaghetti out, and circular dependencies render as a hairball. You also pay for the LLM tokens, and large monorepos can run up a real bill on the first pass.