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To understand a new codebase fast, build a graph of it first, then read the code in the order the graph suggests. Graphify turns a repository into a knowledge graph of files, functions, classes and the calls between them. In 30 minutes you go from git clone to a list of the code that matters most, a wiki you can browse, and answers that point at real lines.

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What you’ll build

  • A graphify-out/ folder with graph.json, GRAPH_REPORT.md and graph.html.
  • A ranked list of the hub functions everyone else depends on.
  • A Markdown wiki with one article per community of related code.
  • A habit: ask the graph before you grep.
This recipe uses the open-source Graphify-Labs/graphify repository as the “new” codebase. Swap in your own.

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Setup

You need Python 3.10 or later and uv.
The package is graphifyy. The command it installs is graphify.

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Step 1: Build the graph

extract --code-only parses source with tree-sitter and needs no LLM or API key. On this repository it took about 26 seconds:
cluster-only writes the report and the HTML view from that graph. --no-label skips LLM community names, so communities show as numbers.

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Step 2: Read the report

Open graphify-out/GRAPH_REPORT.md. The top tells you how much to trust the graph:
EXTRACTED edges come straight from the syntax tree. INFERRED edges were resolved by heuristics and carry a confidence score. The commit line tells you whether the graph matches your checkout.

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Step 3: Find the hub nodes

These are the functions to read first. Most of the codebase calls into them, so understanding them explains a large share of everything else.

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Step 4: Explain one node

Arrows show direction: --> is what this node calls, <-- is what calls it. Every edge has a file and line, so you can jump straight to the source.

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Step 5: Ask questions

The answer is a list of nodes and edges, each with its source location. --budget caps the tokens returned. When the result is cut, Graphify says so and tells you the budget that would fit everything:

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Step 6: Export a wiki

This writes one article per community plus graphify-out/wiki/index.md (904 articles for this repository). Start at the index and open the communities that hold your god nodes.

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When it goes wrong

graphify explain says no node matches. Names are matched against labels like _rebuild_code(). If a name exists in several files, graphify path and similar commands list the candidates in path::symbol form, for example graphify/cli.py::dispatch_command(). Use that form. graph.html shows blobs instead of functions. Above 5,000 nodes the HTML view is aggregated by community. Use explain, query and the wiki for detail.

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Production patterns

  • Commit nothing yet. Add graphify-out/ to .gitignore while you explore. The shared team graph recipe covers committing it.
  • Give the graph to your agent. See Give Claude Code a graph of your monorepo.
  • Keep it fresh with graphify update . after you pull. It re-extracts code without an API cost.

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Complete example

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What you built

You have a graph of the repository, a ranked reading list, a wiki, and a way to ask questions that cite real lines. In Graphify, the hosted product, the same graph is built for you when you connect a repository, and your agent queries it over MCP.

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Next steps

Query the graph

Every way to ask the graph a question, with budgets and filters.

Plan a refactor

Use the same graph to see what a change reaches.

Try it in Graphify

We build and host the graph for you. Start with a 14-day Pro trial, then keep up to 3 repositories on Free. No card required.