Your first knowledge graph - Graphify
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Graphify turns a repository into a graph of its functions, classes, imports, and relationships. Your assistant can query that graph instead of repeatedly scanning the same files. This quickstart uses the open-source engine on your machine. You need Python 3.10 or later and a supported coding assistant. For the hosted product, see Graphify Cloud.
If you are an agent, read Notes for agents before these steps.
1

Install the CLI

Stay on one tab. The version check is the same either way.
graphify --version prints the version you installed. The latest release is on PyPI and in the changelog. The package is graphifyy, with two y’s. The command is graphify. A virtual environment install is on Installation.
2

Connect your assistant

This installs the Graphify skill for a detected assistant. To choose one explicitly:
See all integrations for your assistant’s setup.
3

Map a repository

Open a repository in your assistant, then enter this in its chat:
In Codex, select the Graphify skill with $graphify and ask it to map the current repository. This is an assistant instruction, not a shell command.Code is parsed locally. If the repository includes documents or media, the skill can use your assistant’s model for semantic extraction. For an explicit code-only run, use the local CLI workflow.
4

Inspect the output

Open graph.html in your browser. Click a node to inspect its connections, or start with the report for a tour of the architecture.
5

Ask a question

From a terminal at the repository root:
Use names from your graph to investigate further:
The names above are placeholders. A path only exists if those nodes and connecting edges exist in your project.

Take the full tutorial

Build a small example and follow a real relationship.

Give your agent MCP tools

Expose the graph as structured tools in your editor.
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