How to Build Graphify from Source: Complete Installation Guide

To build Graphify from source, clone the Graphify-Labs/graphify repository, install Python 3.10+, use uv to install the graphifyy package, and run graphify install to register the skill with your AI assistant.

Graphify is a Python-based knowledge-graph engine that constructs rich code graphs using tree-sitter grammars. Building Graphify from source gives you the CLI tool, semantic extraction capabilities, and the MCP server for programmatic access.

Prerequisites

Before building, ensure you have Python 3.10 or higher installed. Check your version with:

python --version

You also need a package manager that supports isolated tool environments. While pip or pipx work, the Graphify project recommends uv for faster builds and dependency resolution.

Install uv using the official installer:

curl -LsSf https://astral.sh/uv/install.sh | sh

Build Steps

Clone the Repository

Retrieve the source code from GitHub and navigate into the project directory:

git clone https://github.com/Graphify-Labs/graphify.git
cd graphify

The repository contains the core package under graphify/, configuration in pyproject.toml, and a container definition in Dockerfile.

Install the Graphify Package

Build and install the graphifyy package (note the package name uses a double "y"). This command compiles the tree-sitter grammars and places the graphify CLI on your PATH:

uv tool install graphifyy

If you prefer pipx or standard pip, use one of these alternatives:

# Using pipx

pipx install graphifyy

# Using pip (user install recommended)

pip install --user graphifyy

Register the Skill

After installation, register Graphify with your AI assistant so it can invoke the /graphify command. Choose between a global or project-scoped installation:

• Global install: graphify install
• Project-scoped install: graphify install --project

The registration process writes a skill definition (for example, to .claude/skills/graphify/SKILL.md) and outputs a git add hint for version control.

Verify the Build

Run a test build on the current directory to ensure everything works:

graphify .

This generates a graphify-out/ directory containing graph.html, GRAPH_REPORT.md, and graph.json. These artifacts confirm that the AST extraction in graphify/build.py and semantic clustering pipelines are functioning correctly.

Optional Build Configurations

Docker Build

For containerized deployments or CI pipelines, build the Docker image defined in the root Dockerfile:

docker build -t graphify .

The Dockerfile packages the CLI, all tree-sitter grammars, and dependencies into a reproducible environment.

Extra Language Backends

Customize your build by installing optional extras for additional file type support. Edit your install command to include specific dependency groups defined in pyproject.toml:

• PDF support: uv tool install "graphifyy[pdf]"
• Office documents: uv tool install "graphifyy[office]"
• Video/audio: uv tool install "graphifyy[media]"
• Neo4j export: uv tool install "graphifyy[neo4j]"

These extras pull in additional libraries for parsing non-code formats and exporting to external graph databases.

Verification and Testing

Validate your build by running the comprehensive test suite located in tests/:

uv run pytest -q

Alternatively, start the MCP server to programmatically access your generated graphs:

python -m graphify.serve graphify-out/graph.json

This launches a local server (STDIO or HTTP mode) that exposes the knowledge graph to compatible AI assistants.

Summary

• Build Graphify from source using Python 3.10+, the uv tool, and the graphifyy package from the Graphify-Labs/graphify repository.
• Core files include pyproject.toml for dependency management and Dockerfile for containerized builds.
• Registration via graphify install enables the /graphify command in your AI assistant.
• Optional extras add support for PDFs, Office files, and Neo4j exports through bracketed install options.
• Verification involves running pytest or generating a test graph with graphify . to confirm AST extraction and semantic analysis pipelines work.

Frequently Asked Questions

What Python version is required to build Graphify?

Graphify requires Python 3.10 or higher. This is specified in pyproject.toml and enforced during the build process to ensure compatibility with modern type hints and async features used in graphify/build.py and related modules.

Why is the package name graphifyy instead of graphify?

The PyPI package is named graphifyy (with two y's) to avoid naming conflicts, while the installed CLI command remains graphify (single y). When building from source, always use uv tool install graphifyy or pip install graphifyy to get the correct distribution.

Can I build Graphify without using uv?

Yes, though uv is recommended for its speed and isolation. Alternatives include pipx (pipx install graphifyy) for isolated CLI tools, or standard pip with a virtual environment. The Docker build method also requires no local Python package manager beyond Docker itself.

How do I enable support for PDF and Office documents?

Install the optional extras using bracket notation when running the install command: uv tool install "graphifyy[pdf]" for PDF parsing or uv tool install "graphifyy[office]" for Word and Excel files. These extras are defined in the [project.optional-dependencies] section of pyproject.toml and pull in specific parsing libraries.

{
  "mcpServers": {
    "instagit": {
      "command": "npx",
      "args": ["-y", "instagit@latest"]
    }
  }
}