workflowstacks
mcp-server

Graphify

Turn any codebase, with its docs, SQL schemas, configs, and PDFs, into a queryable knowledge graph. A /graphify skill for Claude Code, Cursor, Codex, and Gemini CLI: local deterministic AST parsing…
113,199 stars11,018 forksPythonUpdated 8/30/2026100% free · open source
What it does

It builds a deterministic, query‑able knowledge graph of your entire codebase—including source files, docs, SQL schemas, configs and PDFs—so AI assistants can answer exact, code‑level questions without using a vector store.

When to use it
  • •You need an LLM to answer precise “where is X defined?” or “which endpoints touch this table?” questions across a large monorepo.
  • •Your team wants to embed a live code‑graph into Claude Code, Cursor, Codex or Gemini prompts for real‑time debugging or impact analysis.
  • •You must keep the graph up‑to‑date automatically as code changes, without relying on fuzzy vector similarity.
Ready-to-paste prompt
In Claude Code, you can now write:
```
@graphify "Give me all Python functions that write to the `orders` table and are referenced in the API docs. Return the file path and line numbers."
```
Heads up: Graphify requires Python 3.10+ **and** GraphViz installed on the host (e.g., `brew install graphviz` or `apt-get install graphviz`); without GraphViz the AST‑edge visualizer and PDF parsing will fail.
Saves to your device
Use with Claude
New

Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.

✅ Light setup

Installs with a command or two; your AI agent can do it for you.

Try it instantly — no install
Claude Code
mkdir -p ~/.claude/skills/graphify && curl -fsSL https://workflowstacks.com/api/skills/graphify/claude-skill -o ~/.claude/skills/graphify/SKILL.md
Open in another AI app

Opens the app with this repo with the prompt ready to go — no copy-paste needed.

Connect the whole catalog (MCP)
claude mcp add --transport http workflowstacks https://workflowstacks.com/api/mcp

Adds a WorkflowStacks connector to Claude Code: search and load any skill here by chatting.

How Graphify works
Codeflow
Free to inspect

Graphify is a very large Python project (~64k lines across 104 code files, plus 315 test files). Setup is light: installs like a normal app. Reading the code is optional. Last commit this month, Apache-2.0 license, has a test suite.

Size
Very large codebase
~64k lines · 104 code files · days to read — use, don't read
Setup
One-command install
Installs like a normal app. Reading the code is optional.
Runs on
Python · Docker
No API keys detected
Python 100%
Where to start reading
  1. 1
    README.md
    Start here — what it does and how to install it
  2. 2
    AGENTS.md
    The instructions the AI actually follows
  3. 3
    graphify/cli.py
    Where the program starts running
  4. 4
    pyproject.toml
    Dependencies and the commands it exposes
  5. 5
    graphify/__init__.py
    Inside graphify/ — the main logic begins here
What's in each folder
graphify/Core code — the actual logic221 files
docs/Documentation41 files
tools/Helper scripts174 files
worked/Folder36 files
scripts/Helper scripts1 files
tests/Tests — proof it works364 files
.github/CI / automation (GitHub Actions)4 files
READMEHas testsDocumentedCI checksDocker readyApache-2.0 licenseUpdated this month
Quick Actions
Details
Creator
Graphify-Labs
Language
Python
Category
mcp-server
Published
4/3/2026

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