head to head · open source

graphify vs PI-Desktop

graphify has 119,123 GitHub stars, 11,519 forks, 1,350 open issues and last shipped 3 days ago. PI-Desktop has 4,258 stars, 357 forks, 102 open issues and last shipped yesterday. graphify leads on adoption by 2,698% (119,123 vs 4,258 stars). graphify is written in Python under Apache-2.0; PI-Desktop is written in TypeScript under LGPL-3.0. graphify has attracted 10% as many forks as stars, PI-Desktop 8%. PI-Desktop was the more recently maintained of the two, and both are self-hostable with no licence fee.

Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.

graphify ★ 119K PI-Desktop ★ 4.3K category AI & Machine Learning

← all 13541 open source comparisons

Side by side

graphify PI-Desktop
GitHub stars ★ 119K ★ 4.3K
License Apache-2.0 LGPL-3.0
Written in Python TypeScript
Last push 2026-09-16 2026-09-18
Forks ⑂ 12K ⑂ 357
Self-hosting Yes Yes
Data ownership Your server Your server

pick graphify if

  • You weight community size — 119K stars and counting
  • You want the Apache-2.0 license terms
  • Your stack matches Python
  • You value the larger contributor base for long-term maintenance

full graphify profile →

pick PI-Desktop if

  • You want the PI-Desktop feature set and don't need the biggest community
  • You prefer the LGPL-3.0 license terms
  • Your stack matches TypeScript
  • You evaluated both and PI-Desktop fits your workflow better

full PI-Desktop profile →

About graphify

graphify is an Apache 2.0 Python CLI and /graphify skill that turns a whole project — code, docs, SQL schemas, configs, PDFs, images, and video — into a queryable knowledge graph, built for developers and AI agent users in Claude Code, Cursor, Codex, and Gemini CLI who want to query a codebase instead of grepping through files.

read the full graphify overview →

About PI-Desktop

PI Desktop is a local first desktop workspace for AI coding agents, built on an Electron shell with a Rust host core and the pi Agent Harness, extensible through user installable plugins, and aimed at developers who want agents working inside their own local projects against model providers they configure themselves.

read the full PI-Desktop overview →

More in AI & Machine Learning

OpenClaw ★ 390K Hermes Agent ★ 247K Ollama ★ 181K Dify ★ 156K Open WebUI ★ 152K langchain ★ 147K

Related comparisons

openclaw vs dify openclaw vs multica openclaw vs langgraph n8n vs dify dify vs langflow dify vs open-webui dify vs langchain dify vs ponytail openclaw vs hermes-agent openclaw vs opencode openclaw vs n8n openclaw vs open-webui openclaw vs lobechat openclaw vs anythingllm hermes-agent vs opencode hermes-agent vs n8n openclaw vs ollama ollama vs llama-cpp ollama vs vllm ollama vs gpt4all ollama vs llama-index ollama vs localai open-webui vs gpt4all llama-cpp vs vllm

More AI Development Platforms projects

Compare either of these against the rest of the AI Development Platforms field.

graphify vs Dify graphify vs langchain graphify vs ponytail graphify vs generative-ai-for-beginners graphify vs claude-mem graphify vs ragflow graphify vs PaddleOCR graphify vs Agent-Reach graphify vs headroom graphify vs Mem0 graphify vs daily_stock_analysis graphify vs LiteLLM

Frequently asked questions

Is graphify or PI-Desktop more popular?

graphify has 119,123 GitHub stars and PI-Desktop has 4,258. graphify has the larger community by that measure.

Are graphify and PI-Desktop free?

Both are open source. graphify is licensed under Apache-2.0 and PI-Desktop under LGPL-3.0. Neither carries a licence fee.

What is the difference between graphify and PI-Desktop?

graphify is written in Python and PI-Desktop in TypeScript. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.

Which should I choose, graphify or PI-Desktop?

Choose graphify if you want the larger community (119,123 stars) or its Apache-2.0 licence terms. Choose PI-Desktop if its feature set, stack or LGPL-3.0 licence fits better. Both are self-hostable.