head to head · open source

graphify vs headroom

graphify has 118,991 GitHub stars, 11,505 forks, 1,350 open issues and last shipped 2 days ago. headroom has 72,745 stars, 5,589 forks, 643 open issues and last shipped yesterday. graphify leads on adoption by 64% (118,991 vs 72,745 stars). graphify is written in Python under Apache-2.0; headroom is written in Python under Apache-2.0. graphify has attracted 10% as many forks as stars, headroom 8%. headroom was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 2 topic tags (claude-code, cursor), so they are genuine substitutes rather than adjacent tools.

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 headroom ★ 73K category AI & Machine Learning

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Side by side

graphify headroom
GitHub stars ★ 119K ★ 73K
License Apache-2.0 Apache-2.0
Written in Python Python
Last push 2026-09-16 2026-09-17
Forks ⑂ 12K ⑂ 5.6K
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 headroom if

  • You want the headroom feature set and don't need the biggest community
  • You prefer the Apache-2.0 license terms
  • Your stack matches Python
  • You evaluated both and headroom fits your workflow better

full headroom 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 headroom

Headroom is an Apache 2.0 Python library, local proxy, agent wrapper and MCP server that compresses tool outputs, logs, files, RAG chunks and conversation history before they reach an LLM, and it is built for developers running AI coding agents or LLM applications who want to cut token usage without changing the answers they get.

read the full headroom overview →

More in AI & Machine Learning

OpenClaw ★ 390K Hermes Agent ★ 246K Ollama ★ 181K Dify ★ 156K Open WebUI ★ 152K langchain ★ 147K

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dify vs graphify langchain vs graphify ponytail vs graphify dify vs langchain dify vs ponytail langchain vs ponytail dify vs claude-mem dify vs ragflow openclaw vs hermes-agent openclaw vs open-webui openclaw vs lobechat openclaw vs anythingllm openclaw vs cherry-studio openclaw vs nanobot openclaw vs jan openclaw vs librechat ollama vs llama-cpp ollama vs vllm ollama vs gpt4all ollama vs llama-index ollama vs localai llama-cpp vs vllm ollama vs pageindex ollama vs langfuse

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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 Mem0 graphify vs daily_stock_analysis graphify vs LiteLLM graphify vs Multica

Frequently asked questions

Is graphify or headroom more popular?

graphify has 118,991 GitHub stars and headroom has 72,745. graphify has the larger community by that measure.

Are graphify and headroom free?

Both are open source. graphify is licensed under Apache-2.0 and headroom under Apache-2.0. Neither carries a licence fee.

What is the difference between graphify and headroom?

graphify is written in Python and headroom in Python. 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 headroom?

Choose graphify if you want the larger community (118,991 stars) or its Apache-2.0 licence terms. Choose headroom if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.