headroom vs screenpipe
Side-by-side comparison of two AI agent tools
Short answer
- headroom is growing faster: +1,515 GitHub stars in the last 30 days vs +210 for screenpipe.
- Pick headroom for: compresses tool outputs, logs, RAG chunks, files, and conversation history before they reach LLMs. Pick screenpipe for: yC (S26) | Open Computer History | Record your screen continuously locally and provide context to your agents.
From GitHub data refreshed daily.
h
headroomopen-source
Compresses tool outputs, logs, RAG chunks, files, and conversation history before they reach LLMs
s
screenpipeopen-source
YC (S26) | Open Computer History | Record your screen continuously locally and provide context to your agents (Claude, Codex, Openclaw, Hermes, Runner...)
Metrics
| headroom | screenpipe | |
|---|---|---|
| Stars | 74.3k | 21.8k |
| Star velocity /mo | 1.5k | 210 |
| Commits (90d) | 1.2k | 2.8k |
| Releases (6m) | 10 | 10 |
| Overall score | 0.8896326908220638 | 0.8133409649144364 |
FAQ
- Which is more popular, headroom or screenpipe?
- headroom has more GitHub stars (74,277 vs 21,797).
- Which is more actively developed, headroom or screenpipe?
- screenpipe had more commits in the last 90 days (2,791 vs 1,208).
- Should I use headroom or screenpipe?
- Compare their capabilities, limitations and "best for" notes above. Both are open source, so trying each on a small task is the fastest way to decide.