headroom vs screenpipe
Side-by-side comparison of two AI agent tools
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headroomopen-source
Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 20% fewer tokens for coding agents, 60-95% fewer tokens for JSON, same answers. Li
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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 | 74.2k | 21.8k |
| Star velocity /mo | 6.2k | 1.8k |
| Commits (90d) | 1.2k | 2.8k |
| Releases (6m) | 10 | 10 |
| Overall score | 0.91550535160014 | 0.8727681175444836 |
FAQ
- Which is more popular, headroom or screenpipe?
- headroom has more GitHub stars (74,176 vs 21,783).
- Which is more actively developed, headroom or screenpipe?
- screenpipe had more commits in the last 90 days (2,832 vs 1,163).
- 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.