context-mode vs headroom
headroom is much bigger: 78.4k stars against 33.0k. Over the days we have tracked them context-mode moved +68.5% and headroom +22.2%, so context-mode is growing faster right now.
They split the axes: context-mode leads on context depth, headroom on model freedom and setup ease.
Stars and commit dates come from our own daily tracking. The six axes are read off each project's documentation by our review pipeline, so they describe what a project says about itself, not what we measured in its code.
Where they stand today
Sandboxes large tool outputs and persistently indexes session events (SQLite FTS5 + BM25) so agents retrieve only relevant fragments, drastically shrinking context usage while preserving continuity across many MCP clients.
- Stars
- 33.0k
- Tracked growth
- +68.5%
- Maturity
- ●●●●●
- Last commit
- 9m ago
- Language
- TypeScript
- License
- NOASSERTION
- Cost to run
- Free, local install
Local-first, reversible context compression that both shrinks prompts and actively reduces model output tokens via a drop-in proxy and cross-agent memory.
- Stars
- 78.4k
- Tracked growth
- +22.2%
- Maturity
- ●●●●●
- Last commit
- 17h ago
- Language
- Python
- License
- Apache-2.0
- Cost to run
- Local software is free; LLM calls use your API key.
Six axes, head to head
Each axis runs 0 to 5. The label under a score is what that project's own docs claim, not a category average.
| Axis | context-mode | headroom |
|---|---|---|
Context depth How much of your codebase it sees before it answers: the open diff, the diff plus related files, or the whole repository. | ●●●●● Whole-repo analysis | ●●●●● Diff + related files |
Noise control How it keeps output volume down — severity thresholds, deduplication, incremental runs over new commits only. | ●●●●● BM25 & sandboxing | ●●●●● Dedup & shaping |
Customization How far it bends to your team: custom rules, prompts, style guides, per-path config. | ●●●●● Config files & hooks | ●●●●● Rich CLI & config |
Privacy Whether your code stays on your own infrastructure: fully local, self-hostable, or cloud API only. | ●●●●● Fully local | ●●●●● Self-hostable |
Model freedom Whether you can point it at any provider, or it is wired to one. | ●●●●● Multiple providers | ●●●●● Bring-your-key |
Setup ease What it takes to get a first useful run out of it. | ●●●●● Config + one command | ●●●●● One-command start |
Which one to pick
Pick context-mode if…
Context-efficient — drastically reduces context bloat and preserves session continuity across IDEs and CLIs via local MCP hooks and searchable session storage.
- Context depth: Whole-repo analysis (5/5 against 3/5)
Pick headroom if…
Easy setup — wrap agents or run a local proxy in one command to get large token savings, reversible originals, and shared memory across agents without code changes.
- Model freedom: Bring-your-key (5/5 against 3/5)
- Setup ease: One-command start (5/5 against 3/5)
What people want from each one
headroomlabs-ai/headroom
Hacker News: Headroom – The context compression layer for AI agents drew 3 points and 0 comments.
Questions people ask
Is context-mode better than headroom?
They split the axes: context-mode leads on context depth, headroom on model freedom and setup ease. context-mode is worth picking when context-efficient — drastically reduces context bloat and preserves session continuity across IDEs and CLIs via local MCP hooks and searchable session storage.
Which of context-mode and headroom keeps my code private?
context-mode: Fully local (5/5). headroom: Self-hostable (4/5).
What does each one cost to run?
context-mode: Free, local install. headroom: Local software is free; LLM calls use your API key..
Full profiles: mksglu/context-mode and headroomlabs-ai/headroom. Everything else in Memory & context.