claude-mem vs headroom

The two are close in size: 93.2k stars for claude-mem, 69.0k for headroom. Over the days we have tracked them claude-mem moved +6.6% and headroom +15.9%, so headroom is growing faster right now.

Neither one leads on the six capability axes, so the choice comes down to which of them fits the way you already work.

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

Claude-Mem pairs a Claude Code–focused persistent memory with progressive-disclosure search tools and a local worker/web UI to deliver token-efficient, session-persistent context.

Stars
93.2k
Tracked growth
+6.6%
Maturity
Last commit
5h ago
Language
JavaScript
License
Apache-2.0
Cost to run
Your API key for model calls; optional cloud backup to cmem.ai

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
69.0k
Tracked growth
+15.9%
Maturity
Last commit
6h ago
Language
Python
License
Apache-2.0
Cost to run
Local software is free; LLM calls use your API key.
0%+16%52 tracked days
thedotmack/claude-memheadroomlabs-ai/headroom

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.

Axisclaude-memheadroom
Context depth
How much of your codebase it sees before it answers: the open diff, the diff plus related files, or the whole repository.
Related files & memory
Diff + related files
Noise control
How it keeps output volume down — severity thresholds, deduplication, incremental runs over new commits only.
Configurable filters
Dedup & shaping
Customization
How far it bends to your team: custom rules, prompts, style guides, per-path config.
Config file & modes
Rich CLI & config
Privacy
Whether your code stays on your own infrastructure: fully local, self-hostable, or cloud API only.
Self-hostable (local worker)
Self-hostable
Model freedom
Whether you can point it at any provider, or it is wired to one.
Bring-your-key (many providers)
Bring-your-key
Setup ease
What it takes to get a first useful run out of it.
One-command install
One-command start

Which one to pick

Pick claude-mem if…

Easy setup — one-command installer and a local worker that preserves and injects compressed session context into future Claude Code sessions.

Runs in cli, ide, coding-agent-plugin, web-app. Works with byok, anthropic, openai, gemini.

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.

Runs in cli, coding-agent-plugin, web-app. Works with byok, openai, anthropic, gemini, other-fixed.

What people want from each one

Questions people ask

Is claude-mem better than headroom?

Neither one leads on the six capability axes, so the choice comes down to which of them fits the way you already work. claude-mem is worth picking when easy setup — one-command installer and a local worker that preserves and injects compressed session context into future Claude Code sessions.

Which of claude-mem and headroom keeps my code private?

claude-mem: Self-hostable (local worker) (4/5). headroom: Self-hostable (4/5).

What does each one cost to run?

claude-mem: Your API key for model calls; optional cloud backup to cmem.ai. headroom: Local software is free; LLM calls use your API key..

Full profiles: thedotmack/claude-mem and headroomlabs-ai/headroom. Everything else in Memory & context.