# 60–95% fewer tokens in your agent loops, same answers. Meet Headroom.

> Source: <https://dev.to/thegatewayguy/60-95-fewer-tokens-in-your-agent-loops-same-answers-meet-headroom-1999>
> Published: 2026-06-20 09:41:35+00:00

AI coding agents are expensive — not because models cost too much per token, but because they send too many of them. An SRE debugging session with a raw agent: 65,694 tokens in. With Headroom in the middle: 5,118. Same bug found.

[Headroom](https://github.com/chopratejas/headroom) is a new open-source context compression layer that intercepts everything your agent reads — tool outputs, log dumps, RAG chunks, files, conversation history — and compresses it before the LLM ever sees it. It's local, reversible, and available as a drop-in proxy, a library, or an MCP server.

Savings on real agent workloads:

Accuracy on standard benchmarks (GSM8K, TruthfulQA, SQuAD v2, BFCL) is preserved — some scores actually improve slightly, likely because the model sees cleaner signal.

Under the hood, Headroom routes content through a stack of specialised compressors:

It also does **CCR (reversible compression)** — originals are cached locally and the LLM can retrieve them on demand if it needs them. Nothing is destroyed.

The most interesting deployment path: `headroom proxy --port 8787`

, then point your existing tool at localhost. Zero code changes. Works with any language.

Or even simpler: `headroom wrap claude`

wraps Claude Code, routes its traffic through Headroom automatically. One command, savings start immediately. Same for Codex, Cursor, Aider, Copilot CLI.

"Library — compress(messages) in Python or TypeScript, inline in any app. Proxy — headroom proxy --port 8787, zero code changes, any language."

There's also a **cross-agent memory** store — shared context across Claude, Codex, and Gemini sessions with auto-dedup — and a `headroom learn`

feature that mines past failed sessions and writes corrections back to your CLAUDE.md / AGENTS.md.

`pip install "headroom-ai[all]"`

then `headroom wrap claude`

. See the savings in five minutes.`headroom proxy --port 8787`

and point your client at localhost. No code changes needed.`HEADROOM_OUTPUT_SHAPER=1`

— it trims verbose model output too, and on 5× output pricing that adds up fast.Source: [github.com/chopratejas/headroom](https://github.com/chopratejas/headroom)

*✏️ Drafted with KewBot (AI), edited and approved by Drew.*