---
title: "headroom"
type: "tool"
slug: "headroomlabs-ai-headroom"
canonical_url: "https://www.graphcanon.com/tools/headroomlabs-ai-headroom"
github_url: "https://github.com/headroomlabs-ai/headroom"
homepage_url: "https://headroom-docs.vercel.app/docs"
stars: 57440
forks: 4232
primary_language: "Python"
license: "Apache-2.0"
categories: ["llm-frameworks", "developer-tools"]
tags: ["compression", "python", "library", "rag", "context-engineering", "token-optimization", "proxy", "agent"]
updated_at: "2026-07-07T19:03:30.510508+00:00"
---

# headroom

> Context compression layer for AI agents

A library and proxy designed to compress logs, files, and RAG chunks before they reach the LLM. It claims a significant reduction in tokens used (60-95% fewer) without losing information integrity.

## Facts

- Repository: https://github.com/headroomlabs-ai/headroom
- Homepage: https://headroom-docs.vercel.app/docs
- Stars: 57,440 · Forks: 4,232 · Open issues: 547 · Watchers: 178
- Primary language: Python
- License: Apache-2.0
- Last pushed: 2026-07-07T17:23:26+00:00

## Categories

- [LLM Frameworks](/categories/llm-frameworks.md)
- [Developer Tools](/categories/developer-tools.md)

## Tags

compression, python, library, rag, context-engineering, token-optimization, proxy, agent

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## README (excerpt)

```text
<div align="center"><pre>
  ██╗  ██╗███████╗ █████╗ ██████╗ ██████╗  ██████╗  ██████╗ ███╗   ███╗
  ██║  ██║██╔════╝██╔══██╗██╔══██╗██╔══██╗██╔═══██╗██╔═══██╗████╗ ████║
  ███████║█████╗  ███████║██║  ██║██████╔╝██║   ██║██║   ██║██╔████╔██║
  ██╔══██║██╔══╝  ██╔══██║██║  ██║██╔══██╗██║   ██║██║   ██║██║╚██╔╝██║
  ██║  ██║███████╗██║  ██║██████╔╝██║  ██║╚██████╔╝╚██████╔╝██║ ╚═╝ ██║
  ╚═╝  ╚═╝╚══════╝╚═╝  ╚═╝╚═════╝ ╚═╝  ╚═╝ ╚═════╝  ╚═════╝ ╚═╝     ╚═╝
              The context compression layer for AI agents
</pre></div>

<p align="center"><strong>60–95% fewer tokens (for JSON data), 15-20% fewer tokens (for coding agents) · library · proxy · MCP · content-aware compressors · local-first · reversible</strong></p>

<p align="center">
  <a href="https://github.com/chopratejas/headroom/actions/workflows/ci.yml"><img src="https://github.com/chopratejas/headroom/actions/workflows/ci.yml/badge.svg" alt="CI"></a>
  <a href="https://app.codecov.io/gh/chopratejas/headroom"><img src="https://codecov.io/gh/chopratejas/headroom/graph/badge.svg" alt="codecov"></a>
  <a href="https://pypi.org/project/headroom-ai/"><img src="https://img.shields.io/pypi/v/headroom-ai.svg" alt="PyPI"></a>
  <a href="https://www.npmjs.com/package/headroom-ai"><img src="https://img.shields.io/npm/v/headroom-ai.svg" alt="npm"></a>
  <a href="https://huggingface.co/chopratejas/kompress-v2-base"><img src="https://img.shields.io/badge/model-Kompress--v2--base-yellow.svg" alt="Model: Kompress-v2-base"></a>
  <a href="LICENSE"><img src="https://img.shields.io/badge/license-Apache%202.0-blue.svg" alt="License: Apache 2.0"></a>
  <a href="https://headroom-docs.vercel.app/docs"><img src="https://img.shields.io/badge/docs-online-blue.svg" alt="Docs"></a>
</p>

<p align="center">
  <a href="https://headroom-docs.vercel.app/docs">Docs</a> ·
  <a href="#get-started-60-seconds">Install</a> ·
  <a href="#proof">Proof</a> ·
  <a href="#agent-compatibility-matrix">Agents</a> ·
  <a href="https://discord.gg/yRmaUNpsPJ">Discord</a> ·
  <a href="llms.txt">llms.txt</a>
</p>

<p align="center"><sub>
  <b>AI agents / LLMs:</b> read <a href="llms.txt"><code>/llms.txt</code></a> here, or fetch <a href="https://headroom-docs.vercel.app/llms.txt">the live index</a> / <a href="https://headroom-docs.vercel.app/llms-full.txt">full docs blob</a>.
</sub></p>

---
<p align="center"><a href="https://trendshift.io/repositories/20881" target="_blank"><img src="https://trendshift.io/api/badge/repositories/20881" alt="chopratejas%2Fheadroom | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a></p>

Headroom compresses everything your AI agent reads — tool outputs, logs, RAG chunks, files, and conversation history — before it reaches the LLM. Same answers, fraction of the tokens.

<p align="center">
  <img src="HeadroomDemo-Fast.gif" alt="Headroom in action" width="820">
  <br/><sub>Live: 10,144 → 1,260 tokens — same FATAL found.</sub>
</p>

## What it does

- **Library** — `compress(messages)` in Python or TypeScript, inline in any app
- **Proxy** — `headroom proxy --port 8787`, zero code changes, any language
- **Agent wrap** — `headroom wrap claude|codex|copilot|cursor|aider|opencode|cline|continue|goose|openhands|openclaw|vibe` in one command; undo with `headroom unwrap <tool>`
- **MCP server** — `headroom_compress`, `headroom_retrieve`, `headroom_stats` for any MCP client
- **Cross-agent memory** — shared store across Claude, Codex, Gemini, auto-dedup
- **`headroom learn`** — mines failed sessions, writes corrections to `CLAUDE.local.md` (default, gitignored) or `CLAUDE.md` / `AGENTS.md` / `GEMINI.md`
- **Output token reduction** — trims what the model *writes back* (not just what you send): drops ceremony/restated code and skips deep "thinking" on routine steps. See [Output token reduction](#output-token-reduction-cut-what-the-model-writes-back).
- **Reversible (CCR)** — originals are cached for retrieval on demand

## How it works (30 seconds)

```
 Your agent / app
```

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/tools/headroomlabs-ai-headroom`](/api/graphcanon/tools/headroomlabs-ai-headroom)
- LLM index: [/llms.txt](/llms.txt)
- Full corpus: [/llms-full.txt](/llms-full.txt)

_GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_