LibreAI / Dev Tools / headroom
// devtools · headroomlabs-ai/headroom

headroom

Compress tool outputs, logs and RAG chunks before they reach the LLM — same answers, fewer tokens

★ 74.7k stars⑂ 5.8k forksApache-2.0updated 2026-10
▦ visual — this project's README ships no embeddable screenshot,
so here's a placeholder. The guide below is complete regardless.
// project facts

Project facts

headroom is an open-source dev tools project by headroomlabs-ai (headroomlabs-ai/headroom on GitHub). It has 74,736 GitHub stars and 5,785 forks, is released under the Apache-2.0 license, and was last updated on GitHub on 8 October 2026.

GitHub stars
74,736
Forks
5,785
License
Apache-2.0
Last updated on GitHub
8 October 2026
Category
Dev Tools
Listing
Full install guide
Official site
Official site
// how it works

How it works

  1. Clarify your goal

    Decide what you want from headroom and check the README and requirements to confirm it fits your setup and Python environment.

  2. Get the code

    Clone the repository from GitHub (github.com/headroomlabs-ai/headroom) or use the documented install channel if you do not need the source.

  3. Install and configure

    Follow the README quickstart to install dependencies and set any required configuration or credentials.

  4. Run your first task

    Work through the README's first example end to end, then adapt it to your own project or data.

// features

Why people love it

Context compression

Compresses tool outputs, logs, files and RAG chunks before they enter the context window.

Large JSON savings

The project reports 60-95% fewer tokens for JSON payloads while keeping answers the same.

Library, proxy and MCP

Usable as a Python/TypeScript library, a proxy, or an MCP server.

Agent compatible

Works with coding agents such as Claude Code and Cursor and frameworks like LangChain.

Learn mode

`headroom learn` adapts compression to your workload, per the README.

FastAPI based proxy

The proxy is built on FastAPI for easy self-hosting.

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// run it

Run it yourself

  1. Clone the repository

    Start by getting the source and entering the project directory.

    git clone https://github.com/headroomlabs-ai/headroom.git
    cd headroom
  2. Install Headroom

    The README recommends a uv tool install for the CLI, or pip for the Python package.

    pip install "headroom-ai[all]"
  3. Run it with your agent

    Start the proxy or MCP server and point your agent at it, per the 60-second get-started guide.

    headroom  # see README for the exact command
// use cases

What you can build

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// faq

Questions, answered

Who maintains headroom?

It is maintained by headroomlabs-ai and contributors on GitHub, where the repository github.com/headroomlabs-ai/headroom is the canonical home for code, issues and releases.

Is headroom free to use?

Yes — it is open source under the Apache-2.0 license. Read the license in the repository for what is permitted, including any conditions on redistribution or commercial use.

Does it need a paid API key?

No key of its own — it sits in front of your existing LLM provider, which still uses your own key.

How does headroom compare to alternatives?

Compared with manual context pruning: Headroom compresses content automatically as a proxy or MCP server instead of developers hand-trimming every payload.

How do I get started?

Clone github.com/headroomlabs-ai/headroom, follow the README quickstart to install it, and run the documented first example before adapting it to your own work.

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// alternatives

Alternatives in Dev Tools

The most-starred other Dev Tools projects in the LibreAI catalogue — the realistic shortlist if headroom is not the right fit.

Get headroom

Free and open — grab the source, star the repo, and start creating.