// devtools · headroomlabs-ai/headroom

headroom

headroom é um projeto de ferramentas de desenvolvimento de código aberto de headroomlabs-ai (headroomlabs-ai/headroom no GitHub). Tem 74.736 estrelas no GitHub e 5.785 forks, é publicado sob a licença Apache-2.0 e foi atualizado pela última vez no GitHub em 8 de outubro de 2026.

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

★ 74,7 mil estrelas⑂ 5,8 mil forksApache-2.0atualizado out 2026
▦ visual: o README deste projeto não inclui nenhuma captura incorporável,
então aqui vai um marcador. O guia abaixo está completo mesmo assim.
// dados do projeto

Dados do projeto

Estrelas no GitHub
74.736
Forks
5.785
Licença
Apache-2.0
Última atualização no GitHub
8 de outubro de 2026
Tipo de ficha
Guia de instalação completo
Site oficial
Official site
// como funciona

Como funciona

  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.

// recursos

Por que as pessoas gostam tanto

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.

Advertisement
// execute você mesmo

Execute você mesmo

  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
// casos de uso

O que você pode criar

Advertisement
// perguntas frequentes

Perguntas frequentes

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.

// continue explorando

Ferramentas semelhantes

Ferramentas de desenvolvimento

toon

TOON: a compact, human-readable serialization of JSON that saves tokens in LLM prompts

★ 25,5 mil estrelasMIT
Ver o guia →
Ferramentas de desenvolvimento

semble

Fast, accurate semantic code search for agents — about 99% fewer tokens than grep plus read.

★ 6,2 mil estrelasMIT
Ver o guia →
Ferramentas de desenvolvimento

easy-dataset

Turn domain documents into high-quality LLM fine-tuning, RAG and evaluation datasets through a visual UI.

★ 15,0 mil estrelasAGPL-3.0
Ver o guia →
Ferramentas de desenvolvimento

aichat

One Rust CLI for every LLM: shell assistant, chat REPL, RAG, tools and agents across 20+ providers.

★ 10,5 mil estrelasApache-2.0
Ver o guia →
Ferramentas de desenvolvimento

openagent

⚡️next-generation personal AI assistant powered by LLM, RAG and agent loops, supporting computer-use, browser-use and coding agent, demo: https://demo.openag…

★ 5,7 mil estrelasApache-2.0
Ver o guia →
Ferramentas de desenvolvimento

llm-course

A free course to get into large language models, with roadmaps and runnable Colab notebooks

★ 83,3 mil estrelasApache-2.0
Ver o guia →
// alternativas

Alternativas em Ferramentas de desenvolvimento

Os outros projetos de Ferramentas de desenvolvimento com mais estrelas no catálogo do LibreAI — a lista realista de alternativas se headroom não for o ideal para você.

// mais em devtools

Mais em Ferramentas de desenvolvimento

Projetos de Ferramentas de desenvolvimento próximos no catálogo, os mais próximos em estrelas de headroom: continue explorando dos dois lados dele.

Baixe o headroom

Grátis e aberto: pegue o código-fonte, dê uma estrela no repositório e comece a criar.