Analyze your AI outputs
Headroom reduces token usage by 60% to 95% by compressing log files, tool outputs, and contextual data chunks (RAG chunks) sent to large language models (LLM). This Python-based tool offers different integration options as a library, proxy and Model Context Protocol (MCP) server.
What you get
- Reduces coin usage by 60% to 95%.
- Protects privacy by compressing data locally.
- Provides recallable compression without losing original data.
Installation
pip install "headroom-ai[all]" # Python
npm install headroom-ai # Node / TypeScriptRunning it
headroom wrap claude # wrap a coding agent
headroom proxy --port 8787 # drop-in proxy, zero code changesheadroom perfIf you don't write code
I want to optimize my AI agent's consumption of contextual data and log files using the Headroom tool. I completed the installation with the command "pip install "headroom-ai[all]"" in the Python environment. How should I configure the "headroom wrap claude" or "headroom proxy --port 8787" commands to reduce the amount of tokens my agent uses? Also, how should I interpret the savings data I get with the "headroom perf" command?
Repository: https://github.com/chopratejas/headroom. Follow the official instructions in the README of this repository for setup and execution.
Before starting, check which OS we are on and if the necessary tools (e.g., Python, Node.js, Git, Docker) are installed. Install any missing ones step-by-step according to this system.
Create a new, empty folder to work in. Do not touch any files outside this folder and do not delete anything. Tell me what you are going to do in one sentence before running each command.
Tell me what I should see on the screen at the end of each step. If an error occurs, I will paste the error message to you exactly as it is, and we will fix it together.
Related dictionary terms
Links
TreScout did not build this tool · we found it in GitHub trends and wrote it up. This page describes the repository as of 2026-06-03: The star count and our text belong to that day, the repository may have changed since. Check the repository link for the current state. The introductory text was prepared with AI from the repository's own documentation, and this page was machine-translated from the Turkish original · the Turkish version prevails.