⬢github first seen 2 d ago, last just now, peak #4

Headroom tool compresses LLM inputs to cut token costs

Original: headroomlabs-ai/headroom

Headroom, an open-source Python project, compresses tool outputs, logs, files and RAG chunks before they are sent to large language models. Its developers report roughly 20% fewer tokens for coding agents and 60-95% fewer for JSON payloads, with identical answers. It ships as a library, a proxy and an MCP server, and is drawing attention as teams look to rein in the rising cost of running AI agents.

Why now: Developers are actively looking for ways to cut token costs as AI agent usage scales up.

Headroomheadroomlabs-ai

Open on github →

Rank over time, top of the chart is #1. 48 snapshots from 11 h ago to just now.

Evidence

• headroomlabs-ai/headroom · headroomlabs-ai · 16

  Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 20% fewer tokens for coding agents, 60-95% fewer tokens for JSON, same answers. Library, proxy, MCP server.

API: https://socialmediatrends-api.osmike.com/v1/trends/2852465