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headroomlabs-ai/headroom

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.

Latest metrics (snapshot 2026-10-14)

stars75349
forks5847
issues445
pushed_at2026-10-13T23:39:02Z

History

History chart: 1 daily snapshot so far (archive started 2026-10-14). The line fills in as the daily archive grows; full series via the API.

DateGitHub stars
2026-10-1475349

ADC Momentum: 78/100

ADC Momentum 78 Leaderboard

Growth velocity96
Consistency77
Recency96
Agent demand0
Basisbootstrap

ADC Momentum (0-100) = 45% growth velocity (stars/likes gained per day in our daily archive, relative and absolute, percentile-ranked within the category) + 20% consistency (share of recent days with growth) + 20% recency (latest push/update/release, decaying) + 15% agent demand (how often AI agents looked it up via our API/MCP this week). MCP servers use release cadence; LLMs use price cuts, context and recency. Recomputed daily; scores marked "bootstrap" use lifetime rates until the archive has enough days. Method

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Details

descriptionCompress 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.
urlhttps://github.com/headroomlabs-ai/headroom
languagePython
licenseApache-2.0
topicsagent
ai
anthropic
claude-code
compression
context-engineering
context-window
cursor
fastapi
langchain
llm
mcp
created_at2026-01-07T19:58:51Z
homepagehttps://docs.headroomlabs.ai/docs

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