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在AI Agent和MCP(Model Context Protocol)生态快速发展的今天,越来越多优秀的MCP工具涌现出来。今天为大家推荐一个值得关注的项目——headroom

项目简介:Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 60-95% fewer tokens, same answers. Library, proxy, MCP server.

技术信息:主要语言:Python | GitHub Stars:19,119 | 标签:agent, ai, anthropic, claude-code, compression

📖 项目详情

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

该项目主要使用Python开发。

相关领域:Agent, 人工智能, anthropic, claude-code, compression


以下是项目原始介绍(英文):

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The context compression layer for AI agents

60–95% fewer tokens · library · proxy · MCP · 6 algorithms · local-first · reversible

CI

codecov

PyPI

npm

Model: Kompress-base

License: Apache 2.0

Docs

Docs ·

Install ·

Proof ·

Agents ·

Discord ·

llms.txt ·

Enterprise

AI agents / LLMs: read /llms.txt here, or fetch the live index / full docs blob.

chopratejas%2Fheadroom | Trendshift

Headroom compresses everything your AI agent reads — tool outputs, logs, RAG chunks, files, and conversation history — before it reaches the LLM. Same answers, fraction of the tokens.

Headroom in action

Live: 10,144 → 1,260 tokens — same FATAL found.

What it does

Library — `compress(messages)` in Python or TypeScript, inlin

…(更多内容请访问项目主页)

🔗 项目地址

https://github.com/chopratejas/headroom

⭐ 19,119 Stars | Python