Headroom: Compressing Tool Output and RAG Chunks Before the LLM
ORIGINAL / headroomlabs-ai/headroom
This GitHub project ships a library, a proxy, and an MCP server that compress tool outputs, logs, files, and RAG chunks before they reach the LLM. Its novelty is compressing at the prompt entry point rather than inside the model, claiming 20% fewer tokens for coding agents and 60-95% fewer for JSON with the same answers.
01 ABSTRACT
The project describes itself as compressing tool outputs, logs, files, and RAG chunks before the LLM. The authors claim 20% fewer tokens for coding agents and 60-95% fewer for JSON with unchanged answers. These figures come from the project description and are not independently verified.
02 KEY FINDINGS
- Ships three integration forms: library, proxy, and MCP server
- Compresses tool outputs, logs, files, and RAG chunks
- Authors claim about 20% fewer tokens for coding agents
- Authors claim 60-95% fewer tokens for JSON with the same answers
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