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Redirects heavy data to isolated processes and returns concise summaries to prevent token overflow.
Distinct from Output Redirection: Focuses on context window optimization for AI agents rather than simple shell file redirection.
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This project provides a system for managing agent context and session memory, featuring an agent context compactor, an AI session memory manager, and a tool output sandbox. It functions as a middleware layer and server extension for the Model Context Protocol to optimize context windows and reduce token usage. The system optimizes agent performance by sandboxing tool outputs and externalizing large data sets, replacing raw I/O with pointers and concise summaries. It employs a persistent knowledge base that indexes session history and tool outputs for retrieval via full-text search, ensuring s
Redirects heavy tool data to isolated processes and returns summaries to prevent context window overflow.