Reimagining Research Papers as Interactive and Reliable AI Agents (New Journal Article)

Researchers have developed Paper2Agent, an automated framework published in Nature that converts static research papers, codebases, and datasets into interactive AI agents functioning as virtual corresponding authors. By turning scholarly outputs into model context protocol (MCP) servers connected to chat agents, the system enables users to run complex scientific queries, reproduce results, and adapt workflows using natural language. For library science and higher education faculty, this shift signals a potential evolution in scholarly communication and knowledge dissemination from passive text archives to interactive, executable systems.

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