
From papers to interactive AI agents: a framework for reproducible, queryable science
A new framework called Paper2Agent converts scientific papers into autonomous AI agents by packaging a paper’s manuscript, data, code and workflows into a Model Context Protocol (MCP) server and linking it to chat agents; case studies with AlphaGenome, Scanpy, and TISSUE show agents reproduce results and handle novel, user-asked analyses, lowering barriers to adoption and enabling collaborative AI co-scientists.









