Stanford's Paper2Agent turns research papers into collaborating AI agents, published in Nature
james_y_zou · x · 2026-09-17
Paper2Agent, a framework by Jiacheng Miao, James Zou and collaborators at Stanford, is published in Nature. It converts research papers into interactive, reliable AI agents: multiple agents analyze the paper and codebase to build an MCP (Model Context Protocol) server, then generate and run tests to refine it — turning manuscripts, supplementary materials, datasets, code, and workflows into agent-native, active knowledge, like a virtual corresponding author.
Paper agents can also collaborate: the demo shows an AlphaGenome agent working with a GWAS dataset agent to characterize splicing mutations associated with ADHD risk. The authors argue agentifying knowledge makes research easier to reproduce, reuse, and extend. A Paper2Agent agent is also available for others to use.
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