Paper2Agent turns research papers into agents you can question

Published in Nature this week, Paper2Agent is an automated framework that turns a scientific paper, with its supplementary material, datasets and code, into an interactive ai agent. The agent acts as a "virtual corresponding author": it answers questions about the work, reproduces its analyses, applies its methods to new data and can work alongside other paper agents.

It does this by building an MCP server of executable tools around the paper and connecting it to a language model; the team used Claude Sonnet 4.

The results

• 89.0% accuracy on synthesis tasks across 26 data-focused papers
• an agent built from AlphaGenome outscored other leading biomedical agents, including Biomni, on the same questions

Why it matters

Using someone else's method often takes weeks of setting up environments and adapting code. If papers become things you can run, reproducing and reusing research gets cheaper, including across disciplines.