Nature's Paper2Agent converts research papers into interactive AI agents via MCP servers
krishnan · x · 2026-09-17
Stanford's James Zou and colleagues publish Paper2Agent in Nature: an automated framework that converts research papers into AI agents. Instead of readers manually adapting a paper's code, data, and methods, multiple agents analyze the paper and codebase to build a Model Context Protocol (MCP) server, then generate and run tests to refine and harden it — turning the paper into a "virtual corresponding author."
Paper MCPs can be connected to chat agents, exposing manuscripts, supplementary materials, datasets, code, and workflows as active, agent-native knowledge rather than static text. Sharer Krishnan imagines agents talking to every paper on arXiv as a catalyst for scientific innovation.
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