GoKawiilPaper2Agent tool converts research papers into interactive AI agents
Stanford researchers led by James Zou built a system called Paper2Agent that automatically transforms a scientific paper's text, code and data into an AI agent acting as a stand-in for its corresponding author. The tool deposits a paper's materials onto an MCP server, has AI agents build tools that apply the paper's methods to new data, and lets scientists query the resulting agent in plain language via any large language model. In one test, it built an agent for the AlphaGenome paper in about 45 minutes for $14, and that agent answered genetics questions with near-perfect accuracy.
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This approach could turn static publications into interactive, queryable resources, making it easier for researchers outside a paper's field to understand and apply its methods without wading through technical text or code. It also hints at a future where AI agents representing different papers can collaborate directly, potentially accelerating cross-disciplinary discovery and reshaping how scientific knowledge is shared and reused.
- Paper2Agent automatically converts a paper's text, code and data into a conversational AI agent.
- The AlphaGenome paper's agent was built in 45 minutes for $14 and answered genetics queries with near-perfect accuracy.
- The system could let AI agents for different papers collaborate, fostering cross-disciplinary research.
Source: nature.com — Glickman, 2026-09-16
Published there as: “AI tool turns any paper into an ‘agent’ that can collaborate and answer complex queries”
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