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Paper2agent

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Paper2Agent 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.

Paper2Agent turns research papers into AI agents via Claude Code pipeline

Researchers built Paper2Agent, a system that converts a scientific paper and its accompanying codebase into a functional MCP server accessible through an AI agent interface. It uses a multi-agent architecture built on Claude Code's agent SDK, with a central orchestrator directing specialized sub-agents through a six-step process covering repository discovery, environment setup, tutorial scanning, and execution auditing.