Ataraxis: Bridging AI Coding Assistants and Scientific Hardware

Abstract AI coding assistants excel at software tasks but lack structured access to laboratory hardware, the physical instruments that define experimental science. We present A taraxis , an open-source framework that provides hardware control capabilities spanning camera acquisition, microcontroller communication, precision timing, and inter-process coordination, while exposing these capabilities to AI agents through Model Context Protocol (MCP) servers and domain-specific skills. Critically, A taraxis separates configuration-time AI assistance from runtime data acquisition , ensuring that experiments run deterministically regardless of AI service availability. We validate this architecture in a two-photon imaging and virtual reality rodent behavior platform, demonstrating up to order-of-magnitude reductions in hardware validation, integration, and personnel onboarding time. By bridging the gap between AI software capabilities and physical instrument control, A taraxis offers a reusable blueprint for AI-assisted scientific instrumentation across experimental disciplines. All code is available at github.com/Sun-Lab-NBB/ataraxis .