A Model Context Protocol Server for Quantum Execution in Hybrid Quantum-HPC Environments
Masaki Shiraishi, Ikko Hamamura, Tatsuya Ishigaki, Tadashi Kadowaki

TL;DR
This paper introduces a Model Context Protocol server enabling AI agents, particularly large language models, to autonomously execute quantum algorithms on remote hardware within hybrid quantum-HPC environments.
Contribution
It presents a novel MCP server framework that allows AI-driven quantum workflow execution, bridging the gap between hypothesis formulation and quantum algorithm implementation.
Findings
Successfully executed quantum primitives like sampling and expectation value computation.
Demonstrated autonomous quantum workflow execution via remote hardware and emulators.
Validated AI agents can manage complex hardware interactions through the MCP architecture.
Abstract
The integration of large language models (LLMs) into scientific research is accelerating the realization of autonomous ``AI Scientists.'' While recent advancements have empowered AI to formulate hypotheses and design experiments, a critical gap remains in the execution of these tasks, particularly in the domain of quantum computing (QC). Executing quantum algorithms requires not only generating code but also managing complex computational resources such as QPUs and high-performance computing (HPC) clusters. In this paper, we propose an AI-driven framework specifically designed to bridge this execution gap through the implementation of a Model Context Protocol (MCP) server. Our system enables an LLM agent to process natural language prompts submitted as part of a job, autonomously executing quantum computing workflows by invoking our tools via the MCP. We demonstrate the framework's…
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