mlsanityData to 7 Oct 2026

Orchestrating Power Grid Studies with Multi-Agent AI and MCP Servers

arXiv 2607.14158 ↗First posted 14 Jul 2026cs.AI cs.CL cs.MAcited by 0

On the map: LLM agents and tool use → Financial trading and forecasting agents

Abstract (arXiv)

This position paper explores how Agentic AI and Model Context Protocol (MCP) can support power-grid studies in a Transmission System Operator (TSO) context. We focus on integrating Large Language Models with numerical simulation tools, structured workflows, and human supervision. We identify key industrial requirements for agent assisted grid studies and introduce pypowsybl-mcp, an MCP-based interface exposing selected capabilities of our simulation tool, pypowsybl to AI agents. This first step provides a testbed to study how agents can setup simulations, execute analyses, retrieve results, and interact with power-system simulators through standardized tool calls. We also discuss principles for human-in-the-loop, multi-agent workflows and outline an evaluation strategy combining technical metrics and practitioner feedback. The paper positions MCP-based tool integration as a step toward more interactive, auditable, and scalable grid-study environments.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Financial trading and forecasting agents, one of 16 directions in LLM agents and tool use. Builds on 8 of its 16 references that are in the map. First posted on arXiv 14 Jul 2026.

Builds on

8 of 16 references.

Closest ancestors · 2

Same direction, newest first

  1. 2025X-GridAgent: An LLM-Powered Agentic AI System for Assisting Power Grid Analysis23 Dec
  2. 2025Agentic AI Systems in Electrical Power Systems Engineering: Current State-of-the-Art and Challenges18 Nov

Other references · 6

  1. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
  2. 2023Toolformer: Language Models Can Teach Themselves to Use Toolscited by 4,072
  3. 2023AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversationcited by 1,906
  4. 2024EASYTOOL: Enhancing LLM-based Agents with Concise Tool Instructioncited by 153
  5. 2017pandapower - an Open Source Python Tool for Convenient Modeling, Analysis and Optimization of Electric Power Systemscited by 79
  6. 2026A Survey of Agentic Reasoning for Large Language Models: Towards Recursively Self-Improving and Collective Agentscited by 47

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Similar, not cited

Close in wording, no citation either way

  1. 2025GridMind: LLMs-Powered Agents for Power System Analysis and Operations
  2. 2026Power Systems Agent Benchmark: Executable Evaluation of AI Agents in Electric Power Engineering
  3. 2025PowerChain: A Verifiable Agentic AI System for Automating Distribution Grid Analyses
  4. 2025Grid-Agent: An LLM-Powered Multi-Agent System for Power Grid Control
  5. 2026RestoreBench: Can AI Agents Restore Power Flow Convergence?
  6. 2026LLMs and Agentic AI Systems for Smart Grids: A Tutorial on Architectures and Applications
  7. 2026PowerBench: A Benchmark for Agentic Retrieval and Reasoning in Power Systems
  8. 2026AutoB2G: Agentic Simulation and Reinforcement Learning for Spatio-Temporal Grid-Interactive Building Control