An Agentic Interface for End-to-End Probabilistic Seismic Hazard and Risk Analysis

arXiv:2607.16249 · physics.geo-ph, cs.AI · Submitted 2026-06-27 · Read on arXiv

physics.geo-ph, cs.AI

Submitted: 2026-06-27

Updated: 2026-06-27

Code: https://github.com/gem/oq-engine

Terminology

• Model Context Protocol — 12× in this paper
• Provenance — 10× in this paper · explained in 3 episodes
• Core — 7× in this paper · explained in 2 episodes
• Agentic AI — 6× in this paper · explained in 1 episode
• Hallucination — 6× in this paper · explained in 3 episodes
• Accuracy — 4× in this paper · explained in 1 episode
• Model Context Protocol (MCP) — 4× in this paper · explained in 8 episodes
• Verification — 3× in this paper · explained in 2 episodes
• Data Provenance — 2× in this paper · explained in 2 episodes
• Engineering Strong-Motion — 2× in this paper
• Epistemic Uncertainty — 2× in this paper · explained in 9 episodes
• Generative AI — 2× in this paper · explained in 2 episodes
• Global Earthquake Model — 2× in this paper
• Large Language Model (LLM) — 2× in this paper · explained in 3 episodes
• Multi-Agent System — 2× in this paper · explained in 5 episodes
• Trace — 2× in this paper · explained in 2 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Agentic Framework — 1× in this paper · explained in 6 episodes
• Agentic System — 1× in this paper · explained in 2 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Calibration — 1× in this paper · explained in 7 episodes
• European Facility for Earthquake Hazard and Risk — 1× in this paper
• Failure Modes — 1× in this paper · explained in 3 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Natural-hazards Risk Markup Language — 1× in this paper
• RAG — 1× in this paper · explained in 3 episodes
• Systematic Bias — 1× in this paper · explained in 3 episodes
• World Model — 1× in this paper · explained in 7 episodes

Sources

• From Research Question to Scientific Workflow: Leveraging Agentic AI for Science Automation
• An LLM Agent for Automatic Geospatial Data Analysis
• Securing the Model Context Protocol (MCP): Risks, Controls, and Governance
• A Lightweight Large Language Model-Based Multi-Agent System for 2D Frame Structural Analysis
• Agentic AI for Scientific Discovery: A Survey of Progress, Challenges, and Future Directions
• Model Context Protocol (MCP) Tool Descriptions Are Smelly! Towards Improving AI Agent Efficiency with Augmented MCP Tool Descriptions
• Model Context Protocol (MCP): Landscape, Security Threats, and Future Research Directions
• CLIMATEAGENT: Multi-Agent Orchestration for Complex Climate Data Science Workflows
• LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment
• Mitigating Hallucination in Large Language Models: A Capability-Oriented Survey on RAG, Reasoning, and Agentic Systems
• Automating Structural Engineering Workflows with Large Language Model Agents
• LLM-based Agents Suffer from Hallucinations: A Survey of Taxonomy, Methods, and Directions
• Experiences with Model Context Protocol Servers for Science and High Performance Computing
• BioinfoMCP: A Unified Platform Enabling MCP Interfaces in Agentic Bioinformatics
• AQUAH: Automatic Quantification and Unified Agent in Hydrology

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