Item: IMPROVING ACCESSIBILITY OF OPERATIONAL AVALANCHE BULLETINS THROUGH A MODEL CONTEXT PROTOCOL (MCP) SERVER
-
-
Title: IMPROVING ACCESSIBILITY OF OPERATIONAL AVALANCHE BULLETINS THROUGH A MODEL CONTEXT PROTOCOL (MCP) SERVER
Proceedings: Proceedings, International Snow Science Workshop, Whistler, BC, Canada, 2026
Authors:
- Norbert Lanzanasto [ Avalanche Warning Service Tyrol, Innsbruck, Austria ]
- Christoph Stanger [ Google, Zirl, Austria ]
- Bengt Haunerland [ Avalanche Warning Service Tyrol, Innsbruck, Austria ]
- Simon Legner [ TBBM, Innsbruck, Austria ]
Date: 2026-09-28
Abstract: Timely access to official avalanche bulletins is critical for safe decision-making in avalanche terrain. While avalanche warning services publish structured and text-based bulletins, these formats are primarily optimized for direct human consumption. Large language model (LLM) based tools offer new opportunities to improve accessibility by enabling interactive, multilingual, and user-adapted safety assessments. However, a key technical challenge is ensuring LLM responses are strictly grounded in real-time authoritative forecasts to prevent safety-critical hallucinations. To address this, we developed the Albina Model Context Protocol (MCP) server, which exposes published avalanche bulletins directly to LLMs as secure, machine-readable resources and tools. Built upon the Canadian Avalanche Association Markup Language (CAAML) standard, our server acts as a standardized middleware layer that retrieves the latest forecasts at query time. We propose a unified global aggregation model where a single centrally operated server aggregates CAAML-compliant feeds from multiple regional services. This model reduces technical friction for developers, minimizes operational costs for forecast organizations, and preserves strict authority control under the official warning services. Prototype integrations demonstrate that conversational assistants can reliably summarize hazard levels, resolve location queries, and retrieve operational blog posts while remaining strictly grounded in the official, currently active bulletin.
Object ID: ISSW2026_P1.5.pdf
DOI: https://doi.org/10.15788/1790098830
Language of Article: English
Presenter(s): Norbert Lanzanasto
Keywords: Avalanche Bulletin, Model Context Protocol, Large Language Models, CAAML, Information Accessibility
Page Number(s): 86 - 87
-