Travel Trends Europe
Travel Intelligence & MCP
Reviewed by OpenAI and published in ChatGPT — plugin in ChatGPT
Case study & materials
The problem
European tourism data sits in hard-to-use Eurostat tables, while travel disruptions (strikes, weather, NOTAMs) are scattered across dozens of sources nobody tracks in one place.
Description
Interactive European tourism explorer (Eurostat, INSSE and World Bank data, 2015 → present) combined with a live disruption radar and a public 8-tool MCP server — from country profiles to continuous trip monitoring. Interface in EN, RO and PL.
Result
A travel decision-support platform: data for all 27 EU countries (3.09 billion nights analyzed), a live disruption radar with 30+ official sources, and a public MCP server AI agents use to assess trip risk.
Technical details
- Tourism panels for all 27 EU member states: hotel nights, arrivals, comparisons, competitiveness, aviation, plus Romanian county-level data (INSSE) and economic indicators from World Bank data.
- Disruption radar aggregating 30+ official sources (34 active today): NOTAMs, rail and road operators, strikes, weather, civil protection, geopolitical advisories — continuously refreshed, with a public per-source status page.
- Public MCP server with 8 tools, published in the official registry as eu.mmatinca/travel-trends-mcp: assess_trip, country_briefing, list_events plus continuity primitives (watch_trip, whats_changed, explain_silence).
- Publicly documented API + RFC 9727 api-catalog, llms.txt and on-demand markdown for agents.
- Public track record: radar predictions logged and checked against reality.