Is MeteoSwiss MCP Server safe?
Yes, with the usual care.
Passed every safety check we run. Maintained, authenticated, reachable, clean scan.
No critical or high findings in the latest scan.
How MeteoSwiss MCP Server compares
Against every graded Maps and travel MCP server, from our own scans and uptime checks. Updated after each scan run.
- Safety score
- 88/100
- higher than 83% of 679 Maps and travel servers
- Tools that change things
- 0%
- typical: 0%. Fewer write tools means less an agent can break
- Uptime
- 96%
- of our recent checks; the typical remote Maps and travel server answers 100%
What its tools let an agent do: 7 read
Public scan report
scanner v0.1.10 · 2026-11-12 · same rubric, same numbers if you re-run it
1 low
- Code scan41 source files scanned25/25
- Live reliabilityremote reachable in 2109ms17/20
- Tool poisoning7 tool descriptions checked13/15
- Auth qualityopen endpoint, read-only tools10/15
- Maintenancelast push 0 days ago15/15
- Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10
Findings (1)
- lowUnusually long tool description (over 2,000 characters)
poison.long-descriptiontool meteoswissLocalForecast: …Get a multi-day weather forecast for any Swiss location. Returns daily summaries (temperature, precipitation, sunshine, wind, weather icon) plus a hierarchical hourly breakdown of every series. This uses official MeteoSwiss Open Data — the same forecasts powering the MeteoSwiss app and website. Accepts: - Postal codes: "8001" (Zurich), "3000" (Bern), "1200" (Geneva) - Station abbreviations: "SMA" (Zurich Fluntern), "BER" (Bern) - Place names: "Zurich", "Basel", "Lugano" Coverage: ~6000 Swiss locations (all postal codes + weather stations + mountain points). Forecast horizon: up to 9 days. Updated hourly. Each day's summary fields: temperature_min_c, temperature_max_c, precipitation_total_mm, sunshine_total_minutes, wind_avg_kmh, wind_gust_max_kmh, weather, weather_icon_url. Each day also includes "hourly": one array of per-hour objects covering every series together — { time, temperature_c, precip_mm, sunshine_minutes, wind_kmh, wind_gust_kmh } — useful for judging *when* rain, sun, or wind is expected, not just the daily summary: - Each entry's "time" is already local wall-clock time for the location (Europe/Zurich), with the UTC offset included, e.g. "2026-07-09T14:00:00+02:00". It is NOT UTC — do not convert it. - A dry/calm/sunless hour is reported as its measured value (often 0), not omitted. A fully dry day is still a full array of zero-precipitation hours, not an empty array. - Each field is independently null if just THAT series has no reading for a given hour — the other fields for that same hour are still populated. An hour is omitted entirely only when every series is missing for it. - "hourly" itself is null when no hourly breakdown exists for this location at all (a total data gap); [] only when this location supports hourly data but none was available for that specific day. - For weather stations, temperature_min_c/temperature_max_c/precipitation_total_mm are MeteoSwiss's own official daily aggregates — a different, separately-curated product from the hourly series shown alongside them. They can legitimately NOT match summing/ averaging the hourly entries for that day; this is expected, not a data error. sunshine_total_minutes/wind_avg_kmh/wind_gust_max_kmh have no official daily product for stations and are always derived from the hourly series. For postal codes/mountain points, every summary field is derived from the same hourly series shown alongside it, so it always matches summing/averaging that series exactly.…
Overall 88/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON
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