Skip to main content
Glama
kuotunyu

taiwan-weather-mcp

by kuotunyu
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
CWA_API_KEYYesYour free CWA (Central Weather Administration) API key. Required to access Taiwan weather data.

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
get_forecastA

查詢台灣某縣市未來 36 小時天氣預報。

回傳三個時段的天氣現象、降雨機率、氣溫區間與舒適度。
縣市名稱接受常見寫法，例如「台中」「臺北市」「高雄」「Taipei」；
「新竹」「嘉義」同時對應市與縣，會一次回傳兩者。

Args:
    city: 縣市名稱（台灣 22 縣市，中英文皆可）。
get_weather_warningsA

查詢目前生效中的天氣特報（颱風、豪雨、大雨、低溫、強風等）。

依特報種類彙整影響縣市與有效時間；若全臺皆無生效中的警特報， 會明確回覆「目前全臺無生效中的天氣警特報」。

get_recent_earthquakesA

查詢最近幾筆顯著有感地震報告。

每筆包含發生時間、規模、深度、震央位置與各縣市最大震度摘要。

Args:
    limit: 回傳筆數（1–10，預設 5）。

Prompts

Interactive templates invoked by user choice

NameDescription
weather_briefing產生「查詢並播報某縣市天氣」的提示詞範本。 Args: city: 要播報的縣市名稱（預設臺北市）。

Resources

Contextual data attached and managed by the client

NameDescription
taiwan_citiesget_forecast 可查詢的 22 個官方縣市名稱清單（也接受台/臺、英文、簡稱等常見寫法）
Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A4.6/5.0

Scored across 3 tools

Disambiguation5/5

Each tool covers a distinctly separate concern: forecasts, active weather warnings, and recent earthquakes. There is no overlap in purpose or return data, so an agent can select the right tool without ambiguity.

Naming Consistency5/5

All three tools follow the same get_<noun> pattern with clear, descriptive names. The naming is consistent and predictable.

Tool Count4/5

Three tools is at the lower end of a reasonable range, but each covers a meaningful aspect of Taiwan weather information. The count feels slightly minimal rather than bloated, which is appropriate for a focused weather server.

Completeness4/5

The server covers forecasts, warnings, and earthquakes, which are the most commonly requested Taiwan weather data. A minor gap is the lack of current observed weather conditions or air quality, but the existing tools cover the core domain well.

Maintenance

ActivityNo data
ResponsivenessNo issues

Resources