Taiwan Central Weather Bureau MCP Server

The Taiwan Central Weather Bureau (CWA) MCP server bridges the gap between AI assistants and real‑time meteorological data for Taiwan. By exposing a concise set of tools—, , and —the server allows developers to fetch localized forecasts and recent rainfall statistics with a single API call. This eliminates the need for manual data scraping or complex authentication flows, letting AI agents deliver accurate weather information directly to users in natural language.

Why It Matters

Weather data is a high‑value asset for applications ranging from travel planning to agricultural advisories. Traditional approaches require developers to consume the CWA’s REST endpoints, handle pagination, and parse nested XML/JSON structures. The MCP server abstracts these complexities by providing a clean, tool‑centric interface that returns only the essential fields. This makes it trivial to integrate weather insights into conversational agents, enabling instant, context‑aware responses such as “The forecast for Taipei over the next three days shows a 70 % chance of rain at noon” or “Yesterday’s rainfall in Kaohsiung was 12 mm.”

Core Features

• Three‑day & One‑week Forecasts: Retrieve concise, hourly forecasts for any of the 21 official Taiwanese counties and cities.
• Historical Rainfall: Access rainfall amounts for the past three days, useful for trend analysis or emergency response.
• Automatic Cleanup & Formatting: The server normalizes raw CWA data, stripping extraneous metadata and presenting a flat JSON structure that AI agents can consume directly.
• Robust Error Handling: Built‑in retry logic and timeout controls protect against transient network issues, ensuring reliable data delivery.
• Minimal Payload: Only the most relevant weather elements (temperature, humidity, precipitation) are included, reducing bandwidth and simplifying downstream processing.

Real‑World Use Cases

• Travel Assistants: Agents can answer “Will it rain in Taichung tomorrow?” by querying the three‑day forecast tool.
• Agricultural Planning: Farmers receive weekly precipitation projections to schedule irrigation or harvesting.
• Disaster Preparedness: Emergency services can pull recent rainfall data to assess flood risk in real time.
• Smart Home Integration: Voice assistants suggest indoor activities based on upcoming weather, pulling data from the CWA server effortlessly.

Integration into AI Workflows

A typical workflow involves adding the MCP server to an assistant’s configuration, then invoking a tool via a prompt such as:

“Get the 1‑week weather forecast for Kaohsiung.”

The assistant calls with the location parameter, receives a streamlined JSON response, and formats it into a user‑friendly reply. Because the server adheres to MCP standards, any compliant client—Claude, GPT, or custom agents—can interact with it without additional adapters.

Distinctive Advantages

• Locale‑Specific Coverage: Unlike generic weather APIs, this server focuses exclusively on Taiwan’s administrative regions, ensuring accurate and culturally relevant data.
• Transparent Licensing: The open‑source MIT license invites community contributions and easy deployment in private or commercial environments.
• Developer Friendly: With clear environment variable settings and built‑in testing tools, setting up the server requires only an API key from the CWA portal.

By consolidating Taiwan’s official weather data into a developer‑ready MCP server, this project empowers AI assistants to deliver timely, reliable meteorological insights with minimal effort.