Amap Weather Server

The Amap Weather Server is an MCP‑enabled service that exposes real‑time meteorological data from the Gaode (Amap) weather API. By translating Amap’s raw endpoints into a clean, context‑aware interface, the server allows AI assistants to retrieve precise weather information—such as temperature, humidity, wind speed, and forecast summaries—for any geographic location in China. This eliminates the need for developers to handle authentication tokens, query formatting, and rate‑limit logic themselves.

At its core, the server offers a single resource: . Clients can request weather details by providing a latitude/longitude pair or an Amap place ID. The server then performs the necessary HTTP call to Gaode’s API, normalizes the response into a consistent JSON schema, and returns it via MCP. The normalization step removes extraneous fields, maps Chinese field names to English equivalents, and includes unit conversions where appropriate. This ensures that downstream AI models receive data in a predictable structure, simplifying integration into natural language responses or analytic pipelines.

Key capabilities include:

• Geospatial querying: Accepts both coordinate pairs and place identifiers, making it flexible for location‑based requests.
• Forecast retrieval: Supports current conditions and multi‑day forecasts, enabling AI assistants to provide short‑term outlooks.
• Rate‑limit handling: The server internally manages Gaode’s request limits, queuing or throttling as needed to keep the AI experience smooth.
• Secure credential management: API keys are stored on the server side, so client applications never expose sensitive credentials.

Typical use cases span a wide range of AI workflows. A travel assistant can ask, “What’s the weather in Chengdu tomorrow?” and receive a concise forecast without any API key handling. A logistics chatbot might query “Is rain expected on the route from Shanghai to Guangzhou?” and get a weather‑based routing recommendation. Weather‑dependent smart home assistants can schedule HVAC adjustments based on forecasted temperature trends.

The server’s integration is straightforward: once an MCP client registers the resource, any prompt that references it can invoke the tool. Because MCP automatically handles context propagation and response parsing, developers can focus on crafting higher‑level business logic rather than plumbing weather data into their models. The Amap Weather Server thus bridges the gap between raw meteorological services and conversational AI, providing reliable, localized weather intelligence that powers a multitude of real‑world applications.