Python MCP Server
Introduction
This server provides an interface based on the Model Context Protocol (MCP) for obtaining real-time meteorological data. It supports multiple data formats and can be accessed through standard APIs.Main Functions
It includes services such as weather forecasting, climate analysis, and meteorological alerts, which are suitable for multiple fields such as scientific research, agriculture, and transportation.Use Cases
Developers can use this interface to build meteorological-related applications, and researchers can use it for data analysis and modeling.High AvailabilityThe server has load balancing and fault recovery mechanisms to ensure the stability and reliability of the service.
Multi-Data Source SupportIt can integrate multiple meteorological data sources to provide comprehensive data coverage.
ScalabilityThe modular design allows for easy addition of new functions and data types.
Supports multiple data formats to meet different needs.
Built-in cache mechanism to improve data access efficiency.
Provides detailed error logs and debugging information.
Currently, it only supports data sources from the U.S. National Weather Service.
Some advanced functions require additional licenses.
The documentation is still being improved, and there may be difficulties in understanding.
Install Dependencies
Use pip to install the required Python libraries, including mcp-sdk and requests.
Initialize the Server
Configure basic settings and start the service.
Connect the Client
Connect to the server via HTTP or WebSocket protocol.
What Python version is required?
How to conduct a stress test?
Does it support IPv6?
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