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Frequently Asked Questions about Weather MCP Server

Q: What is the Weather MCP Server?

A: The Weather MCP Server is an open-source tool that allows Large Language Models (LLMs) to access real-time weather forecasts and city information via the Model Context Protocol (MCP).

Q: What is MCP (Model Context Protocol)?

A: MCP is an open protocol that standardizes how applications provide context to LLMs, enabling them to access external data sources and tools.

Q: How does the Weather MCP Server work?

A: It acts as a bridge, allowing LLMs to query and receive weather information, such as forecasts, based on location (city name or coordinates).

Q: What is the main tool available in the Weather MCP Server?

A: The primary tool is get_24h_weather, which retrieves weather forecasts for the next 24 hours for a given location.

Q: How do I install the Weather MCP Server?

A: You can install it using uv (recommended), pip, or Docker. Instructions for each method are provided in the documentation.

Q: How do I configure the Weather MCP Server with Claude.app or Zed?

A: Configuration details are provided for both Claude.app and Zed, outlining the necessary JSON settings to integrate the server.

Q: Can I contribute to the Weather MCP Server project?

A: Yes, contributions are encouraged! You can contribute new features, bug fixes, or documentation improvements.

Q: What license is the Weather MCP Server released under?

A: The Weather MCP Server is licensed under the MIT License.

Q: How can I debug the Weather MCP Server?

A: You can use the MCP inspector tool for debugging. Instructions and examples are provided in the documentation.

Q: What are some potential use cases for the Weather MCP Server?

A: Use cases include personalized trip planning, weather-based product recommendations, optimized irrigation in agriculture, and smart home automation.

Q: How does integrating with UBOS enhance the Weather MCP Server?

A: UBOS provides a full-stack AI Agent Development Platform, enabling seamless integration, advanced orchestration, custom agent development, and enterprise-grade security and scalability for your AI applications leveraging weather data.

Q: Where can I find more examples of MCP servers and implementation patterns?

A: You can find more examples at https://github.com/modelcontextprotocol/servers.

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