Frequently Asked Questions about the Celestial Object Calculation MCP Server

Q: What is the purpose of the Celestial Object Calculation MCP Server? A: This MCP Server calculates the altitude, azimuth, rise, and set times of celestial objects for any location on Earth, with optional light pollution analysis. It provides AI models with contextual data about the position of celestial objects.

Q: What celestial objects are supported by this MCP Server? A: The server supports solar system objects (Sun, Moon, planets), stars (e.g., Sirius), and deep-space objects (e.g., Andromeda Galaxy, Orion Nebula).

Q: How does the MCP Server handle time zones? A: The MCP Server is time zone aware and can operate with both local and UTC times, ensuring accurate calculations regardless of the user’s location.

Q: What is light pollution analysis, and how does it work? A: Light pollution analysis involves loading and analyzing light pollution maps (GeoTIFF format) to assess the impact of artificial light on astronomical observations. This helps optimize observation sites.

Q: What are the key features of the MCP Server? A: Key features include altitude/azimuth calculation, rise/set times determination, light pollution analysis, support for various celestial objects, and time zone awareness.

Q: How can I install the MCP Server? A: You can install the MCP Server using pip with the command: pip install astropy pytz numpy astroquery rasterio geopy.

Q: How do I calculate the altitude and azimuth of a celestial object using the server? A: You can use the celestial_pos function, providing the object name, observer location, and time as inputs. The function returns the altitude and azimuth in degrees.

Q: How do I determine the rise and set times of a celestial object? A: Use the celestial_rise_set function, providing the object name, observer location, and date as inputs. The function returns the rise and set times as UTC Time objects.

Q: Can I use this MCP server with UBOS AI Agent Development Platform? A: Yes, the MCP Server is specifically designed to integrate with the UBOS platform, allowing AI Agents to access real-time celestial data for enhanced decision-making and automation.

Q: What are some potential use cases for this MCP Server? A: Use cases include optimizing astronomical observations, predictive agriculture, navigation, renewable energy forecasting, search and rescue operations, and security surveillance.

Q: How do I load and analyze light pollution maps? A: Use the load_map function, providing the path to the GeoTIFF file. The function returns the data, bounds, CRS, and transform for light pollution analysis.

Q: What is the API reference for the MCP Server? A: The API includes functions like celestial_pos, celestial_rise_set, and load_map, each with specific inputs and return values for celestial calculations and light pollution analysis.

Q: What future enhancements are planned for the MCP Server? A: Future enhancements include adding support for comets/asteroids, optimizing SIMBAD queries for offline use, and integrating light pollution data into visibility predictions.