<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/c2b5b05f548d4f1492d5c107f0c48dbc&quot; frameborder=&quot;0&quot; width=&quot;1920&quot; height=&quot;1440&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1440</height><width>1920</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1440</thumbnail_height><thumbnail_width>1920</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/c2b5b05f548d4f1492d5c107f0c48dbc-598a84f02de7e74e.gif</thumbnail_url><duration>60.3603</duration><title>Analyzing Sea Level Rise with AI-Powered Geospatial Tools and Jupyter</title><description>This demo showcases how Model Context Protocol (MCP) simplifies geospatial analysis by integrating AI-powered tools for data search, retrieval, and processing. See how MCP enables seamless access to NASA Earth data and automates Python code generation in Jupyter Notebooks for efficient geospatial analysis.</description></oembed>