Jupyter Earth MCP Server
by Datalayer
Jupyter Earth MCP Server is a Model Context Protocol (MCP) server implementation that provides tools for geospatial analysis in Jupyter notebooks. It facilitates searching, downloading, and analyzing Earth data within a Jupyter environment.
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What is Jupyter Earth MCP Server?
The Jupyter Earth MCP Server is an implementation of the Model Context Protocol (MCP) designed to enhance geospatial analysis within Jupyter notebooks. It allows users to interact with Earth data, download it, and perform analysis using a standardized protocol.
How to use Jupyter Earth MCP Server?
To use the server, first install JupyterLab and the necessary collaboration packages. Then, start JupyterLab with a specified port and token. Configure Claude Desktop by adding the Jupyter Earth MCP server to the claude_desktop_config.json file, ensuring the server URL and token match the JupyterLab settings. The server provides tools and prompts that can be used directly within Jupyter notebooks to download and analyze Earth data.
Key features of Jupyter Earth MCP Server
Integration with Jupyter notebooks
Implementation of the Model Context Protocol (MCP)
Tools for downloading Earth data granules
Prompts for analyzing global sea level data
Compatibility with Claude Desktop
Use cases of Jupyter Earth MCP Server
Analyzing sea level rise
Downloading and processing NASA Earthdata
Performing geospatial analysis in Jupyter
Integrating geospatial data with AI models via Claude
Automating data retrieval and analysis workflows
FAQ from Jupyter Earth MCP Server
What is the Model Context Protocol (MCP)?
What is the Model Context Protocol (MCP)?
The Model Context Protocol (MCP) is a standard for connecting tools and models, allowing them to share context and data. It enables seamless integration and collaboration between different applications.
How do I configure Claude Desktop to use this server?
How do I configure Claude Desktop to use this server?
You need to add the Jupyter Earth MCP server configuration to your claude_desktop_config.json file, specifying the server URL, token, and notebook path. Ensure these settings match your JupyterLab configuration.
What data sources does this server support?
What data sources does this server support?
Currently, the server is designed to work with NASA Earthdata. It provides tools to search and download data granules from this source.
What are the system requirements for running this server?
What are the system requirements for running this server?
You need to have Docker installed to run the server. Additionally, you need JupyterLab and the required Python packages installed in your environment.
Can I use this server with other MCP-compatible applications?
Can I use this server with other MCP-compatible applications?
Yes, the server is designed to be compatible with any application that supports the Model Context Protocol. You can integrate it with other MCP-compliant tools and workflows.