How do I register this skill with Claude?

You can register it using the 'claude mcp add' command with the stdio transport pointing to the local Python installation of the essdive-mcp server.

Can this skill visualize data locations?

Yes, it includes a tool to convert coordinates and bounding boxes into interactive map links for Google Maps, OpenStreetMap, and geojson.io.

ESS-DIVE is the U.S. Department of Energy’s (DOE) data repository for Environmental Systems Science (ESS) research.

Do I need an API token to use this skill?

While public datasets may be searchable, an ESS-DIVE API token is required to access dataset permissions and specific protected metadata tools.

What is the FLMD parsing feature?

It allows Claude to interpret File Level Metadata CSVs, which provide granular descriptions of individual files within a larger scientific dataset.

ESS-DIVE Data Explorer

Name: ESS-DIVE Data Explorer
Author: ess-dive

byess-dive

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Data Science & ML

Searches, retrieves, and parses environmental science datasets from the Department of Energy's ESS-DIVE repository.

About

The essdive-datasets skill enables Claude to interact directly with the Environmental Systems Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) API. It allows users to perform advanced searches for earth science data by keywords, creators, or providers, and retrieve comprehensive metadata for specific datasets. This skill is particularly useful for researchers and data scientists who need to discover scientific packages, manage dataset permissions, parse File Level Metadata (FLMD), and instantly generate geospatial visualization links for study sites directly within their development environment.

Key Features

Advanced dataset searching with keyword, creator, and provider filters
Automated parsing of File Level Metadata (FLMD) CSV files
1 GitHub stars
Detailed metadata and permission retrieval for scientific data packages
Coordinate-to-map conversion for Google Maps, OpenStreetMap, and GeoJSON
Support for both summary and detailed metadata output formats

Use Cases

Visualizing field site locations and bounding boxes during data exploration
Discovering environmental and soil carbon datasets for research and analysis
Automating the collection of metadata for earth science data cataloging

About

Key Features

Advanced dataset searching with keyword, creator, and provider filters
Automated parsing of File Level Metadata (FLMD) CSV files
1 GitHub stars
Detailed metadata and permission retrieval for scientific data packages
Coordinate-to-map conversion for Google Maps, OpenStreetMap, and GeoJSON
Support for both summary and detailed metadata output formats

Use Cases

Visualizing field site locations and bounding boxes during data exploration
Discovering environmental and soil carbon datasets for research and analysis
Automating the collection of metadata for earth science data cataloging