| list_eo_catalogsA | Lists the Earth observation STAC catalogs registered on this server. The registry is data-driven (config/catalogs.yaml): today it contains
Element84 Earth Search over AWS Open Data
(https://earth-search.aws.element84.com/v1) with its searchable
modalities, curated collections and topic keywords.
Usage: Call once to see where EO data can be discovered from before
using `search_eo_datasets` / `search_eo_scenes`.
Returns:
--------
Dictionary containing:
- catalogs: Registered catalogs with id, name, URL, description,
modalities, common collections and supported topics.
|
| search_eo_datasetsA | Searches Earth observation DATASETS (STAC collections) by keyword. Performs collection-level search on the Earth Search STAC API
(AWS Open Data). Queries hit the topics map first ('flood' -> Sentinel-1
+ Sentinel-2, 'dem' -> Copernicus DEM...), then fall back to keyword
matching against live collection metadata; every hit is classified by
sensor modality (optical / radar / elevation).
Usage: Start here for dataset-level discovery ("find me flood/burn
scar/terrain datasets"). Then use the returned collection ids with
`search_eo_scenes`, or jump straight to `create_geocroissant_from_stac`
to get GeoCroissant metadata.
Returns:
--------
Dictionary containing:
- matched_topics: Topic-map hits for the query.
- count: Number of matching collections found.
- collections: Matches with catalog, collection id, title,
description snippet, modality, license and temporal extent.
|
| search_eo_scenesA | Searches satellite SCENES inside a bounding box on Earth Search. Executes a real STAC item search (pystac-client) against
https://earth-search.aws.element84.com/v1 filtered by spatial extent,
time range and cloud cover. Scenes are the individual acquisitions
(tiles/granules) that become records of a GeoCroissant dataset.
Usage: Use after `search_eo_datasets` (or directly with known
collections) to check actual data availability for an area of interest.
Feed promising results into `create_geocroissant_from_stac`.
Returns:
--------
Dictionary containing:
- scene_count and scenes: Per-scene id, collection, acquisition
datetime, platform, cloud cover, native EPSG and asset keys.
|
| validate_croissantA | Validates a Croissant or GeoCroissant JSON-LD document. Runs the official MLCommons ``mlcroissant`` validator: JSON syntax check,
JSON-LD expansion, structure-graph construction (FileObjects/FileSets,
RecordSets, Fields, sources & joins) and full schema conformance checks.
Usage: Call this tool whenever a dataset description is created or edited,
BEFORE publishing it, and after any modification of an existing file.
Works for both plain Croissant documents and documents using the
GeoCroissant extension (`geocr:` properties).
Returns:
--------
Dictionary containing:
- valid: True when the document passes validation.
- errors: Blocking errors reported by the library (empty when valid).
- warnings: Non-blocking recommendations (e.g. missing license).
- is_geospatial: Whether GeoCroissant conformance is declared.
- conforms_to / dataset_name: Extracted metadata when loadable.
|
| inspect_geocroissantA | Inspects a Croissant/GeoCroissant document and returns a structured summary. Parses the document through the ``mlcroissant`` library (which also acts as
a strict syntax/schema check - invalid documents are rejected) and returns
a structured digest: core metadata, GeoCroissant extension properties
(CRS, resolutions, band configuration, spectral bands, record endpoint...),
distribution entries (FileObjects/FileSets with URLs, formats, hashes),
and every RecordSet with its Fields (data types, array shapes,
source/extract/transform chains).
Usage: Use this tool to READ and UNDERSTAND a dataset description before
consuming it, comparing datasets, or planning how to load records.
Returns:
--------
Dictionary containing:
- name/description/license/version/conformsTo and other core metadata.
- geospatial: All declared `geocr:` extension properties.
- distribution: FileObject/FileSet entries.
- record_sets: RecordSets with nested fields and geo properties.
|
| get_structure_graphA | Extracts the internal structure graph of a Croissant document. Builds the directed multigraph that ``mlcroissant`` uses internally for
static analysis: nodes are Metadata / FileObject / FileSet / RecordSet /
Field objects and edges connect fields to their data sources, record sets
to their fields, files to archives they are contained in, and referenced
(foreign-key) fields.
Usage: Use this tool to reason about dataset lineage and dependencies,
e.g. "which files feed this field?", "what does this join look like?",
or to explain a dataset's architecture before writing loading code.
Returns:
--------
StructureGraph containing:
- nodes: Every node with @id, type, name and parent @id.
- edges: Directed edges as {source, target} @id pairs.
|
| list_record_setsA | Lists the RecordSets of a Croissant/GeoCroissant document. A RecordSet is a collection of records (rows/examples) produced by
applying the declared extraction pipeline to the distribution. This tool
returns each RecordSet's @id, name, description, key fields, enumeration
flag, number of inline records/examples and its Fields with their data
types and source chains.
Usage: Call this tool to discover what data a dataset exposes and which
RecordSet names to pass to `get_records_preview`.
Returns:
--------
List of dictionaries, one per RecordSet, each including:
- @id: The RecordSet identifier used by other tools.
- fields: Nested field summaries (dataType, isArray/arrayShape,
source extract/transform chain, geo band properties).
|
| get_records_previewA | Materializes the first records of a RecordSet by executing the data pipeline. This tool runs the real ``mlcroissant`` operation graph: it downloads (or
resolves locally) the declared FileObjects/FileSets, applies extracts and
transforms, and yields actual records - exactly what
``Dataset.records(record_set)`` yields in Python.
Usage: Use it to preview/sample a dataset's actual data before writing
training code, or to sanity-check that a generated Croissant description
produces the expected columns and values.
IMPORTANT: For remote distributions this may download data; keep `limit`
small on large datasets. Datasets with inline `cr:data` return those rows
directly without downloads.
Returns:
--------
RecordsPreview containing:
- record_set: The RecordSet @id that was read.
- columns: Column names found across returned records.
- rows: List of records keyed by fully-qualified field ids.
- truncated: True if more records exist beyond `limit`.
|
| extract_distribution_urlsA | Extracts downloadable URLs from a Croissant document's distribution. Collects the `contentUrl` of every FileObject together with its encoding
formats, sizes and checksums, plus FileSet include patterns and archive
containers. These are the direct access points for the dataset bytes.
Usage: Use this tool to obtain concrete download links (e.g. GeoTIFF /
COG / ZIP assets) for ingestion code without parsing the JSON manually.
Returns:
--------
DistributionUrls containing:
- urls: One entry per distribution item (name, type, contentUrl,
encodingFormat, md5/sha256, includes/containedIn when present).
- count: Number of distribution items with at least one URL.
|
| create_geocroissant_scaffoldA | Generates a validated GeoCroissant JSON-LD scaffold from parameters. Produces a standards-conformant starting point modeled on the official
GeoCroissant example: correct @context (including the `geocr` prefix),
dual conformance (`croissant/1.1` + `geocr`), schema.org spatial/temporal
coverage, GeoCroissant properties (CRS, resolutions, band configuration,
spectral bands), distribution entries and a RecordSet wired to them via
proper cr:source/cr:extract declarations.
The generated document is then parsed and checked by the real
``mlcroissant`` validator, so `valid=True` means the scaffold already
passes the official library checks.
Usage: Call FIRST when creating new dataset metadata, then edit the
returned JSON-LD for domain specifics and re-check with
`validate_croissant`. Use `inspect_geocroissant` afterwards to review it.
Returns:
--------
ScaffoldResult containing:
- valid: Whether the scaffold passed mlcroissant validation.
- json_ld: The generated document.
- errors/warnings: Library messages when not fully clean.
- path: Output file path when output_filename was given.
|
| create_geocroissant_from_stacA | Searches live EO data and generates VALIDATED GeoCroissant metadata from it. This is the flagship end-to-end pipeline of this server:
1. Runs a real STAC search (bbox + collections + datetime + cloud cover).
2. Derives GeoCroissant properties from the results: schema.org spatial/
temporal coverage, CRS (EPSG:4326), record endpoint, band
configuration and spectral band metadata from `eo:bands`
(micrometers converted to nanometers), distribution FileObjects for
direct asset URLs, and a RecordSet with one inline row per scene.
3. Validates the document through the official `mlcroissant` library
before returning it.
Usage: THE tool for turning discovered EO data into GeoCroissant.
After generation use `inspect_geocroissant`, `get_records_preview`
and `extract_distribution_urls` on the output.
Returns:
--------
Dictionary containing:
- valid/errors/warnings: mlcroissant validation outcome.
- json_ld: The generated GeoCroissant document.
- path: Output file path when output_filename was given.
- search_summary: What was searched and how many scenes matched.
|
| get_geocroissant_spec_referenceA | Returns the GeoCroissant specification reference documentation. Provides the vocabulary cheat sheet distilled from the official GeoCroissant
specification: namespace IRIs and prefixes, conformance declarations, every
`geocr:` property with expected types/domains/cardinality, the canonical
JSON-LD @context, a full sample document, and Python snippets for the
``mlcroissant`` API (load, validate, iterate records).
Usage: Read this ONCE before authoring or editing GeoCroissant documents so
property names, types and cardinalities match the specification exactly.
Then use `create_geocroissant_scaffold` and `validate_croissant`.
Returns:
--------
Markdown-formatted reference documentation for the requested topic.
|
