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dynamical.org Weather & Climate Catalog

io.github.dynamical-org/mcpVersion 0.1.1

Search dynamical.org's open STAC catalog of weather & climate datasets (GFS, ECMWF, HRRR).

Status

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Last checked
Nov 14, 2026, 14:50 UTC
Latency
539 ms
Remotes responding
1 of 1
Sign-in
No sign-in
Hosting
Hosted outside the EU (detected)
Registry data as of
Nov 14, 2026, 21:12 UTC

Data from the official MCP Registry, checked by run.zero. How we check

Connect

Streamable HTTP
https://mcp.dynamical.org/mcpResponds539 ms
No sign-in

Claude Code

claude mcp add --transport http dynamical-org https://mcp.dynamical.org/mcp

Claude Desktop and claude.ai

Settings > Connectors > Add custom connector
Name: dynamical-org
Remote MCP server URL: https://mcp.dynamical.org/mcp

Cursor

{
  "mcpServers": {
    "dynamical-org": {
      "url": "https://mcp.dynamical.org/mcp"
    }
  }
}

VS Code

code --add-mcp '{"name":"dynamical-org","type":"http","url":"https://mcp.dynamical.org/mcp"}'

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Tools

4 tools

Tools of dynamical.org Weather & Climate Catalog
Read-only
Idempotent
Open world
get_access_patternGet the storage URI and working code for opening a dynamical.org dataset's data. dynamical.org publishes a Python package, `dynamical-catalog`, that reads the STAC catalog itself to resolve and open a dataset -- it's the recommended access pattern because it can't go stale even if the underlying storage format or location changes. This tool also returns the dataset's low-level storage details (from the STAC asset, fetched live) and a lower-level xarray/fsspec snippet for callers who need direct access instead of the wrapper package. Args: collection_id: A STAC collection id, e.g. "noaa-gfs-forecast". Use search_catalog to discover ids. Returns: A dict with the recommended `dynamical_catalog.open(...)` snippet, a `worked_example` pulled from the collection's own STAC metadata when one is published, the raw asset URI/type/storage options, and a generated low-level open snippet (icechunk/zarr/geoparquet, chosen from the asset's declared type). Raises ValueError (listing valid ids) if collection_id is unknown. Not declaredYesNot declaredYes
get_dataset_infoGet documentation, spatial/time resolution, domain, and update cadence for one dynamical.org dataset. dynamical.org/catalog is itself rendered from this same STAC catalog, so this tool fetches the collection document live (short TTL cache) rather than relying on anything baked into this server -- it's always as fresh as the STAC catalog itself. Args: collection_id: A STAC collection id, e.g. "noaa-gfs-forecast", "noaa-hrrr-analysis", or "ecmwf-aifs-ens-forecast". Use search_catalog to discover ids. Returns: A dict with title/model name, prose descriptions, spatial and time domain/resolution, forecast range (for forecast datasets), license and attribution, the dataset's variables, and links to its docs page and example notebooks. Raises ValueError (listing valid ids) if collection_id is unknown. Not declaredYesNot declaredYes
list_recent_runsCheck run freshness and arrival status for a dynamical.org forecast dataset, from the same public feed status.dynamical.org's dashboard polls. Only forecast collections are pipeline-monitored today (analysis collections like noaa-gfs-analysis or noaa-mrms-conus-analysis-hourly aren't yet tracked by this feed). Args: collection_id: A STAC collection id, e.g. "noaa-gfs-forecast". limit: Maximum number of recent runs to return, most recent first (default 10). Returns: A dict with the overall pipeline `sla_status`, this product's cadence and next expected init/completion time, typical latency stats, and up to `limit` recent runs (`init_time`, `status`, `completion_pct`, `on_timedness`, arrival/latency timestamps). If collection_id isn't pipeline-monitored, returns `monitored`: False plus the list of collection ids that are. Not declaredYesNot declaredYes
search_catalogSearch dynamical.org's STAC catalog of cloud-optimized weather and climate datasets. Matches against each dataset's model name, description, spatial/time domain and resolution, forecast range, and variable names -- so a query can be a model ("GFS"), a variable ("precipitation", "temperature_2m"), a region ("continental US", "global"), or a resolution ("3km", "0.25 degree"). Results are ranked by number of matching terms. Args: query: Free-text search terms, e.g. "hourly precipitation CONUS" or "ECMWF ensemble forecast". limit: Maximum number of results to return (default 5). Returns: {"query": ..., "results": [{"collection_id", "title", "model_name", "description_summary", "spatial_domain", "spatial_resolution", "matched_variables", "score"}, ...]}, most relevant first. Pass a result's collection_id to get_dataset_info, get_access_pattern, or list_recent_runs. Not declaredYesNot declaredYes

Details

Registry status
Active
Published
Jul 6, 2026
Updated
Jul 6, 2026
Repository
Not given
Categories (suggested)
Data and analyticsSuggested categories are assigned automatically from the registry text and may be wrong. Verified operators can correct them.
GDPR
Not declared

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