dynamical.org Weather & Climate Catalog
Search dynamical.org's open STAC catalog of weather & climate datasets (GFS, ECMWF, HRRR).
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质量与安全性
基于对工具定义和协议合规性的自动分析。
上下文开销
这是每次将服务器的工具加载到模型上下文窗口时所消耗的大致 token 数。数值越高,可用于其他任务的注意力就越少。
安装
一键安装
将以下内容添加到你的 `claude_desktop_config.json` 文件中:
{
"mcpServers": {
"mcp": {
"url": "https://mcp.dynamical.org/mcp"
}
}
}远程端点
https://mcp.dynamical.org/mcpstreamable-http它能做什么
工具清单
工具(4)
🟢get_access_pattern(collection_id)
Get 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.
输入模式
{
"type": "object",
"properties": {
"collection_id": {
"title": "Collection Id",
"type": "string"
}
},
"required": [
"collection_id"
],
"title": "get_access_patternArguments"
}输出模式
{
"type": "object",
"additionalProperties": true,
"title": "get_access_patternDictOutput"
}🟢get_dataset_info(collection_id)
Get 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.
输入模式
{
"type": "object",
"properties": {
"collection_id": {
"title": "Collection Id",
"type": "string"
}
},
"required": [
"collection_id"
],
"title": "get_dataset_infoArguments"
}输出模式
{
"type": "object",
"additionalProperties": true,
"title": "get_dataset_infoDictOutput"
}🟢list_recent_runs(collection_id, limit)
Check 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.
输入模式
{
"type": "object",
"properties": {
"collection_id": {
"title": "Collection Id",
"type": "string"
},
"limit": {
"default": 10,
"title": "Limit",
"type": "integer"
}
},
"required": [
"collection_id"
],
"title": "list_recent_runsArguments"
}输出模式
{
"type": "object",
"additionalProperties": true,
"title": "list_recent_runsDictOutput"
}🟢search_catalog(query, limit)
Search 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.
输入模式
{
"type": "object",
"properties": {
"query": {
"title": "Query",
"type": "string"
},
"limit": {
"default": 5,
"title": "Limit",
"type": "integer"
}
},
"required": [
"query"
],
"title": "search_catalogArguments"
}输出模式
{
"type": "object",
"additionalProperties": true,
"title": "search_catalogDictOutput"
}社区
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