io.github.rpconroy/gdex-mcp · v0.1.0 · data-and-databases
io.github.rpconroy/gdex-mcp is healthy: it completed an MCP handshake in 711 ms and exposes 30 tools.
MCP server for the GDEX (Geoscience Data Exchange) data portal: datasets, files, metrics, subsetting
Endpoint: https://gdex-mcp.k8s.ucar.edu/mcp (streamable-http)
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| Users (last 30 days) | 0 |
| Handshake | Healthy |
| Auth needed | None |
| Tool count | 30 |
| Latency | 711 ms |
| Last checked (UTC) | 2026-10-15T08:30:10.136Z |
| Checked (UTC) | Status | Latency | Error |
|---|---|---|---|
| 2026-10-15T08:30:10.136Z | Healthy | 711 |
list_datasets | List datasets available on GDEX, with their IDs and titles. The full catalog has ~1700 datasets — far too many to return at once. Always pass `query` to filter by keyword unless the user specifically wants to browse the whole catalog page by page. Args: query: Keyword(s) to |
get_dataset_metadata | Return full metadata for a GDEX dataset (parameters, temporal range, spatial coverage, etc.). Args: dsid: Dataset ID (dNNNNNN), e.g. d083002 |
get_dataset_field | Return one metadata field for a dataset. Prefer describe_dataset when the user wants a general summary covering several of these at once (abstract, temporal, spatial_coverage, variables, data_formats, volume) — this tool is for pulling a single field, including the fields describe_d |
describe_dataset | Return a combined overview of a dataset — abstract, temporal coverage, spatial coverage, variables, data formats, and volume — in a single call. Prefer this over calling get_dataset_field repeatedly when the user wants a general summary of a dataset. If one of the underlying fields fail |
get_file_groups | Return file groups for a dataset. Pass gindex to get child groups under a parent. Groups nest (dataset -> format -> year -> month, or similar, varying by dataset) and there's no way to predict a child's gindex in advance — each group's gindex/url is dataset-specific and only knowable fr |
get_dataset_files | Return a paginated file listing for a dataset or a specific group. Depending on how deep gindex is in the group hierarchy, this returns either actual file rows or another layer of subgroup summaries — there's no way to tell in advance which you'll get. If you get subgroups, read the |
find_dataset_files | Search a dataset's file-group hierarchy for files matching a name pattern (e.g. a date like "20220808"), without ever pulling a large, context-blowing file listing. Automates the pattern described in get_file_groups: recursively calls get_file_groups, descending into every child gin |
get_filesearch_datatypes | Return the file-search datatypes available for a dataset (a subset of "grid", "cyclone_fix", "sensor"). Call this before the other filesearch_* tools to know which one(s) apply — a dataset only supports search for the datatypes it actually contains. Args: dsid: Dataset ID (d |
get_filesearch_grid_filters | Return the valid parameter/product/grid/level codes and date range for "grid" datatype file search on a dataset. Use this to discover the codes to pass to get_filesearch_grid_files, optionally narrowed by any filters you already know you want. Args: dsid: Dataset ID (dNNNNNN |
get_filesearch_cyclone_fix_filters | Return the valid date range and other filters for "cyclone_fix" datatype file search on a dataset. Args: dsid: Dataset ID (dNNNNNN), e.g. d083002 valid_datetime_min: Restrict to data valid on/after "YYYY-MM-DD HH:MM" valid_datetime_max: Restrict to data valid on/befo |
get_filesearch_sensor_filters | Return the valid date range and other filters for "sensor" datatype file search on a dataset. Args: dsid: Dataset ID (dNNNNNN), e.g. d083002 valid_date_min: Restrict to data valid on/after "YYYY-MM-DD" valid_date_max: Restrict to data valid on/before "YYYY-MM-DD" |
get_filesearch_grid_files | Search for data files containing "grid" datatype data, filtered by parameter code(s) and optionally by time range, product, grid, or level. Results are paginated; use get_filesearch_result_page with the returned result_id to fetch additional pages. Use get_filesearch_grid_filters fir |
get_filesearch_cyclone_fix_files | Search for data files containing "cyclone_fix" datatype data, optionally filtered by time range. Results are paginated; use get_filesearch_result_page with the returned result_id to fetch additional pages. Args: dsid: Dataset ID (dNNNNNN), e.g. d083002 valid_datetime_min |
get_filesearch_sensor_files | Search for data files containing "sensor" datatype data, optionally filtered by date range. Results are paginated; use get_filesearch_result_page with the returned result_id to fetch additional pages. Args: dsid: Dataset ID (dNNNNNN), e.g. d083002 valid_date_min: Restric |
get_filesearch_result_page | Return a page of results from a previous get_filesearch_*_files call, by its result_id. Use this to page through file-search results beyond the first page (see the "pagination" block of a files/results response for num_pages and next_page). Args: dsid: Dataset ID (dNNNNNN), |
get_data_access | Return data access options for a dataset — download links, Globus URLs, access methods. Args: dsid: Dataset ID (dNNNNNN), e.g. d083002 |
has_arco | Check whether Analysis-Ready Cloud-Optimized (ARCO) data is available for a dataset. For analysis tasks, call this (and check for a "Kerchunk Reference Files" group via get_file_groups) before reaching for raw data files — reading through ARCO/kerchunk references avoids downloading whol |
get_arco_variables | Return the list of ARCO variables available for a dataset. Each row's type (index 2) is either "zarr" or "reference" (kerchunk). A "reference" variable is often listed multiple times, once per kerchunk reference variant (plain, "-remote-https", "-remote-osdf", etc.) — always pick th |
search_arco_variables | Search ARCO variables by name for a dataset. As with get_arco_variables, a "reference" (kerchunk) match is often listed once per variant — always pick the "-osdf" variant's URL (reachable from anywhere), and open it with xr.open_dataset(url, engine="kerchunk", storage_options={"remo |
get_portal_metrics | Return a GDEX portal-wide metric. Args: metric: One of: volume_downloaded, unique_users, total_datasets, total_citations, gdex_volume, total_requests, top_datasets, ai_datasets |
get_dataset_metrics | Return a per-dataset metric. Args: dsid: Dataset ID (dNNNNNN), e.g. d083002 metric: One of: users_month, users_year, volume_month, volume_year |
get_staff | Return GDEX staff contacts, optionally filtered to a specific dataset. Args: dsid: Optional dataset ID. If omitted, returns all staff. |
list_request_statuses | List all subsetting request statuses for the authenticated user. Requires GDEX_TOKEN. |
check_request_status | Check the status of a specific subsetting request. Requires GDEX_TOKEN. Args: rindex: Request index/ID |
get_request_files | Return the output files for a completed subsetting request. Requires GDEX_TOKEN. Args: rindex: Request index/ID |
get_control_file_template | Return the control file template for building a subsetting request for a dataset. Args: dsid: Dataset ID (dNNNNNN), e.g. d083002 |
validate_subset_request | Check a subset request body against the dataset's control file template, without submitting anything. Use this before submit_subset_request to catch missing or unrecognized fields fast, instead of finding out from a failed API call. Args: dsid: Dataset ID (dNNNNNN), e.g. d08 |
submit_subset_request | Submit a data subset request to GDEX. Requires GDEX_TOKEN. Args: request_json: JSON string of the subsetting request body. Use get_control_file_template to get the expected structure for a dataset, or validate_subset_request to check it before |
submit_and_wait_for_request | Submit a subset request and poll its status until it finishes, fails, or timeout_s elapses — instead of calling submit_subset_request and then manually looping on check_request_status. Requires GDEX_TOKEN. GDEX's API schema doesn't document the exact status vocabulary, so "finished" |
purge_request | Delete a subsetting request and its output files. Requires GDEX_TOKEN. Args: rindex: Request index/ID to purge |