eurostat-mcp-server

Reviewed 1d ago.

• tools: 8 tools scanned
• metadata: scanned
• packages: 2 checked

No findings.

Tools (8)

• eurostat_search_datasets

  Search the Eurostat catalogue by keyword. Returns matching datasets with codes, descriptions, period coverage, and theme breadcrumbs. Use this to discover dataset codes before calling eurostat_get_dataset_info, then eurostat_query_dataset for a slice of a dataset or eurostat_download_dataset for the whole of one. Results are limited to datasets and predefined tables — folders are excluded. The catalogue joins two sources: the dissemination table of contents, and the Comext host's dataflow list, which adds the DS-* collections — detailed trade by CN8, HS, SITC, BEC and CPA, and PRODCOM — filed under "International trade in goods - detailed data (Comext)" and "Statistics on the production of manufactured goods (PRODCOM)". Comext entries report a last-update date but no period coverage or observation count. A collection on neither list, such as the legacy PRODCOM DS-056120, is not disseminated and cannot be reached through this server.

• eurostat_browse_themes

  Navigate the Eurostat theme tree. Without theme_code returns the top-level theme folders (Economy, Population, Transport, etc.) — the practical starting points. With a theme_code returns its immediate children: subtheme folders and datasets in that branch. Use this for structured discovery when you know the domain but not the dataset code, or to drill down from a broad topic to a specific dataset. Pair with eurostat_search_datasets for keyword-based discovery. The tree is the dissemination table of contents plus the Comext host's DS-* collections: detailed trade under ext_go_detail (inside ext_go, "International trade in goods") and PRODCOM under prom (inside icts, "Industry, trade and services"). A collection on neither, such as the legacy PRODCOM DS-056120, is not disseminated and appears nowhere in the tree.

• eurostat_get_dataset_info

  Fetch metadata for a Eurostat dataset: dimensions with valid values, time range, observation count, and last-update date. Call this before eurostat_query_dataset or eurostat_download_dataset to discover what dimension codes are valid (unit, na_item, geo, etc.); eurostat_download_dataset builds its positional filter key from this dimension list, so a filter naming a dimension absent here is rejected outright. Returns up to 10 sample values per dimension for orientation; use eurostat_get_dimension_values to list the full set for large dimensions. A DS-* code (detailed trade and PRODCOM, in any case) is read from the Comext dissemination host, which reports no period coverage or observation count, so timeRange and obsCount come back unreported; the first call on a large Comext collection downloads its full structure (23 MB for DS-045409) and takes longer, and repeat calls within the hour reuse it.

• eurostat_get_dimension_values

  List the valid values for a specific dimension in a Eurostat dataset (e.g., all unit codes for nama_10_gdp, all geo codes for a regional dataset). Use this when eurostat_get_dataset_info returns more values than the 10-item sample, or to confirm exact codes before querying. For the "geo" dimension, use geo_level to filter by NUTS hierarchy (country, nuts1, nuts2, nuts3). An invalid code matches nothing: eurostat_query_dataset names it in unmatchedValues, or in its no_results error when the query matched nothing at all, and Eurostat rejects it as a fault on eurostat_download_dataset; use this tool to verify codes first. At most 2,000 values come back inline — a longer list, such as the 37,069 CN8 product codes of DS-045409 or a daily time dimension, is cut there and says so. Pass canvas_id to also stage the whole list, whatever its length, as a two-column code/label table on that dataframe canvas: search it with SQL, or join it to a eurostat_download_dataset table, whose columns carry d

• eurostat_query_dataset

  Fetch statistical data from a Eurostat dataset with dimension filters. Returns a deterministic inline prefix of decoded observations with dimension codes and labels, numeric values, an OBS_FLAG status (e.g., "p" = provisional, "e" = estimated) and a separate CONF_STATUS confidentiality marker (e.g., "C" = confidential, which is usually why a value is null). preview_limit controls only that prefix; filters and period controls reduce the matched result itself. Call eurostat_get_dataset_info first to discover valid dimension codes and values. Apply filters to keep the result set manageable — large unfiltered queries may trigger an async response error. Use filters.geo for specific country/region codes, or geo_level for NUTS hierarchy filtering (mutually exclusive). Use last_n_periods for the N most recent periods without knowing the end date. Matches above 5,000 observations are staged whole when this deployment runs a dataframe canvas: call eurostat_dataframe_describe first, then eurosta

• eurostat_download_dataset

  Download a Eurostat dataset in bulk through the SDMX 2.1 TSV endpoint and stage every observation as a SQL table on the dataframe canvas — the route to a whole dataset, where eurostat_query_dataset is the route to a slice of one. The TSV wire format is roughly half the bytes of the JSON-stat body eurostat_query_dataset reads, so it reaches datasets that would otherwise time out, and it is expanded here into one row per observation. Filters take the same dimension-code map eurostat_query_dataset uses and are applied server-side by Eurostat; call eurostat_get_dataset_info first for the dimension codes and eurostat_get_dimension_values for their values. Narrow with since_period/until_period rather than asking for the most recent N periods — the TSV layout keeps a column for every period whichever is requested, so a period range is what actually shrinks the response. Transfers are bounded by a byte budget enforced while streaming: when it is spent the download stops and budgetExceeded is s

• eurostat_dataframe_describe

  List the tables staged on a Eurostat dataframe canvas, with their row counts and column names and types. Call this before eurostat_dataframe_query to learn the table and column names to write SQL against. The canvas_id comes from a eurostat_query_dataset or eurostat_download_dataset response that reported a staged table. Three tools stage tables, and they write different columns, so read the columns reported here rather than assuming. The two observation stagers keep every column flat: eurostat_query_dataset gives each dimension a code column named after the dimension (e.g. "geo") plus a label companion (e.g. "geo_label"); eurostat_download_dataset gives code columns only — the bulk endpoint carries no labels — plus a "time" column. Both write the same five measure columns — obs_value, obs_flag, obs_flag_label, conf_status, conf_status_label — carrying the same codes for the same observation, so their tables join on dimension codes and time and compare like with like. A table staged fr

• eurostat_dataframe_query

  Run a read-only SQL SELECT against tables staged on a Eurostat dataframe canvas — the way to reach observations past the 5,000-row inline cap of eurostat_query_dataset and past the inline preview of a eurostat_download_dataset bulk download, and to aggregate, group, or join across staged tables without re-fetching from Eurostat. Call eurostat_dataframe_describe first for the table and column names, which differ between the tools that stage them. Only a single SELECT statement runs: statement chaining, non-SELECT verbs, and functions that read files or external data are rejected. Columns are flat — every dimension is a code column named after the dimension, the measure is obs_value, the observation flag is obs_flag / obs_flag_label and the confidentiality marker is conf_status / conf_status_label; a "_label" companion per dimension exists only on tables eurostat_query_dataset staged. Both observation stagers write the same five measure columns with the same codes, so join their tables o