# io.github.cyanheads/eurostat-mcp-server

> Search and query the Eurostat catalogue — EU economy, demography, trade, and NUTS regional data.

- name: io.github.cyanheads/eurostat-mcp-server
- version: 0.10.0
- connection class: R0 (autonomous)
- trust: 94/100
- quality: 70/100 (needs work)
- owner: not claimed
- descriptor: https://api.protogrid.dev/v1/servers/io.github.cyanheads%2Feurostat-mcp-server
- tools: https://api.protogrid.dev/v1/servers/io.github.cyanheads%2Feurostat-mcp-server/tools

**An agent can connect right now, no human step.** Remote endpoint, no authentication, reachable on the last probe.

## Connection (mcpServers)

```json
{
  "mcpServers": {
    "eurostat-mcp-server": {
      "type": "http",
      "url": "https://eurostat.caseyjhand.com/mcp"
    }
  }
}
```


## Trust

- hygiene: 100
- liveness: 100
- freshness: 100
- provenance: 80
- drivers: +repository +namespace-matches-repo +reachable +uptime-99% +updated-6d-ago
- Derived from observable signals (official registry feed and our own credential-free probes); no code audit performed.

## Quality 70/100 (needs work)

### protocol: 88 (weight 25)

- pass `protocol.modern`: supports 2026-07-28 (server/discover)
- pass `protocol.stateless`: answers without a session
- pass `protocol.transport`: streamable HTTP
- warn `protocol.list_ttl`: tools/list declares ttlMs 0, so clients re-fetch it on every use

### authorization: n/a (weight 15)

- n/a `auth.prm`, `auth.as_metadata`, `auth.cimd`: no remote uses OAuth
- n/a `auth.secret_in_url`: no templated URL

### tool hygiene: 79 (weight 30)

- pass `tools.descriptions`: every tool has a description
- warn `tools.description_length`: 5 tools have descriptions over 1,024 characters, which crowds the context
- pass `tools.schemas`: every tool has an object input schema
- pass `tools.annotations`: 8 of 8 tools declare readOnlyHint or destructiveHint
- fail `tools.directory_hints`: no tool declares all four of readOnlyHint, destructiveHint, idempotentHint and openWorldHint; missing: eurostat_search_datasets (destructiveHint); eurostat_query_dataset (destructiveHint); eurostat_dataframe_query (destructiveHint); …
- pass `tools.token_cost`: about 5,938 tokens to load every tool
- pass `tools.api_dump`: tools are not a one-to-one API dump

### stability: 25 (weight 15)

- warn `stability.changes`: 14 tool changes in 30 days
- fail `stability.rug_pull`: 2 tools kept their name but changed most of their description in 30 days; review before trusting them

### dependencies: n/a (weight 15)

- n/a `deps.known_vulns`, `deps.mcp_sdk_version`, `deps.resolvable`: deps.dev does not know @cyanheads/eurostat-mcp-server@0.10.0, @cyanheads/eurostat-mcp-server@0.10.0

- tools: 8, about 5,938 tokens to load them all
- tool set hash: 801877095f778f582c36ba756ba2a5f4
- tools last changed: 2026-10-15T08:20:32.974Z
- badge: [![protogrid quality](https://protogrid.dev/badge/io.github.cyanheads/eurostat-mcp-server.svg)](https://protogrid.dev/servers/io.github.cyanheads/eurostat-mcp-server)
- Checks run on what our credential-free, read-only probes observe; tools are never called and no code audit is performed.

### Tool changes

- 2026-10-15 `eurostat_download_dataset` changed (inputSchema, outputSchema)
- 2026-10-15 `eurostat_query_dataset` changed (inputSchema, outputSchema)
- 2026-10-15 `eurostat_get_dimension_values` changed (description, inputSchema, outputSchema)
  - before: 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 dimension codes only.
  - after: 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. To find one code in a long list, such as the 37,069 CN8 product codes of DS-045409, pass filter: words its code or label contains. A long list comes back a page at a time, each response held to 64,000 bytes; a page with more after it carries nextCursor — pass it back as cursor for the next page. 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 dimension codes only.
- 2026-10-15 `eurostat_get_dataset_info` changed (outputSchema)
- 2026-10-15 `eurostat_browse_themes` changed (outputSchema)
- 2026-10-15 `eurostat_search_datasets` changed (inputSchema, outputSchema)
- 2026-09-25 `eurostat_dataframe_query` changed (description, inputSchema)
  - before: 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 two stagers. 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 stagers write the same five measure columns with the same codes, so join their tables on dimension codes and time and compare obs_flag or conf_status across them directly.
  - after: 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 on dimension codes and time and compare obs_flag or conf_status across them directly; a DS-* table also carries obs_value_text, a value published as text (e.g. a PRODCOM unit "KG"). A value list eurostat_get_dimension_values staged has two columns, code and label: join it to the code column of a download (e.g. JOIN df_x g ON d.geo = g.code) to label that table.
- 2026-09-25 `eurostat_dataframe_describe` changed (description, inputSchema)
  - before: 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. Every observation column is flat, but the two stagers write different dimension columns, so read the columns reported here rather than assuming: 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 tables from the two stagers join on dimension codes and time and compare like with like.
  - after: 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 from a DS-* dataset (Comext detailed trade, PRODCOM) adds obs_value_text, holding a value Eurostat published as text, such as a PRODCOM quantity unit. eurostat_get_dimension_values, given a canvas_id, stages one dimension's value list as two columns, code and label, which labels a download's code column through a join (e.g. d.geo = g.code).
- 2026-09-25 `eurostat_download_dataset` changed (inputSchema, outputSchema)
- 2026-09-25 `eurostat_query_dataset` changed (inputSchema, outputSchema)

Full history: https://api.protogrid.dev/v1/servers/io.github.cyanheads%2Feurostat-mcp-server/changes

## Dependencies

- npm @cyanheads/eurostat-mcp-server@0.10.0: unknown
- npm @cyanheads/eurostat-mcp-server@0.10.0: unknown

Dependency graphs from deps.dev; advisories from OSV.dev, including the GitHub Advisory Database and the PyPI Advisory Database; all CC BY 4.0.

## Remotes

- https://eurostat.caseyjhand.com/mcp (streamable-http, auth none, reachable true, uptime30d 0.9915254)

## Packages

- npm @cyanheads/eurostat-mcp-server@0.10.0
- npm @cyanheads/eurostat-mcp-server@0.10.0

## Tools (8)

- `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_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 from a DS-* dataset (Comext detailed trade, PRODCOM) adds obs_value_text, holding a value Eurostat published as text, such as a PRODCOM quantity unit. eurostat_get_dimension_values, given a canvas_id, stages one dimension's value list as two columns, code and label, which labels a download's code column through a join (e.g. d.geo = g.code).
- `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 on dimension codes and time and compare obs_flag or conf_status across them directly; a DS-* table also carries obs_value_text, a value published as text (e.g. a PRODCOM unit "KG"). A value list eurostat_get_dimension_values staged has two columns, code and label: join it to the code column of a download (e.g. JOIN df_x g ON d.geo = g.code) to label that table.
- `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 set, leaving a prefix of the dataset rather than an error. Only preview_limit rows come back inline. When a table is staged, call eurostat_dataframe_describe first to confirm its columns, then eurostat_dataframe_query; without a canvas, rows past the preview are not retained.
- `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. To find one code in a long list, such as the 37,069 CN8 product codes of DS-045409, pass filter: words its code or label contains. A long list comes back a page at a time, each response held to 64,000 bytes; a page with more after it carries nextCursor — pass it back as cursor for the next page. 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 dimension codes only.
- `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 eurostat_dataframe_query. Matches at or below 5,000 are never staged. When the target is a whole dataset rather than a slice, eurostat_download_dataset reads the SDMX bulk endpoint instead and is the cheaper route.
- `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.