# eurostat-mcp-server MCP server

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

## Links
- Registry page: https://www.getdrio.com/mcp/io-github-cyanheads-eurostat-mcp-server
- Repository: https://github.com/cyanheads/eurostat-mcp-server

## Install
- Command: `npx -y @cyanheads/eurostat-mcp-server`
- Endpoint: https://eurostat.caseyjhand.com/mcp
- Auth: Not captured

## Setup notes
- Package: Npm @cyanheads/eurostat-mcp-server v0.1.15
- Environment variable: MCP_LOG_LEVEL (default info)
- Environment variable: EUROSTAT_BASE_URL (default https://ec.europa.eu/eurostat/api/dissemination)
- Environment variable: EUROSTAT_REQUEST_TIMEOUT_MS (default 30000)
- Package: Npm @cyanheads/eurostat-mcp-server v0.1.15
- Environment variable: MCP_HTTP_HOST (default 127.0.0.1)
- Environment variable: MCP_HTTP_PORT (default 3010)
- Environment variable: MCP_HTTP_ENDPOINT_PATH (default /mcp)
- Environment variable: MCP_PUBLIC_URL
- Environment variable: MCP_AUTH_MODE (default none)
- Environment variable: MCP_LOG_LEVEL (default info)
- Environment variable: EUROSTAT_BASE_URL (default https://ec.europa.eu/eurostat/api/dissemination)
- Environment variable: EUROSTAT_REQUEST_TIMEOUT_MS (default 30000)
- Remote endpoint: https://eurostat.caseyjhand.com/mcp

## Tools
- eurostat_search_datasets (Search Eurostat 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. Endpoint: https://eurostat.caseyjhand.com/mcp
- eurostat_browse_themes (Browse Eurostat Theme Hierarchy) - 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. Endpoint: https://eurostat.caseyjhand.com/mcp
- eurostat_get_dataset_info (Get Eurostat 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. Endpoint: https://eurostat.caseyjhand.com/mcp
- eurostat_get_dimension_values (Get Eurostat Dimension Values) - List all 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). Invalid dimension_value codes silently return no data from eurostat_query_dataset, and are rejected by Eurostat as a fault on eurostat_download_dataset; use this tool to verify codes first. Endpoint: https://eurostat.caseyjhand.com/mcp
- eurostat_query_dataset (Query Eurostat Dataset) - Fetch statistical data from a Eurostat dataset with dimension filters. Returns 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), capped at 5,000 inline rows. 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. This tool fetches a slice: past the inline cap, either narrow the filters, or — on a deployment that runs a dataframe canvas — read the staged SQL table this response names in tableName with eurostat_dataframe_query rather than re-querying Eurostat. 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. Endpoint: https://eurostat.caseyjhand.com/mcp
- eurostat_download_dataset (Download Eurostat 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; the rest are reachable with eurostat_dataframe_query when this deployment runs a canvas, and are not retained when it does not. Endpoint: https://eurostat.caseyjhand.com/mcp
- eurostat_dataframe_describe (Describe Eurostat Dataframes) - 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. Endpoint: https://eurostat.caseyjhand.com/mcp
- eurostat_dataframe_query (Query Eurostat Dataframes) - 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. Endpoint: https://eurostat.caseyjhand.com/mcp

## Resources
Not captured

## Prompts
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## Metadata
- Owner: io.github.cyanheads
- Version: 0.1.15
- Runtime: Npm
- Transports: STDIO, HTTP
- License: Not captured
- Language: Not captured
- Stars: Not captured
- Updated: Jul 10, 2026
- Source: https://registry.modelcontextprotocol.io