Remote MCP server to run your Atako AI agents: chat, projects, files, integrations and channels.
- Passed: Handshake
- Passed: Tools listed
- Passed: Updated recently
Median latency 132 ms · Last checked
Explore
Evidence for your next connection.
Independent measurements of remote MCP servers. Every observation has a timestamp.
Read-only probesMCP server · Code & DevOps
Search and query the Eurostat catalogue — EU economy, demography, trade, and NUTS regional data.
0 failed · 8 not measured
Median of successful probes over 7 days
Share of countable probes over 30 days, including daily rollups. Auth challenges are excluded.
Tool definitions returned by this server
Independent monitoring
Responded
The server completed its last measured handshake. This is an observation, not a guarantee.
Last checked| Test area | Passed | Failed | Unmeasured |
|---|---|---|---|
ConnectionCan a client connect and discover tools? | 5 | 0 | 0 |
Reliability & speedDoes it respond consistently and quickly? | 0 | 0 | 4 |
Access & authenticationWhat is required to use this server? | 1 | 0 | 2 |
Tool qualityAre the tool definitions usable by an agent? | 4 | 0 | 0 |
Publisher identityCan the publisher be traced to its source? | 4 | 0 | 2 |
Unmeasured means there is not enough evidence to decide. How these checks work
Start using io.github.cyanheads/eurostat-mcp-server
Choose your client, copy the configuration, then enable the server in your client’s MCP settings.
Run this command in your terminal, then restart Claude Code.
Claude Code
claude mcp add --transport http io-github-cyanheads-eurostat-mcp-server https://eurostat.caseyjhand.com/mcpCapabilities
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.
DiscoveredList 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 columns code and label, plus level for geo (NULL for a code with no NUTS level), which labels a download's code column through a join (e.g. d.geo = g.code). A geo list staged without geo_level holds every level, aggregates and regions beside the countries they contain, so filter level before aggregating.
DiscoveredRun a read-only SQL SELECT against tables staged on a Eurostat dataframe canvas, reaching observations beyond an inline preview and aggregating or joining tables without re-fetching Eurostat. Call eurostat_dataframe_describe first for table and column names. Only a single SELECT runs: statement chaining, non-SELECT verbs, and functions reading files or external data are rejected. Columns are flat: dimension codes, obs_value, obs_flag / obs_flag_label, and conf_status / conf_status_label. Tables eurostat_query_dataset staged also carry dimension _label companions; DS-* tables also carry obs_value_text for published text values. Join observation tables on dimension codes and time. A staged dimension value list has code and label columns, plus level for geo; join it to an observation dimension code to add labels. A geo list staged without geo_level holds every level, and aggregates and regions overlap the countries they contain, so filter level (e.g. g.level = 'country') before summing or averaging. Returns every complete row the canvas supplies, bounded only by the canvas row limit; nested cells render as lossless JSON. A row-limit cut sets truncated and adds a notice: page the same deterministic SELECT over unchanged tables with a total ORDER BY and LIMIT/OFFSET, advancing by actual rowCount. Restart an unordered first page sorted at offset zero; tied keys need tie-breakers. Volatile SQL and changing or expired tables cannot provide stable paging.
DiscoveredDownload a Eurostat dataset in bulk through the SDMX 2.1 TSV endpoint and stage it 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 non-blank TSV cell, including the unflagged ":" cells that mark a period a series lacks or a period of a frequency it has no observation of. 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 decoded-byte budget enforced while streaming: complete rows within the allowed prefix are retained with budgetExceeded set; a budget too small for a usable row fails as byte_budget_exceeded with narrowing guidance. 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.
DiscoveredFetch 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.
DiscoveredList the valid values for a dimension in a Eurostat dataset, preserving value codes and labels exactly. Use this when eurostat_get_dataset_info returns more values than its sample, or to confirm exact filter codes before querying. Dimension identifiers match exactly first, then case-insensitively; TIME_PERIOD aliases time. For geo, use geo_level to select the NUTS hierarchy (country, nuts1, nuts2, nuts3). To find codes in a long list, pass filter: words its code or label contains. To list the codes under a parent, pass code_prefix: the codes starting with it, ignoring case, such as one country's regions (geo_level nuts2, code_prefix DE) or the CN codes under a heading; aggregates outside the code tree are not reached. Pages default to 25 values, maximum 1,000; pass nextCursor back as cursor for the next page with the same dataset, dimension, geo level, filter and code_prefix. Canonical and alias dimension spellings resume the same list. Pass canvas_id on the first call to also stage the dimension's whole list as a table, whatever filter, code_prefix or limit: columns code and label, plus level for geo. For geo, omitting geo_level stages every level, aggregates, countries and regions together, and an explicit geo_level only that level. Inspect that table with eurostat_dataframe_describe, then search or join it with eurostat_dataframe_query.
DiscoveredFetch 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 dataset time positions without knowing the end date; a notice names selected periods with no populated cells for the slice. Set stage=true to stage the whole match at any size on a canvas-enabled deployment; matches above 5,000 observations stage automatically. Call eurostat_dataframe_describe first, then eurostat_dataframe_query. 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.
DiscoveredSearch the Eurostat catalogue by keyword. Returns matching datasets with codes, descriptions, period coverage, and theme breadcrumbs. Matches are ordered by where the words were found: first datasets whose label contains the query as a phrase beginning at the start of a word, then those whose label or code contains every word, then those that match a word only through their theme breadcrumb, each group in table-of-contents order. When no dataset's label, theme breadcrumb, or code holds every word, a query of up to 10 distinct words also has the words a dataset lacks looked for at the start of a word in the English labels of the dimension values Eurostat lists for it (time excluded); those rows carry matchedValues, whose codes are the filters eurostat_query_dataset takes. 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.
DiscoveredRecent measurements
| Checked | Result | Response | Tools |
|---|---|---|---|
| Connected | 1074 ms | 8 |