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eurostat-mcp-server

by io.github.cyanheads

Search Eurostat Datasets

eurostat_search_datasets
Read-onlyIdempotent

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.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoPage size — maximum datasets returned per page (1–100). Default is 20. To retrieve matches beyond one page, pass the returned nextCursor back as cursor; the page size is fixed by this first call.
queryYesSearch terms — at least one non-whitespace token is required. Split on whitespace into tokens; every token must match (AND), case-insensitively, somewhere across the dataset label, theme breadcrumb, or code. Word order does not matter, so "business demography NUTS 3" or "regional economic accounts" resolve without naming a label verbatim.
cursorNoOpaque pagination cursor from a previous call's nextCursor. Omit for the first page; pass it back — with the same query — to fetch the next page of matches over a stable order. A cursor is bound to the query that produced it and to the catalogue snapshot in effect at that time, so reusing one with a different query, or after the catalogue refreshes, is rejected rather than silently paging a different result set.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoPresent when the call failed. Absent on success.
queryNoSearch terms as submitted.
datasetsNoMatching datasets for the current page, up to the requested limit.
nextStepNoSuggested next action based on these results. Populated when there is a clear follow-up call.
truncatedNoTrue when more matches remain beyond this page — pass nextCursor as cursor to fetch them.
nextCursorNoOpaque cursor for the next page of matches. Pass it back as cursor with the same query; it stops working once the catalogue refreshes. Omitted on the last page.
totalMatchesNoTotal distinct dataset codes matching the query across all pages, before the page limit.

TDQS

A4.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint, so no safety contradiction exists. The description adds valuable behavioral context by specifying the result scope: only datasets/predefined tables matched by keyword, with codes, descriptions, period coverage, and theme breadcrumbs returned.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three focused sentences: what the tool does, how to use it in the wider workflow, and its boundary of results. Every sentence contributes and no content is redundant with the annotations or schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a search/discovery tool with an output schema, strong parameter schema, and safe/read-only annotations, this description covers purpose, return contents, workflow ordering, and scope limitations. An agent knows exactly when to invoke it, how it relates to siblings, and what to do after it returns dataset codes.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, and the schema already clearly documents query, limit, and cursor semantics, including cursor staleness and pagination binding rules. The description itself adds little new parameter-level meaning, but no extra help is needed because the schema is already strong.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: 'Search the Eurostat catalogue by keyword' and lists what it returns. It also distinguishes itself from sibling tools by explaining this is the discovery step before eurostat_get_dataset_info, eurostat_query_dataset, and eurostat_download_dataset, and by explicitly excluding folders.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit workflow: search to discover dataset codes, then call get_dataset_info, and then either query a slice or download the whole dataset. It also reminds the agent that results are limited to datasets/predefined tables and folders are excluded, which prevents using this tool for non-dataset browsing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4.7/5.0
Disambiguation5/5

Each tool has a clearly distinct role: discovery, metadata lookup, dimension value lookup, inline query, bulk download, dataframe staging, and dataframe SQL. The two data-fetching tools are explicitly differentiated as slice vs. whole-dataset routes, and the dataframe tools are clearly separate from direct Eurostat queries.

Naming Consistency4/5

Six of eight tools follow a consistent eurostat_verb_noun pattern, e.g., search_datasets, get_dataset_info, query_dataset. The two dataframe tools invert this to eurostat_dataframe_describe and eurostat_dataframe_query, which is a minor deviation but still readable and predictable.

Tool Count5/5

Eight tools is a well-scoped count for the Eurostat data-access domain. Each tool covers a distinct stage in the workflow from discovery, metadata inspection, targeted querying, bulk download, and post-query analysis.

Completeness5/5

The toolset covers the full expected lifecycle: browse and search to find datasets, get metadata and dimension values to construct queries, query or download data, and stage/query results for further analysis. No significant dead ends or missing operations are evident for the stated purpose.

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