Find statistical data cubes in LINDAS by topic.

The entry point. Returns cube URIs you then pass to get_cube_structure. By default only the newest published version of each cube is returned; set latest_only=False to see every version.

Check truncated before you conclude anything from the result. returned alone cannot tell a complete answer from a first page.

• truncated: false — cubes holds every cube that matched. You may say so.

• truncated: true — more cubes matched than you got back, or that could not be ruled out cheaply. Do NOT report the result as the complete set, and do NOT answer "there are N cubes about X" from returned.

On truncated: true, widen in this order:

1. Raise limit (up to 100) and search again — usually enough.

2. Still truncated at 100? Narrow instead of paging: add creator_uri from list_publishers to ask one federal body at a time.

3. Set latest_only=False if you specifically need historical versions. It widens rather than narrows — every version becomes its own hit — so use it to inspect a cube's history, not to escape truncation.

total_matched carries the exact number when one is available and null otherwise. null is not an error and not zero: with latest_only=true the count the store can give cheaply counts cube versions, while this tool returns version-collapsed cubes (measured: 127 versions collapse to 35 cubes for "wald"), so no comparable number exists. truncated is still reliable there — prefer it over guessing from total_matched.

Args: query: Topic term, e.g. "Wald", "Abfluss", "Energie". Matched against cube names and descriptions in the chosen language. language: Language for names and descriptions. creator_uri: Restrict to one publishing body (from list_publishers). limit: Maximum cubes to return (1-100). latest_only: Collapse versions to the newest per cube.

Read a cube's dimensions and measures — what the cube contains.

Tells you which dimensions you can filter on (KeyDimension), which values are measured (MeasureDimension), and which dimensions carry code lists. It also returns the licence, which is frequently a Fedlex URI you can resolve with fedlex-mcp.

Call this to understand a cube before reading it, and to write a run_sparql query against it. It is NOT a prerequisite for readable data: query_cube_observations fetches the structure itself and resolves labels on its own. Note that this result reports only whether a dimension has a code list (has_codelist), not the list's entries — so calling it first does not help you decode raw codes either.

Args: cube_uri: A cube URI from search_cubes. language: Language for dimension names and description.

Read the actual data points of a cube, with codes resolved to labels.

This is phase 2. Values are returned keyed by human-readable dimension names, and coded dimension values (e.g. region "1805") are replaced by their labels (e.g. "Alpennordhang") unless you turn that off.

For large cubes this reads only the first limit observations. LINDAS has no cheap way to filter observations server-side by arbitrary dimension value, so heavy analytical slicing belongs in run_sparql.

Args: cube_uri: A cube URI from search_cubes. language: Language for labels. limit: Maximum observations to return (1-500). resolve_labels: Replace coded values with human labels.

List the federal bodies that publish cubes, with cube counts.

Returns creator URIs you can pass to search_cubes to restrict a search to one authority.

Resolve a Swiss municipality to its LINDAS URI and BFS number.

The BFS commune number is the join key across the whole portfolio: the same number identifies the municipality in swiss-statistics-mcp, zurich-opendata-mcp and any cube that references a place. In LINDAS the URI is literally ld.admin.ch/municipality/.

Args: name_or_bfs: A municipality name ("Zürich") or a BFS number ("261"). language: Language for the name.

Run a raw SPARQL SELECT query. Advanced escape hatch — use sparingly.

Prefer the structured tools. This exists for analytical queries the guarded tools cannot express (cross-cube joins, aggregations, custom filters).

Guardrails, learned from probing: LINDAS times out on unanchored scans, so always anchor on a known class such as ?x a <https://cube.link/Cube>. A bare SELECT * WHERE { ?s ?p ?o } will time out. This tool caps the result at 500 rows and the runtime at 30 seconds.

Args: query: A complete SPARQL SELECT query, including its own PREFIX lines.

Check whether the LINDAS SPARQL endpoint is reachable.

Returns an evaluable status even on failure, so an agent can tell "no data matched" apart from "the endpoint is down".