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datafordeler-dar

by aneal99
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TypeScript
Remote

Run a raw DAR GraphQL query (API key)

dar_graphql
Read-onlyIdempotent

Send custom GraphQL queries to Datafordeler DAR v2 to retrieve Danish addresses, streets, postcodes, and WGS84 coordinates; requires DATAFORDELER_API_KEY.

Instructions

Send any GraphQL query to https://graphql.datafordeler.dk/DAR/v2. REQUIRES DATAFORDELER_API_KEY.

Entities: DAR_Adresse, DAR_Husnummer, DAR_NavngivenVej, DAR_NavngivenVejKommunedel, DAR_NavngivenVejPostnummer, DAR_Postnummer, DAR_SupplerendeBynavn, DAR_Adressepunkt, DAR_Events.

Rules the service enforces:

  • Every entity query needs virkningstid and/or registreringstid (ISO timestamp), or a where filter on id_lokalId. Pass BOTH set to the current time to get the current state; with only one you also get superseded versions.

  • Filters: where: { field: { eq | in } }. startsWith exists only on adgangsadressebetegnelse, adressebetegnelse, vejnavn, postnr and navn, and is case-sensitive. Dates and ints also take gt/gte/lt/lte. Geometry fields take spatial filters (intersects, within, contains ...) with { wkt, crs: 25832 }.

  • Paging: first (max 1000, default 100) and after (cursor); read pageInfo { endCursor hasNextPage }.

  • References are ids, not nested objects: DAR_Husnummer.navngivenVej, .postnummer and .adgangspunkt hold UUIDs; fetch coordinates from DAR_Adressepunkt { position { wkt crs } }.

  • Field names with æ/ø/å use ae/oe/aa (doerbetegnelse, virkningsaktoer).

Example: query { DAR_Husnummer(first: 5, virkningstid: "2026-10-01T12:00:00Z", registreringstid: "2026-10-01T12:00:00Z", where: { adgangsadressebetegnelse: { startsWith: "Rentemestervej 8" }, status: { eq: "3" } }) { pageInfo { endCursor hasNextPage } nodes { id_lokalId adgangsadressebetegnelse status } } }

Returns the raw { data, errors } envelope. Use dar_get_graphql_schema to discover fields.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesGraphQL query document.
variablesNoOptional GraphQL variables object.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.7/5.0
Behavior5/5

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

Annotations cover the safety profile (readOnly/openWorld/idempotent), and the description adds substantial context beyond them: the API key requirement, the service-enforced virkningstid/registreringstid rule and its consequence (superseded versions), paging caps (first max 1000, default 100), the { data, errors } envelope, and reference-vs-nested-object behavior. This is exactly the kind of behavioral detail an agent cannot infer from annotations.

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?

Despite its length, it is front-loaded (purpose, endpoint, auth) and then organized into a scannable rules block plus a complete example and return-shape note. Every line carries operational information the agent needs to build a valid query.

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?

With no output schema, the description compensates by describing the raw return envelope, and it covers auth, entity inventory, mandatory filters, paging, spatial filters, and field-name quirks. Nothing an agent needs to issue a correct first query appears to be missing.

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

Parameters4/5

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

Schema coverage is 100% for the two parameters (query, variables), so the schema baseline already carries the parameter contract. The description goes further by specifying what the query string must contain (entity names, required time filters, filter operators, cursor paging, ae/oe/aa field encoding) and provides a worked example, adding real meaning beyond the schema.

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 ('Send any GraphQL query') plus the exact endpoint (graphql.datafordeler.dk/DAR/v2), and the 'raw' framing implicitly separates it from the typed sibling helpers like dar_get_address. An agent can identify this as the escape-hatch tool without opening a schema.

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

Usage Guidelines4/5

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

Gives clear context for what the tool is for and directs the agent to dar_get_graphql_schema to discover fields, but never states when to prefer this raw tool over the typed siblings (dar_get_address, dar_list_addresses, etc.) or what it cannot do. Context is clear; exclusions and alternative-selection criteria are absent.

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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