dannet

DanNet - Danish WordNet with rich lexical relationships and SPARQL access.

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What it can do

    What data it sees

    Do you need an account

    No: the server works without sign-in

    DanNet - Danish WordNet with rich lexical relationships and SPARQL access.

    How to connect

    How to connect dannet to Claude

    The server address to paste into Claude settings:

    https://wordnet.dk/mcp

    1. Open Claude (claude.ai or the desktop app).
    2. Go to Settings → Connectors.
    3. Click Add custom connector.
    4. Paste the server address copied below into Remote MCP server URL and click Add.
    5. In a chat, click + → Connectors and switch the new connector on.

    Custom connectors are available on Free, Pro, Max, Team and Enterprise plans (Free is limited to one). On Team and Enterprise an organization Owner adds the connector first under Organization settings → Connectors.

    Authorization

    After you click Add, a sign-in window for the service opens. Sign in with your own account and approve access. Claude never sees your password.

    How to connect dannet to ChatGPT

    The server address to paste into ChatGPT settings:

    https://wordnet.dk/mcp

    1. Open ChatGPT in a browser (chatgpt.com). A Plus, Pro, Business, Enterprise or Edu plan is required.
    2. Turn on developer mode once: Settings → Apps → Advanced settings → Developer mode.
    3. Open Settings → Connectors and click Create.
    4. Fill in the form: Name (anything), Description (one line about what the service does), MCP server URL (copy it below).
    5. Under Authentication choose OAuth if the service requires sign-in, otherwise None. Click Create.
    6. In a new chat open + → Apps/Connectors and enable the connector.

    OpenAI has renamed this section before (Connectors → Apps/Plugins). If the label differs, search settings for "developer mode". On Business/Enterprise workspaces an admin must allow custom connectors first.

    Authorization

    On first use ChatGPT opens the service's sign-in window. Sign in and approve access.

    How to connect dannet to Cursor

    The server address to paste into Cursor settings:

    https://wordnet.dk/mcp

    Fastest: click Open in Cursor below and confirm the prompt.

    Manually:

    1. In Cursor open Settings → Cursor Settings → MCP and click Add new global MCP server.
    2. Paste the JSON copied below into ~/.cursor/mcp.json (per project: .cursor/mcp.json in the repo root).
    3. Save the file. The server appears in the MCP list; authorize it there if asked.

    Authorization

    If the service needs sign-in, an authorize button appears next to the server in the MCP list.

    Server tool list (6)

    Raw names from tools/list. Only developers need these.

    get_word_synsetsThe synsets (senses) of the Danish `word`, as JSON-LD entries with @id (e.g. "dn:synset-3047" for get_entity_info), skos:definition, dns:ontologicalType and wn:lexfile. A word with a single synset gives that synset's full JSON-LD as the only entry.
    get_entity_infoFull JSON-LD of a DanNet resource: a synset ("synset-3047"), word ("word-11021628") or sense ("sense-21033604"), given bare or prefixed ("dn:synset-3047"), or an external resource by prefix ("ili:i76470", "ontolex:LexicalConcept"). Properties use prefixed names (wn:hypernym, ontolex:isEvokedBy, ...); language-tagged values are {"@value": ..., "@language": ...}.
    get_word_overviewEvery sense of the Danish `word` in one call: a list with synset_id, label, definition, lexfile, ontological_types, synonyms (words sharing the synset) and hypernym ({synset_id, label} or null) per synset. Only synsets where the word itself has a sense count, not multi-word expressions containing it.
    autocomplete_danish_wordDanish words starting with `prefix` (at least 3 characters), at most `max_results`, as {"autocompletions": [...]} where lemmas are plain strings and inflected forms of a matching lemma are [lemma, form] pairs.
    fetch_ddo_definitionThe full definitions of `synset_id` from DDO (ordnet.dk), where DanNet's own skos:definition may be truncated. Follows the dns:source of each sense. Returns the DanNet definition, the DDO definitions found and any errors; DDO and DanNet have drifted apart, so some source URLs no longer resolve.
    sparql_queryRun a SPARQL SELECT `query` against DanNet and return standard SPARQL JSON results ({"head": ..., "results": {"bindings": [...]}}). The common prefixes (dn, dns, dnc, dnf, wn, ontolex, lexinfo, skos, rdfs, rdf, owl, marl, dc, ili, en, enl, cor) are declared automatically. `timeout` is in ms (max 15000), `max_results` at most 100, `distinct` adds DISTINCT, and `inference` selects the model: None tries the base model and retries with inference on an empty result; True forces inference, which inverse relations like wn:hyponym and wn:holo_* need; False forces the base model. Performance rules: anchor every query on a known URI or a word lookup (dn:synset-3047 wn:hypernym ?x, never ?x wn:hypernym ?y alone); never FILTER(CONTAINS(...)) over all labels, look the word up first; make every triple pattern share a variable with another; add LIMIT; prefer VALUES over FILTER for several known URIs; the store also holds the English WordNet (en:), so anchor on dn: or "..."@da to stay in Danish. Templates: Synsets of a word: SELECT DISTINCT ?synset ?label WHERE { ?entry ontolex:canonicalForm/ontolex:writtenRep "hund"@da . ?entry ontolex:sense/ontolex:isLexicalizedSenseOf ?synset . ?synset rdfs:label ?label } Taxonomic ancestors: SELECT DISTINCT ?ancestor ?label WHERE { dn:synset-3047 wn:hypernym+ ?ancestor . ?ancestor rdfs:label ?label } Hyponyms (needs inference=True, or query the inverse wn:hypernym): SELECT DISTINCT ?hyponym ?label WHERE { ?hyponym wn:hypernym dn:synset-3047 . ?hyponym rdfs:label ?label } Ontological types (an RDF bag): SELECT ?type WHERE { dn:synset-3047 dns:ontologicalType/?pos ?type . FILTER(STRSTARTS(STR(?pos), STR(rdf:_))) } Taxonomic similarity (dnf:path, dnf:lch, dnf:wup score two synsets of the same language and part of speech, 1.0 for identical): SELECT ?synset ?score WHERE { ?synset a ontolex:LexicalConcept . FILTER(STRSTARTS(STR(?synset), STR(dn:))) BIND(dnf: