Prototyp · Vorschau: alle Server aus der offiziellen Registry, alle 30 Minuten synchronisiert. Bewertungen und Benutzerkonten folgen in einem späteren Schritt.
PopNx MCPMCP-Server für alle, die KI nutzen · in einfachen Worten erklärt

Sdchealthdcatap

von SemanticDataCharterVersion 4.1.1i★ –iLäuft auf deinem Computer
Name in der Registryio.github.SemanticDataCharter/sdchealthdcatap

Installieren

Überblick

Beschreibung vom Entwickler (englisches Original)

HealthDCAT-AP catalogs of published Semantic Data Charter models; Turtle or JSON-LD; no account.

Die drei Säulen von PopNx MCP

Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.

Was du damit machen kannst

Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.

  • Verbindung: Läuft auf deinem Computer
  • Transport: stdio
  • Kategorie: Sonstiges

Installation

Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.

Bevor du installierst

  • Basischecks: 1 von 1 bestanden
  • Läuft auf deinem Computer mit den Rechten deines Benutzerkontos (Dateien, Netzwerk, Apps).
  • Die Registry nennt keinen Schlüssel zum Eintragen.

Du brauchst

  • PyPIuv für Python installiert (für den Befehl uvx)

Welche App nutzt du?

Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.

Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein

{
  "mcpServers": {
    "sdchealthdcatap": {
      "command": "uvx",
      "args": [
        "sdchealthdcatap",
        "mcp"
      ]
    }
  }
}

Führe das in deinem Terminal aus

claude mcp add sdchealthdcatap -- uvx sdchealthdcatap mcp

In Cursor öffnen

Oder kopier die Einstellungen selbst

In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen

{
  "mcpServers": {
    "sdchealthdcatap": {
      "command": "uvx",
      "args": [
        "sdchealthdcatap",
        "mcp"
      ]
    }
  }
}

Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.

In VS Code öffnen

Oder kopier die Einstellungen selbst

In .vscode/mcp.json in deinem Projekt einfügen

{
  "servers": {
    "sdchealthdcatap": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "sdchealthdcatap",
        "mcp"
      ]
    }
  }
}

Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.

Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.

Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.

Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.

Was er kann

Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.

Basischecksi

Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 6. Nov. 2026

  • ✓ Bestanden

    Entwickler passt zum Repo

    Der Registry-Name wurde mit dem GitHub-Konto SemanticDataCharter bestätigt, dem das Repo gehört

  • … Noch nicht geprüft

    Wird noch gepflegt

    Dieses Repo haben wir noch nicht von GitHub gelesen

  • … Noch nicht geprüft

    Hat eine Lizenz

    Dieses Repo haben wir noch nicht von GitHub gelesen

  • – Nicht zutreffend

    Endpunkt antwortet

    Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet

  • – Nicht zutreffend

    Anmeldung mit OAuth

    Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen

  • … Noch nicht geprüft

    Keine versteckten Anweisungen in Tool-Beschreibungen

    Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen

Im Vergleich mit anderen in Sonstigesi

  • Mehr Sterne als 0 % der anderen 32466 Server in dieser Kategorie
  • Neuer in der Registry veröffentlicht als 75 % der anderen 32466 Server in dieser Kategorie
  • Basischecks gleich gut wie oder besser als bei 100 % der anderen 32466 Server in dieser Kategorie

Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.

Häufige Fragen

Ist Sdchealthdcatap sicher?

Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.

Welche Schlüssel oder Codes braucht er?

Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.

Läuft er auf meinem Computer oder in der Cloud?

Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).

Wird er noch gepflegt?

Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (4.1.1) kam vor 12 Tagen in die Registry.

Welche Apps können ihn nutzen?

Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Python (uv) auf deinem Computer.

Was kann ich stattdessen nutzen?

In derselben Kategorie: Spec Driven Development, Remote Desktop Commander, HotCodePush

Alternativen

Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.

So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti

Spec Driven Development

von formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

Läuft auf deinem Computer★ 440MITAktualisiert vor 14 Monaten
Installieren

Remote Desktop Commander

von desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Läuft in der Cloud★ 211Aktualisiert gestern
Installieren

HotCodePush

von hotcodepush-team

Manage over-the-air (OTA) updates for React Native, Expo, Capacitor and Cordova apps.

Läuft in der CloudAktualisiert heute
Installieren

README vom Entwickler

README öffnen

Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.

sdc_healthdcat_ap

One Semantic Data Charter model, described in HealthDCAT-AP.

sdchealthdcatap reads a published SDC model's package and writes the dcat:Dataset description that HealthDCAT-AP, the health extension of DCAT-AP for the secondary use of health data under the European Health Data Space, asks a data holder to publish into the HealthData@EU catalogue: one Dataset per model at a declared access level, its variables as a CSVW table group built from the record's leaves, its coding systems from the model's bindings, and the holder's facts from declared input. One rdflib graph, serialized as Turtle and as JSON-LD. The output is checked with the HealthData@EU validator's own shape set for the level, at a pinned commit of the specification's repository.

1. What this is, and where it came from

The sample, samples/nhanes-participant/catalog.ttl (and catalog.jsonld, the same graph), is one Dataset at the NON_PUBLIC access level, with no catalogue wrapper, as the release's own examples are (part 4 says why): the records of NHANES Participant (dm-xy8upneajsb8vdcmnve01g6g) from the FAIR Data Demo, a demographic, examination and laboratory record of the National Health and Nutrition Examination Survey (CDC), 9,254 records, one per participant. The model is public:

  • the catalog record: https://sdcstudio.axius-sdc.com/api/v1/catalog/dm/xy8upneajsb8vdcmnve01g6g/
  • the schema the records conform to: https://sdcstudio.axius-sdc.com/dmlib/dm-xy8upneajsb8vdcmnve01g6g.xsd
  • the Semantic Data Charter: https://semanticdatacharter.com
pip install -e ".[fetch]"

sdchealthdcatap write --package samples/nhanes-participant --out catalog.ttl --jsonld catalog.jsonld sdchealthdcatap write --ct-id xy8upneajsb8vdcmnve01g6g --save-package pkg/ --out catalog.ttl # any published model, from the public catalog sdchealthdcatap write --package DIR --catalog my-catalog.yaml --out catalog.ttl # a data holder's own declared input

Two kinds of input, kept apart. From the model's package (its JSON-LD, its schema, the public catalog record and the published schema versions; no account needed; a model without a package is refused): title, description, identifier, creator, dates, licence, the schema's URL and SHA-256, every leaf of the record for the variables, every concept system the model binds to for the coding systems, and the model's own Dublin Core when the modeler wrote it. From the data holder, declared in catalog.yaml because the profile asks for facts only a holder has and for values from the DG SANTE and EU vocabularies: the access level, the health data access body, the applicable legislation, the health category and theme, the dataset type, the distribution that is the access route, the counts of records and individuals, typical ages, population coverage, personal-data categories, legal basis, purpose, the publisher's type, the contact point. The package ships the sample's file (src/sdchealthdcatap/data/catalog.yaml); a holder supplies its own.

The data dictionary is a slot here. healthdcatap:hasVariables takes a csvw:TableGroup; the writer builds one table with one csvw:Column per leaf of the record, 153 for NHANES Participant: csvw:name the leaf's path in the record, csvw:title its label, csvw:datatype its XSD type, dct:description its definition, csvw:propertyUrl its library slot (the identifier that says what the variable means wherever it is reused), dct:identifier its element name. healthdcatap:hasStructuredData is true. healthdcatap:hasCodingSystem carries SNOMED CT, LOINC and NCIT from the Coding System NAL, derived from the model's skos:exactMatch bindings by IRI prefix.

What else the Dataset carries:

dct:title, dct:description, dct:identifier, adms:identifier, dcat:keyword, dcat:landingPage, dct:issued, dct:modified, dct:language, dct:license, dct:provenance, dcat:versionas the DCAT-AP writer does, from the package
dct:accessRightsNON_PUBLIC from the Access Rights NAL (declared; it selects the validator's shape set)
dcatap:applicableLegislationthe EHDS Regulation's ELI, http://data.europa.eu/eli/reg/2025/327/oj, on the Catalog, the Dataset and the Distribution (declared)
healthdcatap:hdab, geodcatap:custodianthe publisher, a foaf:Agent with a cv:ContactPoint and a type from the Health Publisher Types NAL (declared; see part 3)
healthdcatap:healthCategory, healthdcatap:healthTheme, dct:type, dcat:themeRQSH (research cohorts, questionnaires and surveys), noncommunicable diseases, STATISTICAL, HEAL (declared)
dcat:distributionthe access route: title, description, dcat:accessURL, availability, the legislation, the licence, and dct:conformsTo the schema as a dct:Standard by its pinned URL
foaf:pagethe schema at its stable URL, described as the data dictionary
healthdcatap:numberOfRecords, numberOfUniqueIndividuals, minTypicalAge, maxTypicalAge, populationCoverage9,254; 9,254; 0; 80; the NHANES population (declared)
dpv:hasPersonalData, dpv:hasLegalBasis, dpv:hasPurposeage, gender and health record from the DPV personal-data taxonomy; the basis and purpose as text (declared)
dqv:hasQualityAnnotationa dqv:QualityCertificate whose body is the schema: every record is validated against it before it exists

Every NAL concept the graph uses states its scheme (skos:inScheme), and every scheme is typed and titled, because the validator's codelist shapes check membership that way. Every agent is typed and named, with a contact point.

2. How to verify it

The tests run the HealthData@EU validator's own configuration from data/healthdcat-ap-r8-cd7841f/validator/ (build/snapshot_healthdcat_ap.py verifies the pin first): config.properties names the shape files per access level, and the tests load exactly those for the declared level, plus SEMIC's DCAT-AP 3.0.1 shapes as the release ships them, plus the thirteen vocabularies the codelist shapes name, which the validator preloads as background:

pip install -e ".[dev]"

python -m pytest tests -q

Result at the pin, NON_PUBLIC, in Turtle and in JSON-LD: 0 violations, 10 warnings, the recommended properties the package does not carry (analytics, retention period, frequency, dct:conformsTo on the Dataset, references, relations, source, temporal coverage and resolution, a sample). The committed samples are asserted isomorphic to a fresh run. The release's own ARCA example, run the same way at PUBLIC, passes except where the background we carry stops (part 4).

Second witness, the Interoperability Test Bed, which the specification's validation section names as where the shape and import files "can be loaded": its generic SHACL validator (https://www.itb.ec.europa.eu/shacl/any/upload, REST API /shacl/any/api/validate) given the release's non-public shape files as external rules, 9 October 2026: no violation on any node of the document, 14 warnings (the ten above, plus dct:format on the distribution, dct:spatial, and dct:type on the creator agent and the licence document). The 22 violations it also reports fall on nodes the Test Bed carries itself, six ADMS concept schemes without a title and five unnamed blank agents, each twice, the same an empty catalog receives on its DCAT-AP domain. The network-marked test asserts the first part; CI skips it. The HealthData@EU platform's own validator page was not reachable: both the production and the acceptance platforms answer 404 at the validator path, and the platform's public pages do not link one.

3. What the projection could not say

Declared rather than read from the package, and said so here:

  • The health data access body is the publisher. The field is mandatory at every level and no EU body holds this dataset. The sample names Axius SDC, Inc., with its contact point, as the body that grants access, which is true of the FAIR Data Demo and would be replaced by the real body for a dataset inside the EHDS.
  • The applicable legislation is the EHDS Regulation, as the profile's usage note recommends, for a dataset the Regulation does not govern. It is the profile's required way of saying "described for the EHDS framework."
  • The counts, ages, population, personal-data categories, legal basis and purpose are the holder's statements about the FAIR Data Demo's generation run and the NHANES source, not facts the package carries.
  • The distribution is a route, not a file. The records are not published; the access route is the contact page. A holder with a download or a data service replaces it.

Left out: retention period, analytics distribution, sample distribution, frequency, temporal coverage, relations. The package does not carry them, and the profile recommends rather than requires them.

In the other direction, what the record carries that the catalog entry only points at:

  • The governance envelope is data in every record, an audit event, a PROV activity and a PROV agent, validated with the rest. The columns for them are in the table group, so a reader can see they exist; the values are in the records.
  • The schema is bound to each record, and cited here on the distribution and the page by URL and SHA-256.
  • The reason a value is missing is typed in the record. The table group's description says every column may carry one of sixteen exceptional values; which one applies, and where, is in the record.

4. What we learned about HealthDCAT-AP Release 8 and its validator

Implementer's notes from building this against healthdataeu/healthdcat-ap at cd7841f on 9 October 2026. They describe how the artifacts behave, so the next implementer spends the day on their own catalog rather than on these.

  • The document is the Dataset, not a Catalogue. The release's examples are dataset-only, and the reason shows under validation: with DCAT loaded as background (dcat:Catalog is a subclass of dcat:Dataset), a validator reads a dcat:Catalog node as a Dataset and holds it to the Dataset's mandatory list, eleven violations on the wrapper alone (contact point, distribution, keyword, theme, access rights, identifier, provenance, type, health category, access body, the structured-data flag). The writer emits no Catalogue; the HealthData@EU catalogue is the catalogue.
  • The validator ships with the release, configured. html/shacl/HealthDCAT-AP_validator/config/rdf-validator/ehds/ holds config.properties, which names the shape files per access level, and the vocabularies and ontologies the validator preloads. Running that file set with pySHACL is running the validator's logic; the hosted instance adds background knowledge and a web interface.
  • Membership in a vocabulary is checked through `skos:inScheme`. Every codelist restriction asks the concept for skos:inScheme , several also ask the scheme to be a typed skos:ConceptScheme, and SEMIC's base shapes then ask every scheme in the graph for a dct:title. The hosted validator preloads the vocabularies, which supply the inScheme; offline, either load them or state them. The writer states them for every concept it uses, and the tests load the thirteen vocabularies anyway, which is why the release's ARCA example passes offline except for its language (the Languages NAL is 14 MB and stays out) and its licence type (the ADMS scheme is not among the preloads).
  • `dct:conformsTo` on a Dataset is closed to the Technical Standard NAL (FHIR, OMOP-CDM, openEHR, DICOM, CDISC SDTM and about twenty more), at violation level. A schema of one's own cannot go there; the writer cites it on the distribution, which has no such restriction, and on foaf:page.
  • **A health publisher is an agent with exactly on

Nur der Anfang wird gezeigt; den Rest findest du im Repo

PopNx fragen