Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
제작자가 쓴 설명(영어 원문)
HealthDCAT-AP catalogs of published Semantic Data Charter models; Turtle or JSON-LD; no account.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"sdchealthdcatap": {
"command": "uvx",
"args": [
"sdchealthdcatap",
"mcp"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add sdchealthdcatap -- uvx sdchealthdcatap mcp프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"sdchealthdcatap": {
"command": "uvx",
"args": [
"sdchealthdcatap",
"mcp"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"sdchealthdcatap": {
"type": "stdio",
"command": "uvx",
"args": [
"sdchealthdcatap",
"mcp"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검
레지스트리 이름이 GitHub 계정 SemanticDataCharter 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(4.1.1)은 12일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Python (uv)도 있어야 해요.
같은 카테고리에는: Spec Driven Development, Remote Desktop Commander, Fomu MCP
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Kenya government form guides: checklists, draft letters, eCitizen, Huduma, timelines. Sample data.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
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.
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:
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:version | as the DCAT-AP writer does, from the package |
dct:accessRights | NON_PUBLIC from the Access Rights NAL (declared; it selects the validator's shape set) |
dcatap:applicableLegislation | the 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:custodian | the 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:theme | RQSH (research cohorts, questionnaires and surveys), noncommunicable diseases, STATISTICAL, HEAL (declared) |
dcat:distribution | the 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:page | the schema at its stable URL, described as the data dictionary |
healthdcatap:numberOfRecords, numberOfUniqueIndividuals, minTypicalAge, maxTypicalAge, populationCoverage | 9,254; 9,254; 0; 80; the NHANES population (declared) |
dpv:hasPersonalData, dpv:hasLegalBasis, dpv:hasPurpose | age, gender and health record from the DPV personal-data taxonomy; the basis and purpose as text (declared) |
dqv:hasQualityAnnotation | a 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.
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.
Declared rather than read from the package, and said so here:
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:
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.
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.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.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).foaf:page.앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요