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Sdchealthdcatap

作者:SemanticDataCharter版本 4.1.1i★ 0i在你的电脑上运行
注册名称io.github.SemanticDataCharter/sdchealthdcatap

安装方法

What it does

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

  • Connects 在你的电脑上运行
  • Account or key No key needed
  • Category 开发者工具

安装

选择你使用的 AI 应用,然后复制设置。

通过 3/3 项检查 · 在你的电脑上运行 · ✓ 命令已检查 2026年11月13日

第一步:你用哪个 AI?

选择你用的应用,步骤会显示在下方。

可连接 Claude,但需要先准备

需要先在电脑上安装 Python (uv)(只需一次) · 仅限电脑上的 Claude 应用(Windows 或 Mac),网页和手机不可用

  1. 安装 Python (uv)

    只需一次,所有需要 Python (uv) 的服务器都能用

    打开 Python (uv) 下载页 ↗

  2. 打开电脑版 Claude 应用的设置文件

    SettingsDeveloperEdit Config

  3. 粘贴这些设置并保存文件

    {
      "mcpServers": {
        "sdchealthdcatap": {
          "command": "uvx",
          "args": [
            "sdchealthdcatap",
            "mcp"
          ]
        }
      }
    }
  4. 退出 Claude 再重新打开

  5. 试一试

    用 Sdchealthdcatap 告诉我你能帮我做什么,然后做一件给我看

    ✓ 如果 Claude 说正在使用 Sdchealthdcatap,或回答中出现 Sdchealthdcatap 的工具名称,就表示连接成功

菜单名称已于 2026年11月11日 对照 Anthropic 帮助页面核实 · 你的界面可能因版本略有不同

ChatGPT 暂时无法连接 Sdchealthdcatap

Sdchealthdcatap 需要安装在你的电脑上,而 ChatGPT 只能连接在网上运行的服务器

你可以改用这些方式

A · 使用能连接 Sdchealthdcatap 的应用

  • 需要先在电脑上安装 Python (uv)(只需一次) · 仅限电脑上的 Claude 应用(Windows 或 Mac),网页和手机不可用
  • 需要先在电脑上安装 Python (uv)(只需一次)
  • 需要先在电脑上安装 Python (uv)(只需一次)
  • 需要先在电脑上安装 Python (uv)(只需一次)

B · 开发者工具 类中能连接 ChatGPT 的其他服务器

从同类中使用较多的里挑选,仅限用地址即可连接、无需密钥的

可连接 Claude Code,但需要先准备

需要先在电脑上安装 Python (uv)(只需一次)

  1. 安装 Python (uv)

    只需一次,所有需要 Python (uv) 的服务器都能用

    打开 Python (uv) 下载页 ↗

  2. 打开终端

    Mac:按 Command+空格,输入 Terminal · Windows:打开 PowerShell

  3. 粘贴这条命令并按 Enter

    claude mcp add --scope user sdchealthdcatap -- uvx sdchealthdcatap mcp
  4. 在 Claude Code 中输入 /mcp

    应能看到 Sdchealthdcatap 在列表中并显示已连接

  5. 试一试

    用 Sdchealthdcatap 告诉我你能帮我做什么,然后做一件给我看

    ✓ 如果 Claude Code 说正在使用 Sdchealthdcatap,或回答中出现 Sdchealthdcatap 的工具名称,就表示连接成功

菜单名称已于 2026年11月11日 对照 Anthropic 帮助页面核实 · 你的界面可能因版本略有不同

可连接 Cursor,但需要先准备

需要先在电脑上安装 Python (uv)(只需一次)

  1. 安装 Python (uv)

    只需一次,所有需要 Python (uv) 的服务器都能用

    打开 Python (uv) 下载页 ↗

  2. 点击这个按钮打开 Cursor

    在 Cursor 中打开

    Cursor 会请你确认安装,点击 Install

  3. 在 Cursor 中以 Agent 模式打开 AI 聊天

  4. 试一试

    用 Sdchealthdcatap 告诉我你能帮我做什么,然后做一件给我看

    ✓ 如果 Cursor 说正在使用 Sdchealthdcatap,或回答中出现 Sdchealthdcatap 的工具名称,就表示连接成功

菜单名称已于 2026年11月11日 对照 Cursor 帮助页面核实 · 你的界面可能因版本略有不同

可连接 VS Code,但需要先准备

需要先在电脑上安装 Python (uv)(只需一次)

  1. 安装 Python (uv)

    只需一次,所有需要 Python (uv) 的服务器都能用

    打开 Python (uv) 下载页 ↗

  2. 点击这个按钮打开 VS Code

    在 VS Code 中打开

    VS Code 会请你确认安装,点击 Install

  3. 在 VS Code 中以 Agent 模式打开 AI 聊天

  4. 试一试

    用 Sdchealthdcatap 告诉我你能帮我做什么,然后做一件给我看

    ✓ 如果 VS Code 说正在使用 Sdchealthdcatap,或回答中出现 Sdchealthdcatap 的工具名称,就表示连接成功

菜单名称已于 2026年11月11日 对照 VS Code 帮助页面核实 · 你的界面可能因版本略有不同

其他支持 MCP 的应用(如 Windsurf、Zed、Gemini CLI)添加方式各不相同,请在应用列表中查看

查看所有支持 MCP 的应用 →

JSON 设置在下方“开发者专用”中

卡住了?问问正在用 Sdchealthdcatap 的人💬 讨论 →
开发者专用:终端命令和 JSON 设置

安装在电脑上

Claude Code

claude mcp add --scope user sdchealthdcatap -- uvx sdchealthdcatap mcp

Claude Desktop (claude_desktop_config.json)

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

Cursor (~/.cursor/mcp.json)

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

VS Code (mcp.json)

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

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

一览

每周下载量i
28/周
许可证i
Apache-2.0
连接方式
在你的电脑上运行
最新版本i
4.1.1
发布到注册中心i
2026年10月26日
代码最后更新i
2026年11月10日
作者
SemanticDataCharter
软件包
pypi: sdchealthdcatap
注册状态
活跃

哪些应用可以使用它

依据这个服务器的连接方式和各应用自己的文档,检查于 2026年11月10日。

在你的电脑上运行,适用于

ClaudeGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatRaycast

全部应用及其优缺点 →

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月14日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 SemanticDataCharter 验证,该账户拥有此仓库

  • ✓ 通过

    仍在维护

    代码最后更新于4天前

  • ✓ 通过

    有许可证

    使用 Apache-2.0

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

讨论

提问、分享技巧或报告无法使用。按“有帮助”数量排序。

还没有帖子,欢迎第一个提问或分享。

此处内容由用户撰写,不代表 PopNx 团队。

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与“开发者工具”中的其他服务器比较i

  • 星标数多于此分类中其他 5868 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 5868 个服务器的 59% 更新
  • 基础检查结果等于或优于此分类中其他 5868 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Sdchealthdcatap 安全吗?

它在 3 项适用的基础检查中通过了 3 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于4天前,最新版本(4.1.1)于19天前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。

有什么可以替代它?

同一分类中有:REA, GitHub, Serena MCP: the IDE for your agent

同类别的其他选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:↓ 每周下载量i★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

REA

Reverse engineer anything from your terminal or agent with one CLI and MCP server.

作者:morluto广泛使用↓ 38.9万/周★ 45.8万前天更新

在你的电脑上运行

GitHub

Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.

作者:github广泛使用★ 3.4万11天前更新

电脑或云端

Serena MCP: the IDE for your agent

A powerful toolkit for coding, providing semantic retrieval and editing capabilities.

作者:oraios广泛使用↓ 3.5万/周★ 3.1万6个月前更新

在你的电脑上运行

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

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

只显示了开头部分;其余内容请在仓库中阅读