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Sdcdcatap

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

安装

概览

作者提供的说明(英文原文)

DCAT-AP 3.0.1 catalogs of published Semantic Data Charter models; Turtle or JSON-LD; no account.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 其他

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 注册中心没有列出需要填写的密钥。

你需要

  • PyPI已安装 Python 的 uv(用于 uvx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

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

在终端中运行这条命令

claude mcp add sdcdcatap -- uvx sdcdcatap mcp

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

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

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

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

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

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。

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6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

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 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

与“其他”中的其他服务器比较i

  • 星标数多于此分类中其他 32464 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 32464 个服务器的 75% 更新
  • 基础检查结果等于或优于此分类中其他 32464 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

Sdcdcatap 安全吗?

它在 1 项适用的基础检查中通过了 1 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–,最新版本(4.1.1)于12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:Spec Driven Development, Remote Desktop Commander, yontu

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ 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

Spec Driven Development

作者:formulahendry

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

在你的电脑上运行★ 440MIT14个月前更新
安装

Remote Desktop Commander

作者:desktop-commander

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

在云端运行★ 211昨天更新
安装

yontu

作者:senrecep

Türkçe yazı denetimi: TDK kuralları, yapay zekâ izleri, metin türüne göre üslup.

在你的电脑上运行今天更新
安装

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_dcat3_ap

One Semantic Data Charter model, described in DCAT-AP 3.0.1.

sdcdcatap reads a published SDC model's package and writes the dcat:Catalog that DCAT-AP, the DCAT Application Profile for data portals in Europe, asks a portal to exchange: one Dataset per model, the model's schema cited as the standard its records conform to (dct:conformsTo) and as the document that defines their variables (foaf:page), by URL and SHA-256. One rdflib graph, serialized as Turtle and as JSON-LD. The output is checked with SEMIC's own SHACL shapes at a pinned commit and with the Interoperability Test Bed's SEMIC validator.

1. What this is, and where it came from

The sample, samples/nhanes-participant/catalog.ttl (and catalog.jsonld, the same graph), is a Catalog with one Dataset: 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). 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]"

sdcdcatap write --package samples/nhanes-participant --out catalog.ttl --jsonld catalog.jsonld sdcdcatap write --ct-id xy8upneajsb8vdcmnve01g6g --ct-id --save-package pkg/ --out catalog.ttl # a catalog of models, from the public catalog sdcdcatap write --package DIR --catalog my-catalog.yaml --out catalog.ttl # a publisher'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, the variable count, and the model's own Dublin Core when the modeler wrote it (publisher, subject keywords, contributors, coverage). From the catalog's publisher, declared in catalog.yaml because the profile's controlled vocabularies and range rules demand values the package cannot know: the contact point, the EU data theme, access rights, language, the publisher's ADMS type, the catalog's own title, description and homepage. The package ships a default file for the sample (src/sdcdcatap/data/catalog.yaml); a publisher supplies its own.

Every referenced node is typed and named inline. The range shapes require every object value to be an instance of its class, and the mandatory shapes require a name on every agent and a label on every concept, wherever they sit in the graph. So the publisher is a foaf:Agent with a foaf:name, the theme is a skos:Concept with a skos:prefLabel in its scheme, the licence is a dct:LicenseDocument, the language a dct:LinguisticSystem, and so on. A harvesting portal gets a complete graph.

What the Dataset carries:

dct:title, dct:descriptionthe model's, English-tagged, plus one sentence saying what a governed data record is and that the schema is immutable
dct:identifier, adms:identifierdm-xy8upneajsb8vdcmnve01g6g, as a literal and as an adms:Identifier with skos:notation
dct:conformsToa dct:Standard: the schema at its pinned URL (?sha256=), with the SHA-256 as dct:identifier
foaf:pagea foaf:Document: the schema at its stable URL, described as the data dictionary (153 variables), dct:format XML from the File Type NAL, itself dct:conformsTo the SDC4 reference model
dct:publisher, dct:creatorfoaf:Agents with names; the publisher with its ADMS type and homepage
dcat:contactPointa vcard:Kind with vcard:fn and vcard:hasEmail, from the declared input
dcat:theme, dct:language, dct:accessRightsHEAL from the EU Data Theme vocabulary, ENG from the Languages NAL, PUBLIC from the Access Rights NAL, from the declared input
dct:licensethe model's licence URL as a dct:LicenseDocument
dcat:keyword, dcat:landingPage, dct:issued, dct:modifiedfrom the package
dct:provenance, dcat:versiona dct:ProvenanceStatement: a published model never changes, a revision is a new model naming the one it revised; the SHA-256 as the version

The Catalog carries its title, description, publisher, homepage, language, dates, the Data Theme vocabulary as dcat:themeTaxonomy, and the Dataset.

2. How to verify it

The tests run SEMIC's shapes from data/dcat-ap-3.0.1-4470b8e/, copied at the pinned commit (build/snapshot_dcat_ap.py verifies the pin first), with pySHACL:

pip install -e ".[dev]"

python -m pytest tests -q # the Interoperability Test Bed test runs too, over the network python -m pytest tests -q -m "not network" # offline, as CI runs it

Offline: the mandatory-property shapes (dcat-ap-SHACL.ttl) and the range shapes (ranges.ttl), both conforms, in Turtle and in JSON-LD. The committed samples are asserted isomorphic to a fresh run.

The second judge, the Interoperability Test Bed's SEMIC SHACL validator (https://www.itb.ec.europa.eu/shacl/dcat-ap/, v1.14.0-SNAPSHOT on 9 October 2026, through its REST API), on the sample:

Validation typeResult
dcatap.3_0_1_base0 (mandatory, no background knowledge)conforms
dcatap.3_0_1_range0 (ranges, no background knowledge)conforms
dcatap.3_0_1_codelists (controlled vocabularies)conforms, 3 warnings: the publisher is not in the EU Corporate Bodies NAL (it is a company, not an EU body)
dcatap.3_0_1_rec (recommendations)conforms, 19 warnings, listed in part 4
dcatap.3_0_1_full (everything, with background knowledge)11 violations that are not in the document: see part 4

The network test asserts the first four.

3. What the projection could not say

Left out rather than filled in:

  • No `dcat:distribution` of the records. The FAIR Data Demo's records are not published; the model is. The profile recommends a distribution and does not require one; the writer emits one when a publisher declares an access URL.
  • No temporal coverage, no geometry, no frequency, no dataset series, no data service. The package does not carry them. Spatial coverage, subject keywords, contributors and the model's own publisher come from the model's Dublin Core when the modeler wrote them; SDCStudio's field defaults ("Universal" for coverage, "None" for relation, blanks) read as unset, which is why the NHANES catalog carries none of them.
  • Nothing a publisher would have to decide. The data theme, access rights, language, the publisher's type and the contact point are declared input, said so here, and defaulted only for the sample.

In the other direction, what the record carries that a catalog entry has no place for, stated so a reader knows where to look rather than as a shortcoming of either side:

  • The governance envelope is data in every record. Each Governed Data Record carries its own audit event, PROV activity and PROV agent as validated leaves. DCAT-AP's dct:provenance and prov:wasGeneratedBy describe the dataset; the per-record facts are in the records, defined in the schema the catalog points at.
  • The schema is bound to each record. Every record names the schema it was validated against; the catalog says that once, in dct:conformsTo with the SHA-256.
  • The reason a value is missing is typed in the record. A leaf may carry one of sixteen exceptional values in place of its value; the schema defines them; which one applies, and where, is in the record.
  • There is no data-dictionary slot. DCAT-US 3.0 has describedBy for "the names and definitions of all variables"; DCAT-AP has dct:conformsTo and foaf:page, which is where the schema goes here.

4. What we learned about DCAT-AP 3.0.1 and its validators

Implementer's notes from building this against SEMICeu/DCAT-AP at 4470b8e and the Interoperability Test Bed 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.

  • Type and name everything you reference. The ranges file checks sh:class on every object property, and the base file requires foaf:name on every foaf:Agent and skos:prefLabel on every skos:Concept in the graph, including vocabulary terms you merely point at (the ADMS publisher type, the data theme). SEMIC's own minimal example, with its publisher as a bare URI, passes the mandatory shapes and fails the ranges for exactly this reason.
  • The `full` and `base` types report violations that are not in the document. An empty minimal catalog (title, description, a named publisher) submitted to dcatap.3_0_1_base returns the same five foaf:name violations on blank-node agents as our sample does, and full adds six dct:title violations on ADMS concept schemes (http://purl.org/adms/publishertype/1.0 and siblings). They come from the background knowledge those types load, not from the content. Read the four groups individually (base0, range0, codelists, rec), each of which reports only on the document; that is what the table in part 2 does.
  • The recommendations type treats the Catalog as a Dataset. With DCAT loaded as background knowledge (dcat:Catalog is a subclass of dcat:Dataset), the Dataset recommendations fire on the Catalog too: contact point, distribution, keyword, theme, spatial and temporal coverage, licence. Of the 19 warnings on the sample, nine are those; the rest are the Dataset's missing distribution, spatial and temporal coverage, dct:type on the creator agent and on the licence document (ADMS licence type), and the publisher outside the Corporate Bodies NAL.
  • `ranges.ttl` references property shapes it does not define. 206 sh:property triples point at nodes with no triples of their own. A Jena-based validator passes over them; pySHACL refuses to run ("not a well-formed SHACL PropertyShape"). The tests drop the undefined references before running; the 91 defined property shapes are what is checked.
  • The REST API is simple. POST https://www.itb.ec.europa.eu/shacl/dcat-ap/api/validate with a JSON body of contentToValidate (the document as a string), embeddingMethod: STRING, contentSyntax, validationType and reportSyntax; the answer is a SHACL validation report. /api/info lists the validation types and the validator version. JSON-LD and Turtle gave identical results.
  • `dcat:version` is a DCAT 3 property that rdflib's closed `DCAT` namespace does not know; build the IRI by hand.
  • The language is a NAL concept, not a tag. dct:language takes http://publications.europa.eu/resource/authority/language/ENG, a dct:LinguisticSystem; a BCP 47 string fails the ranges.

MCP server

sdcdcatap is also an MCP server, registered as io.github.SemanticDataCharter/sdcdcatap, so an assistant that can read a published model with sdcreader can ask for its DCAT-AP 3.0.1 description. One tool, write_catalog, over the same function the CLI calls; stdio; read-only apart from the document it returns; no account; no tool takes a URL (the catalog host is fixed at start with --host). The protocol scaffold is sdcreader.mcp, shared by every SDC projection server.

uvx sdcdcatap mcp            # or: sdcdcatap-mcp, or sdcdcatap mcp

Layout

  • The model's package is read with sdcreader (load_package, fetch_package, read_model): the record tree, its leaves, the enumerated values with their codes, the model's Dublin Core with SDCStudio's defaults as unset. The

只显示了开头部分;其余内容请在仓库中阅读

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