Ermöglicht es einem AI-Client, Semantic Data Charter Modelle und verwaltete Datensätze zu suchen, zu beschreiben und zu lesen.
Auch bekannt als SemanticDataCharter/sdcreader
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- Neueste Version
- 4.4.1
- Letzter Commit
- 10. Nov. 2026
- Lizenz
- Apache-2.0
Was ist sdcreader MCP?
sdcreader ist ein MCP server. Ermöglicht es einem AI-Client, Semantic Data Charter Modelle und verwaltete Datensätze zu suchen, zu beschreiben und zu lesen.
Zusammenfassung generiert aus dem README des Projekts
Über sdcreader MCP server
sdcreader ermöglicht es KI-Assistenten, Semantic Data Charter Modelle und verwaltete Datensätze zu suchen und zu interpretieren. Es erlaubt einem Client, veröffentlichte Modelle zu explorieren, deren Komponenten zu untersuchen und spezifische Datensätze zu lesen, indem Werte mit ihren definierenden Komponenten verknüpft werden. Der Server fungiert als Read-only-Interface, das dieselben strukturellen Belege liefert, die auch Projection Writer nutzen, um Daten auf Standards wie CDIF oder DCAT-US abzubilden.
Nutzer können den Server via stdio über uvx ausführen. Er kann so konfiguriert werden, dass er eine Verbindung zu einem souveränen SDCStudio öffentlichen Katalog herstellt, indem ein Host angegeben wird. Für den Betrieb sind weder ein Konto noch ein SDK erforderlich. Der Server stellt spezifische Tools bereit, wie find_models für Katalog-Suchen, describe_model zum Abrufen von Metadaten und Schema-URLs, list_leaves zum Anzeigen von Dokumenten-Pfadstrukturen und read_record zum Parsen von XML-Instanzen gegen ein Modell. Er gewährleistet die Datenintegrität, indem er prüft, ob die Schema-Bytes mit den veröffentlichten SHA-256-Hashes übereinstimmen.
Was du damit machen kannst
- 1Den öffentlichen Katalog durchsuchenFinde spezifische Semantic Data Charter Modelle, indem du nach Text suchst oder Modelle innerhalb eines öffentlichen Projekts auflistest.
Geschrieben aus dem README des Projekts. Jeder Use Case wurde gegen ein Zitat daraus geprüft.
So installierst du sdcreader MCP
Formate geprüft am 10. Nov. 2026Zu Cursor hinzufügenZu Goose hinzufügensdcreader MCP in Claude Code installieren
$ claude mcp add sdcreader -- uvx sdcreadersdcreader MCP in Cursor installieren
~/.cursor/mcp.json
{
"mcpServers": {
"sdcreader": {
"command": "uvx",
"args": [
"sdcreader"
]
}
}
}sdcreader MCP in VS Code installieren
.vscode/mcp.json
{
"servers": {
"sdcreader": {
"type": "stdio",
"command": "uvx",
"args": [
"sdcreader"
]
}
}
}sdcreader MCP in VS Code CLI installieren
$ code --add-mcp '{"name":"sdcreader","type":"stdio","command":"uvx","args":["sdcreader"]}'sdcreader MCP in Claude Desktop installieren
claude_desktop_config.json
{
"mcpServers": {
"sdcreader": {
"command": "uvx",
"args": [
"sdcreader"
]
}
}
}sdcreader MCP in Codex installieren
$ codex mcp add sdcreader -- uvx sdcreadersdcreader MCP in Codex config.toml installieren
~/.codex/config.toml
[mcp_servers.sdcreader] command = "uvx" args = ["sdcreader"]
sdcreader MCP in Gemini CLI installieren
$ gemini mcp add -s user sdcreader uvx -- sdcreadersdcreader MCP in Gemini settings.json installieren
~/.gemini/settings.json
{
"mcpServers": {
"sdcreader": {
"command": "uvx",
"args": [
"sdcreader"
]
}
}
}Automatisierte Checks
Geluften am 14. Nov. 2026Vollständiger Bericht →Unsere automatisierten Checks bestanden. Das ist kein Security-Audit: Lies den Code und gib dem Server nur den minimal notwendigen Zugriff. Wie die Checks funktionieren
- Source Repository verknüpft und erreichbarsemanticdatacharter/sdcreader is public and reachablegithub.com/semanticdatacharter/sdcreader ↗Bestanden
- Paket nennt dieses Repository als Quellesdcreader names semanticdatacharter/sdcreader as sourcepypi.org/project/sdcreader/ ↗Bestanden
- Build-Provenienz (Sigstore-Attestierung)Sigstore attestation for sdcreaderpypi.org/project/sdcreader/ ↗Bestanden
- Open Source Lizenz (OSI)Apache-2.0spdx.org/licenses/Apache-2.0.html ↗Bestanden
- Commit oder Release im letzten JahrLast commit or release 2026-11-10github.com/semanticdatacharter/sdcreader ↗Bestanden
- OpenSSF ScorecardNicht geprüft
- Package-Name ähnelt keinem populären PackageNo popular package one edit away from sdcreaderBestanden
- Keine kritischen Advisories im Paket oder seinen Abhängigkeiten7 resolved dependencies checked; no critical advisoryosv.dev ↗Bestanden
- Keine versteckten Anweisungen an das Modell0 tool descriptions and the README read; no override phrases, credential paths or hidden charactersBestanden
- Destruktive Tools sind markiertNicht geprüft
- Remote-Endpoint beantwortet den MCP-HandshakeNicht geprüft
README
Auf GitHub ansehensdcreader
Read a published Semantic Data Charter model's package for projection into other standards.
A projection describes a model's governed data records in another standard's terms: CDIF, DCAT-US 3.0, DCAT-AP
3.0.1, HealthDCAT-AP, and whatever comes next. What every projection describes is the same evidence, the model's
package, and reads it into the same shape. sdcreader is that evidence and that shape, once, with nothing about
any projection in it. The four projection writers (sdc_cdif, sdc_dcat3_us, sdc_dcat3_ap, sdc_healthdcat_ap)
carried it as identical copies until this package.
pip install sdcreader # the reader, with HTTP for fetching from the public catalog (since 4.1.0 no extra is needed)
from sdcreader import fetch_package, load_package, read_model
pkg = load_package("samples/nhanes-participant") # a package on disk
pkg = fetch_package("xy8upneajsb8vdcmnve01g6g", save_to="pkg/") # or from SDCStudio's public catalog, no account
model = read_model(pkg)
pkg.schema_url_pinned # https://sdcstudio.axius-sdc.com/dmlib/dm-xy8u...xsd?sha256=0df4... the exact bytes the records are validated against
model.title, model.leaves # 'NHANES Participant', 153 leaves in document order, each with its path of clusters
model.codes[ct_id] # the enumerated values of a component with the IRI, definition and code the schema annotates them with
model.dc("publisher") # what the modeler wrote, None where SDCStudio's default sits
What a package is
SDCStudio generates a package for every published model and serves it publicly for models in public projects:
GET /api/v1/catalog/dm/<ct>/ |
the catalog record: title, description, project, the artifact list (catalog.json) |
GET /api/v1/catalog/dm/<ct>/<artifact>/ |
a storage pointer, {"download_url": ..., "filename": ..., "storage": "gcs"}, for jsonld, xsd and the rest; the reader follows it |
dm-<ct>.jsonld |
the model and its components: type, label, description, cardinality, constraints (enumerations, units, ranges, patterns), semantic links (dcterms:identifier the library slot, dcterms:source, dcterms:publisher, skos:exactMatch, rdfs:seeAlso, prov:wasRevisionOf), contains |
GET /dmlib/dm-<ct>.xsd |
the schema bytes: the Dublin Core header for the model, and for each enumerated value its definition and the code it is defined by (dm-<ct>.xsd) |
GET /dmlib/dm-<ct>.versions.json |
every published version of the schema by SHA-256, with the current one (versions.json) |
A package directory holds those four files. The reader refuses a directory without the JSON-LD and the schema, a JSON-LD whose identifier is not the directory's model, and a schema whose bytes are not the published current version: a projection cites the schema by URL and SHA-256, so the bytes have to be the ones that URL serves.
Two gaps in the package are on SDCStudio's issue tracker: the JSON-LD metadata drops fields the schema header
carries (#748), and the header omits dc:source (#749). The reader takes the model's Dublin Core from the header,
which is complete.
What the reader gives
ModelPackage: the four files, the SHA-256, the schema URL and its pinned form (?sha256=), the public catalog URL, andcheck().Model:title,description,root(the governed record's cluster),componentsby identifier,leavesin document order (each aLeafwith itscomponent, itspathof clusters and aslugof that path, unique in the record),codes(the enumerated values per component asCode: value, IRI, definition, the code it is defined by),metadata(the JSON-LD's) andheader(the schema's Dublin Core).Model.dc(name): what the modeler wrote, the header first and the JSON-LD second, with SDCStudio's field defaults as unset: "Universal" for coverage, "None" for relation, "SDC Data Model (DM)" for type, blanks. A projection never publishes a default as a fact.contributors,subjects(the semicolon list),rights_urlandrights_statementderive from it.Component:sdc_type,label,description,data_type,constraints,linksby predicate (link(p)for the first),contains,iri.- Constants: the leaf, numeric and quantified types; the predicate IRIs
IDENTIFIER,SOURCE,PUBLISHER,EXACT,CLOSE,SEE_ALSO,HAS_UNIT;DC_DEFAULTS.
Reading a record (4.3.0)
read_record(source, model) reads a Governed Data Record, the XML instance, and joins each value to the component
that defines it. source is the record's bytes, its text or a path; a record of another model is refused
(RecordError), as is anything that is not an sdc4:dm-<ct_id> record.
Record:attributes(instance_id,instance_version,creation_timestamp,current-state, ...),valuesin document order, andexceptional, the values that carry an Exceptional Value.RecordValue: thecomponent, itspathof clusters (root first),instancesparallel to the path (which occurrence each cluster is among the same cluster's repeats under the same parent;instance_keypairs them with the clusters' identifiers, one key per cluster instance), anoccurrenceindex for a component repeated within its cluster instance, itsposition, itselementsas the record holds them (a quantity's units nested:{"xdquantity-value": "1", "xdquantity-units": {"label": "Trade Units", "xdstring-value": "EA"}}), and itscontext(act,vtb,vte,tr,modified,latitude,longitude).ExceptionalValue: the ISO 21090 null flavor (code,name) and itsorigin:sourcewhen it stands in place of the value,recoverywhen sdcvalidator's recovery inserted it beside a value that failed its constraint. Forrecovery,RecordValue.rejectedis that value, kept so a person can see it.
Cluster members sit inside adapter elements that are not components of the model; the reader passes through them. It does not type, validate or interpret values: that is the caller's work (a mapper, an exporter, a checker).
MCP server
sdcreader is also an MCP server, registered as io.github.SemanticDataCharter/sdcreader, so an assistant can read a
published model the way sdcvalidator, sdcgovernance and sdcreceipt let it validate, govern and settle a record.
stdio, no SDK, no account, read-only.
uvx sdcreader # or: sdcreader-mcp, or python -m sdcreader.mcp_server
uvx sdcreader --host https://your-sdcstudio.example # a sovereign SDCStudio's public catalog
| Tool | Does |
|---|---|
find_models |
search the public catalog by text, or list a public project's models by name |
describe_model |
one model: title, project, root record, leaf and component counts by type, Dublin Core with SDCStudio's defaults as null, the schema URL pinned to its SHA-256 |
list_leaves |
the leaves in document order with path, type, constraints, code count and identity links, paged |
list_codes |
one component's enumerated values with IRI, definition and code system |
check_package |
the reader's integrity check on a package directory |
read_record |
a Governed Data Record on disk read against its model: attributes, then each value with its component, path, elements, context and Exceptional Value, paged; the model is the one the record names unless a source is given |
Each model tool takes a ct_id (fetched from the host the server was started with) or a package directory on disk.
No tool takes a URL: the host is fixed at start, so a caller cannot point the server elsewhere. Every tool calls the
same functions as the library; the two interfaces describe one model the same way.
Also listed on mcprush.
Tests
pip install -e ".[dev]"
python -m pytest tests -q # includes one fetch against production
python -m pytest tests -q -m "not network" # offline, as CI runs it
The fixture is the NHANES Participant package of the FAIR Data Demo, the record every projection is proven on.
Versioning
The leading 4 is the SDC4 reference model, as with every Semantic Data Charter package. An addition to what the reader exposes is a minor version, a fix a patch; the major changes only when the reference model does.
License
Apache-2.0 (see LICENSE, NOTICE).
sdcreader MCP Fragen
Wie füge ich sdcreader MCP zu Claude Code hinzu?
Führe claude mcp add sdcreader -- uvx sdcreader in deinem Terminal aus. Füge --scope user hinzu, damit der Server in jedem Projekt verfügbar ist.
Wie füge ich sdcreader MCP zu Cursor hinzu?
Öffne ~/.cursor/mcp.json und füge den Server unter mcpServers hinzu, mit der Cursor-Config aus dem Installationsabschnitt oben.
Wie kann ich nach Modellen suchen?
Du kannst das find_models Tool nutzen, um den öffentlichen Katalog per Text zu durchsuchen oder Modelle in einem öffentlichen Projekt per Name aufzulisten.
Kann der Server Datensätze lesen?
Ja, das read_record Tool liest einen Governed Data Record anhand seines Modells und liefert Attribute, Werte, Pfade und Kontext.
Benötigt der Server ein Konto?
Nein, der Server ist schreibgeschützt und benötigt kein Konto, um auf den öffentlichen Katalog zuzugreifen.