sdcreader MCP server
Commit Nov 10, 2026Allows an AI client to search, describe, and read Semantic Data Charter models and governed data records.
Also known as SemanticDataCharter/sdcreader
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- Latest version
- 4.4.1
- Last commit
- Nov 10, 2026
- License
- Apache-2.0
What is sdcreader MCP?
sdcreader allows an AI client to search, describe, and read Semantic Data Charter models and governed data records.
Summary generated from the project's README
About sdcreader MCP server
Searching and interpreting Semantic Data Charter models and governed data records is what sdcreader enables for AI assistants. It allows a client to explore published models, examine their components, and read specific data records by joining values to their defining components. The server functions as a read-only interface that provides the same structural evidence used by projection writers to map data to standards like CDIF or DCAT-US.
Users can run the server via stdio using uvx, and it can be configured to connect to a sovereign SDCStudio public catalog by specifying a host. It requires no account or SDK to operate. The server provides specific tools such as find_models for catalog searches, describe_model for retrieving metadata and schema URLs, list_leaves for viewing document order paths, and read_record for parsing XML instances against a model. It ensures data integrity by verifying that schema bytes match the published SHA-256 hashes.
What you can do with it
- 1Search the public catalogFind specific Semantic Data Charter models by searching for text or listing models within a public project.
Written from the project's README. Every use case is checked against a quote from it.
How to install sdcreader MCP
Formats verified 10 Nov 2026Install sdcreader MCP in Claude Code
$ claude mcp add sdcreader -- uvx sdcreaderInstall sdcreader MCP in Cursor
~/.cursor/mcp.json
{
"mcpServers": {
"sdcreader": {
"command": "uvx",
"args": [
"sdcreader"
]
}
}
}Install sdcreader MCP in VS Code
.vscode/mcp.json
{
"servers": {
"sdcreader": {
"type": "stdio",
"command": "uvx",
"args": [
"sdcreader"
]
}
}
}Install sdcreader MCP in Claude Desktop
claude_desktop_config.json
{
"mcpServers": {
"sdcreader": {
"command": "uvx",
"args": [
"sdcreader"
]
}
}
}Install sdcreader MCP in Codex
~/.codex/config.toml
[mcp_servers.sdcreader] command = "uvx" args = ["sdcreader"]
Install sdcreader MCP in Gemini CLI
~/.gemini/settings.json
{
"mcpServers": {
"sdcreader": {
"command": "uvx",
"args": [
"sdcreader"
]
}
}
}README
View on GitHubsdcreader
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 questions
How do I add sdcreader MCP to Claude Code?
Run claude mcp add sdcreader -- uvx sdcreader in your terminal. Add --scope user to make it available in every project.
How do I add sdcreader MCP to Cursor?
Open ~/.cursor/mcp.json and add the server under mcpServers, using the Cursor config shown in the install section above.
How can I search for models?
You can use the find_models tool to search the public catalog by text or list models in a public project by name.
Can the server read data records?
Yes, the read_record tool reads a Governed Data Record against its model, providing attributes, values, paths, and context.
Does the server require an account?
No, the server is read-only and does not require an account to access the public catalog.