Context7
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作者による説明(英語の原文)
Read published Semantic Data Charter models: catalog search, record structure, codes, pinned schema.
この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。
このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。
使っているAIアプリを選んで、設定をコピーしてください。
必要なもの
どのアプリを使っていますか?
上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。
Claude Desktop → Settings → Developer → Edit Config を開き、claude_desktop_config.json にこれを貼り付けます
{
"mcpServers": {
"sdcreader": {
"command": "uvx",
"args": [
"sdcreader"
]
}
}
}ターミナルでこれを実行します
claude mcp add sdcreader -- uvx sdcreaderプロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"sdcreader": {
"command": "uvx",
"args": [
"sdcreader"
]
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
プロジェクトの .vscode/mcp.json に貼り付けます
{
"servers": {
"sdcreader": {
"type": "stdio",
"command": "uvx",
"args": [
"sdcreader"
]
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
これはパソコンで動くサーバーですが、ChatGPTがつなげるのはインターネット上のサーバーだけです。ほかのアプリを選んでください。
選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。
この設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。
パソコンで動くサーバーです。インストールすると、ツール一覧がAIアプリに表示されます。
誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月6日にチェック
レジストリ名は、リポジトリを所有するGitHubアカウント SemanticDataCharter で確認済みです
このリポジトリはまだGitHubから読み取っていません
このリポジトリはまだGitHubから読み取っていません
これはパソコンで動くため、インターネット上のエンドポイントはありません
パソコンで動き、代わりにローカルの設定を使います
パソコンで動くサーバーです。ツール一覧を読み取れるのは、インターネット上のエンドポイントがある場合だけです
レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。
当てはまる基本チェック1項目のうち1項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。
レジストリには必須のキーは載っていません。ただし、最初に使うときにサインインを求めるサーバーもあります。
あなたのパソコンで動きます。必要なときにAIアプリが起動し、データは作者のサーバーを通りません(サーバー自体がオンラインサービスを呼び出す場合を除きます)。
GitHubリポジトリの最終更新は–、最新バージョン(4.4.1)がレジストリに届いたのは11 日前です。
Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。パソコンにPython (uv)も必要です。
同じカテゴリには:Context7, Codebase Memory, Exa
同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。
カードの見方:★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日i
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作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。
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
SDCStudio generates a package for every published model and serves it publicly for models in public projects:
GET /api/v1/catalog/dm/ / | the catalog record: title, description, project, the artifact list (catalog.json) |
GET /api/v1/catalog/dm/ / / | a storage pointer, {"download_url": ..., "filename": ..., "storage": "gcs"}, for jsonld, xsd and the rest; the reader follows it |
dm- .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- .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- .xsd) |
GET /dmlib/dm- .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.
?sha256=), the public catalog URL, and check().title, description, root (the governed record's cluster), components by identifier, leaves in document order (each a Leaf with its component, its path of clusters and a slug of that path, unique in the record), codes (the enumerated values per component as Code: value, IRI, definition, the code it is defined by), metadata (the JSON-LD's) and header (the schema's Dublin Core).contributors, subjects (the semicolon list), rights_url and rights_statement derive from it.sdc_type, label, description, data_type, constraints, links by predicate (link(p) for the first), contains, iri.IDENTIFIER, SOURCE, PUBLISHER, EXACT, CLOSE, SEE_ALSO, HAS_UNIT; DC_DEFAULTS.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- record.
attributes (instance_id, instance_version, creation_timestamp, current-state, ...), values in document order, and exceptional, the values that carry an Exceptional Value.component, its path of clusters (root first), instances parallel to the path (which occurrence each cluster is among the same cluster's repeats under the same parent; instance_key pairs them with the clusters' identifiers, one key per cluster instance), an occurrence index for a component repeated within its cluster instance, its position, its elements as the record holds them (a quantity's units nested: {"xdquantity-value": "1", "xdquantity-units": {"label": "Trade Units", "xdstring-value": "EA"}}), and its context (act, vtb, vte, tr, modified, latitude, longitude).code, name) and its origin: source when it stands in place of the value, recovery when sdcvalidator's recovery inserted it beside a value that failed its constraint. For recovery, RecordValue.rejected is 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).
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.
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.
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.
Apache-2.0 (see LICENSE, NOTICE).