REA
Reverse engineer anything from your terminal or agent with one CLI and MCP server.
HealthDCAT-AP catalogs of published Semantic Data Charter models; Turtle or JSON-LD; no account.
Pick the AI app you use, then copy the settings.
Passed 3/3 checks · Runs on your computer
First: which AI do you use?
Pick your app and the steps appear below.
Works with Claude, with some setup first
Install Python (uv) on your computer first (one time) · Only the Claude desktop app (Windows or Mac), not the web or phone
One time only; it works for every server that needs Python (uv)
SettingsDeveloperEdit Config
Checking the commands · copy buttons appear once they pass
Use Sdchealthdcatap and tell me what you can do for me, then show me one thing✓ If Claude says it is using Sdchealthdcatap or shows a Sdchealthdcatap tool in the answer, you are connected
Menu names checked against Anthropic’s help page on Nov 11, 2026 · your screen may differ slightly by app version
ChatGPT cannot connect Sdchealthdcatap yet
Sdchealthdcatap runs on your computer, but ChatGPT can only connect servers that run on the web
A · Use an app that can connect Sdchealthdcatap
B · Others in Developer tools that work with ChatGPT
Picked from the most used in the same category, only ones that connect by address with no key
Works with Claude Code, with some setup first
Install Python (uv) on your computer first (one time)
One time only; it works for every server that needs Python (uv)
Mac: press Command+Space and type Terminal · Windows: open PowerShell
Checking the commands · copy buttons appear once they pass
You should see Sdchealthdcatap listed as connected
Use Sdchealthdcatap and tell me what you can do for me, then show me one thing✓ If Claude Code says it is using Sdchealthdcatap or shows a Sdchealthdcatap tool in the answer, you are connected
Menu names checked against Anthropic’s help page on Nov 11, 2026 · your screen may differ slightly by app version
Works with Cursor, with some setup first
Install Python (uv) on your computer first (one time)
One time only; it works for every server that needs Python (uv)
Checking the commands · copy buttons appear once they pass
Use Sdchealthdcatap and tell me what you can do for me, then show me one thing✓ If Cursor says it is using Sdchealthdcatap or shows a Sdchealthdcatap tool in the answer, you are connected
Menu names checked against Cursor’s help page on Nov 11, 2026 · your screen may differ slightly by app version
Works with VS Code, with some setup first
Install Python (uv) on your computer first (one time)
One time only; it works for every server that needs Python (uv)
Checking the commands · copy buttons appear once they pass
Use Sdchealthdcatap and tell me what you can do for me, then show me one thing✓ If VS Code says it is using Sdchealthdcatap or shows a Sdchealthdcatap tool in the answer, you are connected
Menu names checked against VS Code’s help page on Nov 11, 2026 · your screen may differ slightly by app version
Other apps that use MCP, such as Windsurf, Zed or Gemini CLI, each add servers differently. See how in the app list.
JSON settings are under “For developers” below
Claude Code
Checking the commands · copy buttons appear once they pass
Claude Desktop (claude_desktop_config.json)
Checking the commands · copy buttons appear once they pass
Cursor (~/.cursor/mcp.json)
Checking the commands · copy buttons appear once they pass
VS Code (mcp.json)
Checking the commands · copy buttons appear once they pass
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Based on how this server connects and on each app’s own docs, checked Nov 10, 2026.
Run on your computer in
ClaudeGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatRaycast
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 13, 2026
The registry name was verified with the GitHub account SemanticDataCharter, which owns the repo
Code last changed 3 days ago
Uses Apache-2.0
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Ask, share a tip or report that it does not work. Sorted by what people marked helpful.
No posts yet. Be the first to ask or share.
Posts here are written by users, not the PopNx team.
No reviews yet
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 3 of 3 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed 3 days ago, and the latest version (4.1.1) reached the registry 18 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.
Servers in the same category from other makers, sorted by stars.
Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Reverse engineer anything from your terminal or agent with one CLI and MCP server.
A powerful toolkit for coding, providing semantic retrieval and editing capabilities.
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
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.
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:
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:version | as the DCAT-AP writer does, from the package |
dct:accessRights | NON_PUBLIC from the Access Rights NAL (declared; it selects the validator's shape set) |
dcatap:applicableLegislation | the 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:custodian | the 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:theme | RQSH (research cohorts, questionnaires and surveys), noncommunicable diseases, STATISTICAL, HEAL (declared) |
dcat:distribution | the 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:page | the schema at its stable URL, described as the data dictionary |
healthdcatap:numberOfRecords, numberOfUniqueIndividuals, minTypicalAge, maxTypicalAge, populationCoverage | 9,254; 9,254; 0; 80; the NHANES population (declared) |
dpv:hasPersonalData, dpv:hasLegalBasis, dpv:hasPurpose | age, gender and health record from the DPV personal-data taxonomy; the basis and purpose as text (declared) |
dqv:hasQualityAnnotation | a 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.
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.
Declared rather than read from the package, and said so here:
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:
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.
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.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.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).foaf:page.