Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Beschreibung vom Entwickler (englisches Original)
Deterministic SHACL-based assessment and comparison for digital passport data models.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
Du brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein
{
"mcpServers": {
"dpawb": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/ce-rise-software/dpawb-mcp:0.1.2"
]
}
}
}Führe das in deinem Terminal aus
claude mcp add dpawb -- docker run -i --rm ghcr.io/ce-rise-software/dpawb-mcp:0.1.2In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"dpawb": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/ce-rise-software/dpawb-mcp:0.1.2"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"dpawb": {
"type": "stdio",
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/ce-rise-software/dpawb-mcp:0.1.2"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 6. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto CE-RISE-software bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.1.2) kam vor 6 Monaten in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Docker auf deinem Computer.
In derselben Kategorie: Spec Driven Development, Remote Desktop Commander, Recta
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Cheaper cross-chain stablecoin routes for AI agents; 5 % of the verified saving, nothing if none.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
A Python toolkit and thin CLI for SHACL-based assessment of digital passport data models, pairwise comparison of composed solutions, and SHACL-only use-case coverage analysis.
This README is primarily a repository and development entry point. The user-facing conceptual and usage reference is at the published documentation site. The repository-source docs remain available in docs/.
dpawbdpawb-mcpThe tool is designed primarily as an agent-usable analytical toolkit with a thin CLI. The core command surface is:
assesscoveragecompareprioritizerecommend-compositionschemavocabularytemplatecapabilitiessummarizeThe intended primary integration mode is an AI agent orchestrating the analytical pipeline through the package API or the CLI. In practice, this means:
The CLI remains useful for direct human invocation, but the main product shape is an analytical engine that can be called by agent skills, workflow runners, or tool adapters.
The package also ships a thin stdio MCP server over the same deterministic command surface:
assesscoveragecompareprioritizerecommend-compositionschemavocabularytemplatecapabilitiessummarizeThe MCP surface stays intentionally thin:
dpawb as the core Python packagedpawb-mcpThe MCP runtime and publication shape are documented in the published MCP server page.
The public Python API is documented in the published API reference.
The MCP server is published with this identity:
io.github.CE-RISE-software/dpawbghcr.io/ce-rise-software/dpawb-mcp: stdiohttps://registry.modelcontextprotocol.io/The server is discoverable in the official MCP Registry under the name io.github.CE-RISE-software/dpawb.
Registry discovery page:
https://registry.modelcontextprotocol.io/?q=dpawbLocal client configuration example:
{
"mcpServers": { "dpawb": { "command": "dpawb-mcp" } } }
OCI-oriented registry metadata is declared in server.json. The publish workflow fills in the release version and image tag when publishing.
python -m venv .venv
. .venv/bin/activate pip install -e .
Published package name:
pip install dpawb
The installed MCP server command is:
dpawb-mcp
If you are working in a restricted environment, the package is configured to build with setuptools so editable installs do not depend on fetching an extra build backend.
If build isolation or wheel support is unavailable locally, use:
python -m pip install --no-build-isolation -e .
In constrained environments where editable installation is blocked by local Python packaging tooling, the repository still supports a repo-native execution path:
./scripts/run-local.sh capabilities
./scripts/test-local.sh make smoke make test make validate
Minimal local MCP runtime command:
python -m dpawb.mcp_server
dpawb assess --profile fixtures/profiles/synthetic_evolution_latest.yaml
dpawb coverage --profile fixtures/profiles/synthetic_evolution_latest.yaml --use-case fixtures/use_cases/product_identity_lookup.yaml dpawb compare --left left_assessment.json --right right_assessment.json dpawb recommend-composition --left left_assessment.json --right right_assessment.json --comparison comparison_result.json dpawb summarize --result comparison_result.json --format markdown dpawb capabilities
Before wiring PyPI CI/CD, run the local packaging check in an environment with wheel available:
make release-check
This builds a wheel and sdist, installs the wheel into a clean temporary environment, and runs installed CLI smoke checks.
There are two distinct input areas in this repository:
fixtures/ Synthetic, repository-local test data only. These files are used by tests, smoke checks, and CI validation.examples/01-source-ingestion/ Live-source example inputs intended for manual runs. These are the first step in the tutorial progression and are not part of CI validation.The full examples tree is organized by analytical task, not by input data model:
examples/01-source-ingestion/ Load and assess declared profiles.examples/02-structural-comparison/ Compare two profile assessment results.examples/03-reduced-use-case-comparison/ Run the first aligned use-case comparison.examples/04-extended-use-case-comparison/ Run a broader aligned use-case comparison.examples/05-composition-recommendation/ Recommend a combined profile from two assessed model sets.Each example is usable by humans as a step-by-step command tutorial and by AI agents as a deterministic recipe over explicit files.
Example profiles for live SHACL sources are included at:
examples/01-source-ingestion/profiles/battery_dpp_representation_live.yamlexamples/01-source-ingestion/profiles/battery_product_identification_live.yamlexamples/01-source-ingestion/profiles/dp_record_metadata_live.yamlexamples/01-source-ingestion/profiles/traceability_and_life_cycle_events_live.yamlexamples/01-source-ingestion/profiles/metadata_focused_composition_live.yamlexamples/01-source-ingestion/profiles/metadata_and_traceability_live.yamlexamples/02-structural-comparison/profiles/metadata_slice_left_live.yamlexamples/02-structural-comparison/profiles/metadata_slice_right_live.yamlIf you want a single live source, the metadata-oriented example is the main starting point:
./scripts/run-local.sh assess --profile examples/01-source-ingestion/profiles/dp_record_metadata_live.yaml
If you want a composed profile, use:
./scripts/run-local.sh assess --profile examples/01-source-ingestion/profiles/metadata_and_traceability_live.yaml
You can also run the traceability-only example:
./scripts/run-local.sh assess --profile examples/01-source-ingestion/profiles/traceability_and_life_cycle_events_live.yaml
For manual coverage runs, example use cases are included at:
examples/01-source-ingestion/use_cases/battery_dpp_representation.yamlexamples/01-source-ingestion/use_cases/battery_product_identification.yamlexamples/01-source-ingestion/use_cases/battery_passport_metadata_and_classification.yamlexamples/01-source-ingestion/use_cases/record_identity_lookup.yamlexamples/01-source-ingestion/use_cases/provenance_actor_lookup.yamlExample:
./scripts/run-local.sh coverage \
--profile examples/01-source-ingestion/profiles/dp_record_metadata_live.yaml \ --use-case examples/01-source-ingestion/use_cases/record_identity_lookup.yaml
The main real comparison-driver use case is:
examples/01-source-ingestion/use_cases/battery_dpp_representation.yamlIt intentionally stays narrow. It requires:
and the joins needed to treat those as one battery-DPP representation slice.
The matching starting composition for that use case is:
examples/01-source-ingestion/profiles/battery_dpp_representation_live.yamlIt currently composes:
dp_record_metadatatraceability_and_life_cycle_eventsThis is the current broader baseline for the battery-DPP comparison work.
For the first reduced real pass, the narrower identity-focused comparison slice is:
examples/03-reduced-use-case-comparison/examples/03-reduced-use-case-comparison/use_cases/use_case.yamlexamples/03-reduced-use-case-comparison/profiles/left_profile.yamlexamples/03-reduced-use-case-comparison/profiles/right_profile.yamlThis reduced slice composes:
dp_record_metadataproduct_profiletraceability_and_life_cycle_eventsand is the first validated product-identification comparison slice against the BatteryPass General Product Information model.
A second broader validated slice is also included:
examples/04-extended-use-case-comparison/examples/04-extended-use-case-comparison/use_cases/use_case.yamlexamples/04-extended-use-case-comparison/profiles/left_profile.yamlexamples/04-extended-use-case-comparison/profiles/right_profile.yamlThis slice adds passport version/revision and battery type/classification while keeping the same CE-RISE composed model set.
The two current cross-ecosystem validation notes are:
examples/03-reduced-use-case-comparison/notes/comparison_note.mdexamples/04-extended-use-case-comparison/notes/comparison_note.mdThe step-by-step user reference for these examples is in the published example applications guide.
For manual comparison runs, a comparison-ready live pair is included with the same declared scope label:
examples/02-structural-comparison/profiles/metadata_slice_left_live.yamlexamples/02-structural-comparison/profiles/metadata_slice_right_live.yamlexamples/02-structural-comparison/alignments/metadata_slice_alignment.yaml as a starting-point alignment exampleTypical flow:
./scripts/run-local.sh assess --profile examples/02-structural-comparison/profiles/metadata_slice_left_live.yaml --output /tmp/left.json
./scripts/run-local.sh assess --profile examples/02-structural-comparison/profiles/metadata_slice_right_live.yaml --output /tmp/right.json ./scripts/run-local.sh compare --left /tmp/left.json --right /tmp/right.json
With an explicit analyst-authored alignment:
./scripts/run-local.sh compare \
--left /tmp/left.json \ --right /tmp/right.json \ --alignment examples/02-structural-comparison/alignments/metadata_slice_alignment.yaml
When an alignment file is provided, the comparison result now includes two alignment-oriented views:
evaluated_pairs Full per-pair presence status for every declared equivalence.ranked_alignment_observations Review-oriented gaps for any declared pair that is only present on one side or missing on both sides.So the main things to inspect in an alignment-aware comparison result are:
Nur der Anfang wird gezeigt; den Rest findest du im Repo