Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Beschreibung vom Entwickler (englisches Original)
Turn Microsoft Fabric tables into an explainable graph and a GraphQL API.
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.
Funktioniert in Claude im Web, auf dem Desktop und auf dem Handy:
https://krusgraph.com/mcpFühre das in deinem Terminal aus
claude mcp add --transport http krusgraph https://krusgraph.com/mcpIn .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"krusgraph": {
"url": "https://krusgraph.com/mcp"
}
}
}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": {
"krusgraph": {
"type": "http",
"url": "https://krusgraph.com/mcp"
}
}
}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.
ChatGPT verbindet sich nur mit Servern im Internet:
https://krusgraph.com/mcpMenünamen können sich je nach Tarif und mit der Zeit leicht unterscheiden.
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.
Die Tool-Liste dieses Servers haben wir noch nicht gelesen; wir prüfen die Endpunkte reihum.
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 Herausgeber (krusgraph.com) ist nicht der Repo-Inhaber (Krusmaster); vielleicht hat jemand anderes ihn eingetragen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Noch nicht geprüft; wir prüfen die Endpunkte reihum
Noch nicht geprüft; wir prüfen die Endpunkte reihum
Noch nicht geprüft; wir lesen die Tool-Liste, wenn wir den Endpunkt prüfen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 0 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 in der Cloud des Entwicklers. Du verbindest dich übers Internet, ohne etwas zu installieren, aber was du sendest, läuft über die Server des Entwicklers.
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.8.0) kam vor 9 Tagen in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Er verbindet sich per URL, also funktionieren auch Apps, die Remote-MCP-Server akzeptieren, zum Beispiel ChatGPT im Entwicklermodus.
In derselben Kategorie: Spec Driven Development, Remote Desktop Commander, AI Deprecations
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.
AI model shutdown dates, replacements, change feed and webhook alerts for 8 providers.
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.
See how your business tables really connect – with the proof behind every link – so your reports, apps and agents get the numbers right.
Hosted as [Krusgraph](https://krusgraph.com): https://krusgraph.com/mcp for Claude, and https://krusgraph.com/mcp/connect for VS Code, Cursor and other MCP clients that register themselves (signed in and used on 27 October 2026 from VS Code, Cursor and Glama); sign-in with your Microsoft work account, every call with your own Fabric permissions. The guided demo and the demo graph run the same engine on a synthetic schema and need no account. This repository is the whole thing: engine, MCP server, website and deployment. Krusgraph is independent and not affiliated with Microsoft; "Microsoft Fabric" is used descriptively.
Try it without an account: [krusgraph.com/check](https://krusgraph.com/check). No account, no Fabric and no administrator needed. Drop CSV or Excel files, or paste a list of columns, and see how the tables connect and what is wrong with them. The files are read in your browser and are not uploaded. No files at hand? Four synthetic examples are one click away.
The problem. You have a lakehouse or warehouse in Fabric and you want an app on top of it — in Lovable, or generated by an agent in Cursor or Claude Code. Those tools can read a Fabric *API for GraphQL* item. They cannot make one. So before the first line of app code you spend an afternoon in the portal: create the GraphQL item, pick tables, define every relationship by hand (no relationships, no nested queries), register a service principal, grant it on the item, turn on introspection, copy the endpoint. Then the schema changes and you do the relationships again.
Microsoft's own GraphQL MCP server queries an API that already exists. Lovable's Fabric connector consumes one. As far as we have found (October 2026), nothing provisions one from inferred relationships; if you know of something that does, open an issue.
What this does. Reads the tables, infers keys and relationships from names (declared constraints win when a warehouse has them), writes the GraphQLApi item definition with ManyToOne / OneToMany relationships, creates the item — or updates it in place when the name exists — and prints the endpoint plus the two portal clicks the API cannot do yet.
%pip install git+https://github.com/Krusmaster/fabric-backend[deploy]
import fabric_backend as fb
out = fb.create(workspace=" ", source="my_lakehouse", name="shop_api", spark=spark, keys={"order_items": ["order_id", "line_no"]}) # optional here: rule K5 infers this one; keys overrides print(out["plan"].summary()) print(out["card"])
7 tables, 6 with keys, 6 relationships no key (query only; can reference others, cannot be referenced): audit_log GraphQL endpoint: https://api.fabric.microsoft.com/v1/workspaces/ /graphqlapis/ /graphql Still to do in the Fabric portal (no API for these yet): [ ] shop_api -> Settings -> Introspection -> On (workspace admin; Lovable needs this) [ ] shop_api -> Manage permissions -> add the service principal with 'Run Queries and Mutations'
Paste the endpoint, tenant id, client id and secret into Lovable's Fabric connector. Done.
pip install "fabric-backend[mcp]"
FABRIC_ODBC="Driver={ODBC Driver 18 for SQL Server};Server= ;Database= ;Authentication=ActiveDirectoryInteractive" \ fabric-backend-mcp
The same engine over the one connection in FABRIC_ODBC: list_tables, plan_backend (keys, relationships, Mermaid — nothing deployed), validate_plan, sample_rows, create_backend, rayfin_connector, ontology_draft, semantic_model_draft, join_path, data_dictionary, dbt_schema, analyze_schema, suggest_relationships and create_views (dry run by default). The tools that need Fabric item ids (describe_backend, plan_drift, app_starter, create_semantic_model, create_data_agent) live in the remote server only. Set FABRIC_SOURCE_KIND (Lakehouse, Warehouse, SQLDatabase) and FABRIC_SCHEMAS_ENABLED=1 for a lakehouse created with schemas so that semantic_model_draft writes schemaName; SQLServer for an on-prem or Azure SQL Server, where the two Fabric-only drafts answer with an explanation. Windows set-up with Claude Desktop, Windows sign-in and what works locally: docs/LOCAL.md. fabric-backend demo is the 20-minute demo on a laptop: one local page on 127.0.0.1 with the map, the health check with Accept / Skip and five questions run on the customer's own SQL Server or on a folder of CSV / Excel files; script in docs/DEMO-20-MIN.md. Add the stdio server to Claude Desktop (docs/LOCAL.md) or another MCP client that starts local stdio servers; only the Claude Desktop set-up is documented. The agent can then say *"give me a GraphQL API over orders, customers and products"* and get an endpoint back.
The hosted instance is https://krusgraph.com/mcp. Add it in Claude under Customize → Connectors → Add → Add custom connector and sign in with your Microsoft work account; your Entra admin consents once (https://krusgraph.com/start has the steps, https://krusgraph.com/docs the details). VS Code, Cursor and other MCP clients that register themselves use https://krusgraph.com/mcp/connect: Krusgraph shows its own approval page for the client, then the Microsoft sign-in (https://krusgraph.com/docs#other-mcp-clients; tested on 27 October 2026 with VS Code, Cursor and Glama; docs/CLIENT-REGISTRATION.md). To run your own:
docker build -t fabric-backend-server . && docker run -p 8000:8000 \
-e FABRIC_TENANT_ID=... -e FABRIC_CLIENT_ID=... -e FABRIC_CLIENT_SECRET=... fabric-backend-server
Streamable HTTP at /mcp, thirty-eight tools, every one with a title and a readOnlyHint/destructiveHint (the directory requires it): list_workspaces, list_sources, list_tables, plan_backend (nothing deployed; suggests composite keys), sample_rows, validate_plan (keys and relationships checked against the rows; by default a summary with every failing check in full, detail="full" for every check), create_backend (creates or updates one item, never deletes), describe_backend, query_graphql (read-only; mutations refused), rayfin_connector and ontology_draft; every tool takes the workspace by id or name. Five more read-only tools turn the same plan into the week's deliverables, all unit-tested and run against the demo workspace (synthetic shop data) on 26 and 27 October 2026:
semantic_model_draft — a Power BI semantic model in TMDL: Direct Lake tables on the SQL analytics endpoint, relationships with one active path per table pair, suggested measures with their reasons (the row count of each fact table, sums only where summarizeBy sums; never an id, code or year) and, when fact tables have date columns, a calendar marked as the date table; a README.generated.md with the decisions to check (fabric_backend/semantic_model.py cites the Microsoft sample definitions it follows). The measures and the calendar were added after 26 October and came back from the live run of 27 October (summarizeBy: none on ship_to_id).join_path — the shortest chain of relationships between two tables, rule per hop, ready T-SQL; or which relationship is missing.data_dictionary — hand-over documentation in Markdown with an empty Description column; validate=true adds counts.dbt_schema — a dbt sources file with unique, not_null and relationships tests (fabric_backend/dbt.py cites the dbt docs).domain_draft — proposed domains (candidate data products) from the plan's graph, the relationships that cross them, unassigned tables and one ODCS v3.2.0 data contract per domain; Fabric domains are created by the customer's admin (docs/DOMAINS.md). Unit tests only.plan_drift — today's plan against an existing API for GraphQL item: what a create_backend with that name would change.Four more tools create things from the same plan, each dry_run=true by default so the first answer is exactly what would be created, each creating or updating in place under a name and never deleting (create_report only creates); all unit-tested with Fabric mocked. On 27 October 2026 the first three ran as dry runs against the demo lakehouse; create_semantic_model then created shop_model_live live on 29 October 2026 (reviewed in the Fabric portal the same day; shop_model updated in place from Lovable on 30 October 2026) and create_report created shop_report_live and shop_report live on 30 October 2026 (opened and reviewed in the Fabric portal the same day), while creating with create_views or create_data_agent is unit-tested only (the status per tool: https://krusgraph.com/docs#test-status). The delegated permissions they need, against what the app has today, and the az commands to add them are in docs/SCOPES.md:
create_semantic_model — a SemanticModel item from the TMDL draft (POST /semanticModels, updateDefinition); needs SemanticModel.ReadWrite.All or Item.ReadWrite.All (Item.ReadWrite.All granted since 28 October 2026).create_views — CREATE OR ALTER VIEW in a schema of its own (krusgraph) on the SQL analytics endpoint or warehouse: a wide view per fact table, one per header table (vw_orders: each order with its customer and, once orders.ship_to_id is confirmed, its ship-to address; in the dry run of 27 October, not yet created live) and one per hard-to-read relationship; needs no new scope, only the SQL right to create objects.create_data_agent — a Fabric data agent through the public staging API: the plan as instructions, the source as data source, 5–10 example questions with T-SQL, published; needs Item.ReadWrite.All (granted since 28 October 2026).create_report — an empty Power BI report (one blank page, no visuals) bound to an existing semantic model (POST /reports with creationPayload.semanticModelReference); a report of that name is left alone, never updated or deleted; needs Report.ReadWrite.All or Item.ReadWrite.All. Experimental; created live on 30 OctoberNur der Anfang wird gezeigt; den Rest findest du im Repo