Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
제작자가 쓴 설명(영어 원문)
Turn Microsoft Fabric tables into an explainable graph and a GraphQL API.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
웹, 데스크톱, 모바일의 Claude에서 쓸 수 있어요:
https://krusgraph.com/mcp터미널에서 이 명령어를 실행하세요
claude mcp add --transport http krusgraph https://krusgraph.com/mcp프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"krusgraph": {
"url": "https://krusgraph.com/mcp"
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"krusgraph": {
"type": "http",
"url": "https://krusgraph.com/mcp"
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요:
https://krusgraph.com/mcp메뉴 이름은 요금제나 시기에 따라 조금 다를 수 있어요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
아직 이 서버의 도구 목록을 읽지 않았어요. 엔드포인트는 차례대로 돌아가며 점검해요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검
게시자(krusgraph.com)가 저장소 소유자(Krusmaster)가 아니에요. 다른 사람이 등록했을 수 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 점검하지 않았어요. 엔드포인트는 차례대로 돌아가며 점검해요
아직 점검하지 않았어요. 엔드포인트는 차례대로 돌아가며 점검해요
아직 점검하지 않았어요. 엔드포인트를 점검할 때 도구 목록을 읽어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 0개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
제작자의 클라우드에서 실행돼요. 설치 없이 인터넷으로 연결하지만, 보내는 내용은 제작자의 서버를 거쳐요.
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.8.0)은 9일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. URL로 연결되기 때문에, 원격 MCP 서버를 지원하는 앱(예: 개발자 모드의 ChatGPT)에서도 쓸 수 있어요.
같은 카테고리에는: Spec Driven Development, Remote Desktop Commander, Dechonet MCP
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
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제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
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 October앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요