Is Power BI Modeling MCP Server safe?
What Power BI Modeling MCP Server does
The Power BI Authoring MCP Server lets an AI agent create and change Power BI semantic models, such as tables, columns, measures and relationships, in Power BI Desktop, Microsoft Fabric workspaces and local PBIP or TMDL files. The npm author field lists Microsoft; the package is a JavaScript wrapper that downloads the server. It uses the Azure Identity SDK for credentials, acts with your Fabric RBAC permissions, and passes access tokens to hosts listed in PBI_MODELING_MCP_ALLOWED_CONNECTION_HOSTS. Before installing, apply least-privilege roles as the README advises, and add only hosts your organization uses as Analysis Services or XMLA endpoints.
- Node.js shell/command execution
- Node.js network egress
What to do: Nothing here argues against installing it. Grant the capabilities it lists only if you expect the tool to need them.
Power BI Modeling MCP Server is an MCP server analyzed by SkillTotal's deterministic static scanner. The scan found no malicious indicators. It can: network egress and shell execution — capabilities are what the code can do, not a verdict on intent. Risk score 0/100 (low).
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Automated static-analysis result. It can contain false positives and false negatives, and is not a claim about the intent of Power BI Modeling MCP Server's authors. Report a false positive.
Behavioral traits
How this component maps to the CSA agentic threat model. Descriptive — it never affects the risk score.
Findings (2)
The component can run operating-system commands or spawn processes.
const { execFileSync } = require('child_process')Why it matters: Powerful and often legitimate — confirm the commands aren't built from untrusted input.
Fix: Confirm the command and its arguments are fully controlled and not derived from untrusted input; prefer execFile with an argument array.
The component makes outbound network requests.
const { get } = require('http')Why it matters: Usually legitimate, but confirm the destinations are expected and no sensitive data leaves.
Fix: Confirm the destination hosts are expected and that no sensitive data is sent off-host.
How attackers abuse these capabilities
Interactive labs on the attack class behind the rules above. They show the technique, not anything found in Power BI Modeling MCP Server.
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Scan your own componentHow we determine this: deterministic static analysis (regex + AST), evidence-anchored, no code execution. Methodology →