Power BI + AI via MCP: what actually works - and what to watch out for.

A practical breakdown built from real Reddit threads, independent tests, and production use cases. No hype - just what works, what breaks, and how to ship it safely.

"Full_Metal_Analyst added descriptions to 447 measures in one evening. Another writes: I feel more like a prompt machine than a PBI developer. This isn't the future - it's happening right now."

r/PowerBI thread, December 2025

30 SEC OVERVIEW

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What's covered

Bulk operations via MCP
WORKS

Rename 50+ measures, add descriptions to 200+ columns, build hierarchies - hours become minutes.
Debugging diverging measures
WORKS

Agent writes its own DAX test queries, runs them and traces why two measures disagree - what takes hours manually.
Complex DAX generation
PARTIAL

Looks plausible, often semantically wrong. Works for simple measures. Needs validation for anything with filter context.
Corporate data + Claude Pro
RISK

Pro plan may use data for training by default. API is different - but requires a contract, DPA, and setup.

Inside the guide

Ready-to-copy prompts DAX unit tests CI/CD schema Security checklist .pbip + LLM trick RACI table What-works matrix

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