mcp-engine-public

Validate Power BI changes with tests and checkpoints. Use when creating or running model tests, exporting results, managing baselines or snapshots, checking dependency impact before refactors, or using checkpoints, changesets, rollback, and stable model identity.

Handle Power BI security and governance workflows. Use when defining or validating RLS or OLS, perspectives, policies, masking rules, or audit workflows, and when distinguishing between security enforcement and model curation.

Guide new SemanticOps MCP users through a plain-language setup concierge for licensing, modes, masking, guardrails, preferences, model safety, tests, reporting, diagnostics, RLS testing, and Enterprise posture. Use when a user types onboarding, asks to set up SemanticOps MCP, wants help choosing Free vs Pro, or wants MCP tailored to their workflow.

Author and refine Power BI semantic layer logic. Use when creating or updating measures, calculation groups, named expressions, DAX UDFs, Power Query parameters, model properties, or semantic naming and style patterns, and when deciding between measures and calculated columns.

Prepare and recover Power BI SemanticOps MCP sessions. Use when starting a session, connecting to a model, checking current connection, applying preferences, selecting the right tool family, troubleshooting empty results or stale metadata, or fixing malformed tool arguments and bulk payloads.

Write, review, scope, execute, and analyze DAX queries in Power BI models. Use when creating or fixing DAX queries, deciding between run_query operations, investigating performance or VertiPaq issues, testing RLS access, or discovering schema before querying.

Plan and execute Power BI physical model changes. Use when creating or updating tables, columns, relationships, hierarchies, calendars, partitions, or refresh strategy, especially when changes may affect dependencies, data shape, or refresh behavior.

Assess Power BI semantic models for bad or questionable modeling practices and produce a source-backed quality scorecard. Use when reviewing model quality, semantic model assessment, semantic model best practices, star schema fit, relationships, DAX maintainability, VertiPaq/storage risk, metadata hygiene, governance signals, validation gaps, or when the user asks for a scorecard, recommendations, model audit, model quality review, bad practices review, best practices audit, or best practices assessment.

Assess Power BI semantic models for Copilot, Fabric data agent, and natural-language Q&A readiness. Use when reviewing whether a model has clear business terminology, unambiguous metrics, usable date defaults, focused field exposure, descriptions, AI instructions, AI data schema recommendations, verified-answer candidates, or natural-language validation tests.