Can Dax Query help me build and manage DAX queries?

Yes, it offers a first-class query builder save flow for `.dax` and `.dax.queryBuilder` artifacts, enabling you to save structured query definitions and even scaffold portable Python workspaces from validated DAX queries.

How does Dax Query enhance AI client integration?

It provides a connection-centric MCP server, allowing AI clients to discover available connections, leverage curated markdown context files for accurate query generation, and execute DAX queries efficiently.

Which semantic models can Dax Query connect to?

It primarily supports Power BI datasets and Analysis Services semantic models, enabling powerful querying capabilities against these data sources for analytics and reporting.

What are the main system requirements for Dax Query?

Dax Query requires Windows (due to its reliance on COM/ADODB for DAX execution), `MSOLAP` / Analysis Services client libraries, Python 3.12+, and `uv` for package management.

Dax Query

Name: Dax Query
Author: wes-stone

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Execute DAX and metadata queries against Power BI and Analysis Services semantic models, supporting both CLI operations and AI client integration.

Dax Query is a Windows-first Python package tailored for DAX professionals, streamlining interactions with Power BI and Analysis Services semantic models. It provides a command-line interface for executing pre-configured queries and a comprehensive query-builder save flow that generates both `.dax` and structured `.dax.queryBuilder` artifacts. Designed with AI clients in mind, it includes a connection-centric MCP server and allows for context-rich metadata through markdown files. A key capability is its ability to scaffold self-contained Python workspaces from validated DAX queries, enhancing portability and sharing of analysis.

主な機能

01Connection-centric MCP server for AI clients with markdown context files.

02CLI for running configured DAX queries with preview options.

03Scaffolding portable Python workspaces from validated DAX queries.

040 GitHub stars

05Inspect semantic model schemas using safe `$SYSTEM.MDSCHEMA_*` rowsets.

06First-class query builder save flow for `.dax` and `.dax.queryBuilder` artifacts.

ユースケース

01Convert Excel PivotTable layouts into `SUMMARIZECOLUMNS` DAX queries for advanced analysis, inspection, or sharing.

02Generate and validate DAX queries via AI or CLI, then open them in DAX Studio for visual editing, profiling, and execution.

03Export validated DAX queries into self-contained Python projects for sharing, running with `uv run`, or embedding in Jupyter/Fabric notebooks.