dax-query-mcp 0.2.1

Windows-first DAX and MCP toolkit for Power BI semantic models

dax-query-mcp

MCP server for running DAX queries against Power BI semantic models.

Check out making use of skills and extensions for getting better results since the MCP can't do it all

Features

• Connection-centric MCP server — discover models, query with DAX, inspect schemas
• Curated context — teach the LLM your model via markdown docs (no admin privileges needed)
• Fuzzy search — search columns and measures across tables by name or description
• Export anywhere — CSV, clipboard, Power Query M code, Streamlit apps, standalone Python projects
• Query builder — save .dax + .dax.queryBuilder artifacts, open directly in DAX Studio
• Workstation session — save, list, and batch-export queries during an exploration session

Prerequisites

1. Windows — the server uses COM/ADODB under the hood, so it's Windows-only.

2. MSOLAP provider — the OLE DB driver that talks to Power BI semantic models. Download from Microsoft — grab the "AMO + ADOMD.NET" or "MSOLAP (OLE DB)" installer. If you already have Power BI Desktop, Excel with Power Pivot, or SSMS installed, you likely have it.

   To check: open PowerShell and run:

   (New-Object System.Data.OleDb.OleDbEnumerator).GetElements() | Where-Object { $_.SOURCES_NAME -like "*MSOLAP*" }
   

   If that returns a row, you're good.

3. uv — Python package manager. Install with:

   winget install astral-sh.uv
   

Quick start

1. Install

From PyPI (recommended):

uvx --from dax-query-mcp dax-query-server

From source (for development or latest changes):

git clone https://github.com/wes-stone/dax-query-mcp.git
cd dax-query-mcp
uv sync

2. Add a connection

Create Connections/my_model.yaml:

connection_string: |
  Provider=MSOLAP.8;
  Data Source=powerbi://api.powerbi.com/v1.0/myorg/MyWorkspace?readonly;
  Initial Catalog=MySemanticModel

description: "My semantic model"
command_timeout_seconds: 1800

Optionally add Connections/my_model.md alongside it to document tables, measures, and common filters for the LLM.

3. Wire up MCP

Add to .copilot/mcp.json (or your MCP client config):

Using PyPI (via uvx):

{
  "mcpServers": {
    "dax-query-server": {
      "command": "uvx",
      "args": ["--from", "dax-query-mcp", "dax-query-server"],
      "env": {
        "DAX_QUERY_MCP_CONNECTIONS_DIR": "C:\\absolute\\path\\to\\Connections"
      }
    }
  }
}

Using a local clone:

{
  "mcpServers": {
    "dax-query-server": {
      "command": "uv",
      "args": ["run", "--directory", "C:\\path\\to\\dax-query-mcp", "dax-query-server"],
      "env": {
        "DAX_QUERY_MCP_CONNECTIONS_DIR": "C:\\absolute\\path\\to\\Connections"
      }
    }
  }
}

Tip: DAX_QUERY_MCP_CONNECTIONS_DIR lets you share one Connections/ folder across workspaces.

4. Run your first query

Ask Copilot (or any MCP client):

"List connections, then run a DAX query against my model."

The server returns plain markdown — results render as tables directly in chat.

Connection YAML

connection_string: "..." # required — MSOLAP connection string
description: "..." # human-readable label
command_timeout_seconds: 1800 # DAX query timeout
connection_timeout_seconds: 300 # connection open timeout
max_rows: null # row cap (null = unlimited)
suggested_skill: "..." # optional — hint an MCP client toward a specific skill
suggested_skill_reason: "..." # optional — why that skill is relevant

MCP tools

Tool	Purpose
Discovery
list_connections	Discover available connections
get_connection_context	Curated markdown context (tables, columns, measures)
search_connection_context	Search context docs for specific terms
inspect_connection	Live schema via safe MDSCHEMA rowsets
Querying
run_connection_query	Run DAX against a named connection
run_ad_hoc_query	Run DAX against a raw connection string
Search
search_columns	Fuzzy-search columns across tables
search_measures	Fuzzy-search measures by name or expression
Export
export_to_csv	Export results to a timestamped CSV
copy_to_clipboard	Copy results to clipboard (TSV or markdown)
scaffold_power_query	Generate Power Query M code for Excel
scaffold_streamlit_app	Generate a Streamlit visualization app
scaffold_dax_workspace	Scaffold a standalone Python project
quick_chart	Render a bar/line/pie chart as PNG
Query builder
save_query_builder	Save .dax + .dax.queryBuilder artifacts
get_query_builder	Load a saved query builder definition
get_query_builder_schema	Get the expected JSON payload shape
Workstation
save_to_workstation	Save a query to the session workstation
list_workstation	List saved workstation queries
export_workstation	Batch-export workstation as scaffold or .dax files

Admin queries are blocked. INFO.*() and $SYSTEM.DISCOVER_* require server admin rights. Use get_connection_context or inspect_connection for metadata.

CLI usage

# List configured queries
dax-query --list --config-dir queries

# Run a query
dax-query --query my_query --preview --config-dir queries

# Inspect a connection schema
dax-query --inspect-connection my_model --connections-dir Connections

# Save a query builder artifact
dax-query-builder --save-query-builder-from builder.json --config-dir queries

Saved .dax files open directly in DAX Studio. See docs/ for detailed CLI documentation.

Copilot guard hook

A pre-commit hook reviews staged changes for private content (real workspace URIs, local paths, non-sample connection files).

# Install
powershell -ExecutionPolicy Bypass -File .\scripts\install-git-hooks.ps1

# Runs automatically on commit:
dax-query-guard --mode staged

Add repo-specific patterns via .copilot-guard.local.json:

{
  "blocked_content_patterns": [
    {
      "pattern": "PrivateWorkspace|InternalDataset",
      "reason": "Internal identifiers"
    }
  ]
}

Fails closed by default. Set COPILOT_GUARD_FAIL_OPEN=1 to allow commits when Copilot CLI is unavailable.

Requirements

• Windows (COM/ADODB used for DAX execution)
• MSOLAP OLE DB provider (see Prerequisites)
• Python 3.12+ (handled automatically by uvx)
• uv (winget install astral-sh.uv)