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mdspinali/powerbi-mcp-workshop

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2 Hours (Hands-On Lab Format) Power BI Developers familiar with semantic models, new to MCP VS Code + GitHub Copilot + Power BI Desktop Sales & Returns Sample v201912.pbix (download from Microsoft)

Обзор

2 Hours (Hands-On Lab Format) Power BI Developers familiar with semantic models, new to MCP VS Code + GitHub Copilot + Power BI Desktop Sales & Returns Sample v201912.pbix (download from Microsoft) - 2 Hours | Hands-On Lab | VS Code + Copilot - AI-Powered Semantic Model Development - github.com/microsoft/powerbi-modeling-mcp - What is MCP? Protocol fundamentals - Power BI Modeling MCP architecture - Install VS Code extension - Configure GitHub Copilot - Download sample report & save as PBIP - Set up two-folder workspace - Connect MCP to Power BI Desktop Everyone connected and making their first MCP call - Bulk rename columns & measures - Add descriptions across model - Create KPI Measures table with complex DAX - Build Product Performance calculated table - Add fiscal calendar columns & time intelligence - Create Calculation Groups (Time & Currency) - Implement Row-Level Security (static roles by store type/product category) - Create Perspectives & generate documentation - Git...

README

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Power BI Modeling MCP Server Workshop

Deep Dive: AI-Powered Semantic Model Development

Duration: 2 Hours (Hands-On Lab Format)
Audience: Power BI Developers familiar with semantic models, new to MCP
Tools: VS Code + GitHub Copilot + Power BI Desktop
Sample Report: Sales & Returns Sample v201912.pbix (download from Microsoft)


HOUR 1: Setup & Architecture (~60 minutes)


Title

Power BI Modeling MCP Server
Deep Dive Workshop


Workshop Agenda

Hour 1 — Setup & Architecture

  • What is MCP? Protocol fundamentals
  • Power BI Modeling MCP architecture
  • Install VS Code extension
  • Configure GitHub Copilot
  • Download sample report & save as PBIP
  • Set up two-folder workspace
  • Connect MCP to Power BI Desktop

Goal: Everyone connected and making their first MCP call

Hour 2 — Hands-On Lab

  • Lab 1: Bulk rename columns & measures
  • Lab 2: Add descriptions across model
  • Lab 3: Create KPI Measures table with complex DAX
  • Lab 4: Build Product Performance calculated table
  • Lab 5: Add fiscal calendar columns & time intelligence
  • Lab 6: Create Calculation Groups (Time & Currency)
  • Lab 7: Implement Row-Level Security (static roles by store type/product category)
  • Lab 8: Create Perspectives & generate documentation
  • Lab 9: Git commit, push, and rollback
  • Lab 10: Fix report visual references (separate VS Code window)

Goal: Complete real-world model changes with CI/CD safety net


What is MCP?

Model Context Protocol — The bridge between AI and your tools

MCP is an open protocol that standardizes how AI assistants connect to external tools, data sources, and services. Think of it as a universal adapter between LLMs and the real world.

Three Core Components:

Component Description
TOOLS Functions the AI can call to perform actions (create measure, modify table, execute DAX)
RESOURCES Data and context the AI can read (model metadata, DAX patterns, documentation)
PROMPTS Pre-built templates for common tasks (connect, query, analyze performance)

Key Insight

MCP servers run locally on your machine. Your data never leaves your environment — the AI sends commands, not your data.

Reference: modelcontextprotocol.io


Architecture Overview

Data Flow Diagram

┌─────────────────────────────────┐
│     YOU                         │
│     VS Code + GitHub Copilot    │
│     (Natural language prompts)  │
└───────────────┬─────────────────┘
                │
                │ MCP Protocol (stdio)
                ▼
┌─────────────────────────────────┐
│     LOCAL SERVER                │
Открыть полный README на GitHub

Установка

This server does not publish a one-line install command.

Open the repository installation guide Новичок в MCP? Начните с руководства на mcpskill.org →