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Power BI Modeling MCP Server

Connects AI agents to Power BI semantic models for authoring, bulk changes, DAX validation, and TMDL-based workflows.

Install Power BI Modeling MCP Server

Pick your client, then add it in one click or paste the config.

STDIONode.js
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "power-bi-modeling-mcp-server": {
      "command": "npx",
      "args": [
        "-y",
        "@microsoft/powerbi-modeling-mcp@latest"
      ]
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

We couldn’t confirm it starts correctly

We ran the install command but it didn't respond within our test window — this can mean a slow first-time install rather than a real problem.

npx -y @microsoft/powerbi-modeling-mcp@latest

No response to initialize.

This is an experimental automated check and can have false negatives — missing environment variables, a slow cold install, etc. It doesn’t necessarily mean something’s wrong. Last checked Today.

Overview

Power BI Modeling MCP Server connects AI agents to semantic models in Power BI Desktop, Fabric workspaces, or Power BI Project files. It runs locally through MCP and lets agents create and modify tables, columns, measures, relationships, security rules, and other modeling objects using natural language. Use it for bulk refactoring, modeling best-practice work, agentic TMDL workflows, and DAX query validation. The server supports Visual Studio Code with GitHub Copilot and manual registration in other MCP clients.

Use cases

  • Create and modify Power BI semantic model objects with natural-language prompts
  • Bulk-rename and refactor model objects
  • Validate DAX queries and troubleshoot measures
  • Apply modeling conventions and best practices
  • Automate TMDL and PBIP model development workflows

Key features

  • Power BI Desktop and Fabric semantic model connections
  • PBIP and TMDL workflow support
  • Bulk modeling operations with transactions and error handling
  • DAX query execution and validation
  • Natural-language model authoring
  • Modeling best-practice evaluation

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked Today

Recent health check succeeded.

52/55 checks healthy over the last 92d

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 5d ago via OSV.dev · @microsoft/powerbi-modeling-mcp@latest (npm)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars1.3kStargazers on the source repository.
npm downloads41kPackage downloads in the last 30 days.
Last commit4d agoMost recent push to the default branch.
Install checkInconclusiveDidn't respond in our test window — often a slow first install.
Directory activity14 viewsConfig copies, upvotes, and views on AllMCPs.

How Power BI Modeling MCP Server works

What Power BI Modeling MCP Server does

Power BI Modeling MCP Server exposes Power BI semantic modeling operations to MCP-compatible AI agents. After connecting to a model, an agent can create, update, and manage tables, columns, measures, relationships, and security rules. It also supports executing and validating DAX queries, which can help test measures, investigate calculations, and inspect model behavior.

The server is intended for authoring rather than general Power BI metadata management. Its supported scope covers semantic model operations, including models associated with Power BI Desktop, Fabric workspaces, and Power BI Project files using TMDL. It does not handle report pages or diagram layouts.

How it works

The local server communicates with an MCP client over stdio. An agent first establishes a connection to one of three model sources:

  • A semantic model open in Power BI Desktop
  • A semantic model in a Fabric workspace
  • A semantic model definition inside a Power BI Project folder

Once connected, prompts can describe modeling changes in natural language. Operations can also be applied in batches across many objects, supporting tasks such as renaming, refactoring, translations, and model security updates. Transaction support and error handling are available for bulk modeling operations.

TMDL and PBIP support enables agent workflows that plan and apply changes against semantic model files. The server also includes an accept_eula tool for interactive license acceptance.

Setup and configuration

The recommended setup uses Visual Studio Code with the GitHub Copilot Chat extension and the Power BI Authoring MCP extension. After installation, open Copilot Chat and ensure powerbi-modeling-mcp is enabled in the available tools. GitHub Copilot MCP server access may need to be enabled in Copilot settings; enterprise accounts may require an administrator to enable it.

For other clients, Node.js can launch the package through npx:

config.json
{
  "powerbi-authoring-local": {
    "type": "stdio",
    "command": "npx",
    "args": ["-y", "@microsoft/powerbi-modeling-mcp@latest", "--start"]
  }
}

Review and accept the Power BI Authoring MCP Server EULA before using the npm package. Interactive sessions can authorize the accept_eula tool. Unattended setups can add --accepteula to the arguments or set PBI_MODELING_MCP_ACCEPT_EULA to true after accepting the terms.

A VSIX package can also be downloaded, extracted, and launched with its bundled powerbi-modeling-mcp.exe, then registered as a stdio server in the chosen client.

Tools and capabilities

  • Create, update, and manage semantic model tables, columns, measures, and relationships
  • Apply bulk renames, refactoring, translations, and security-rule changes
  • Execute and validate DAX queries against a connected model
  • Evaluate and apply modeling best practices
  • Work with TMDL and Power BI Project model files
  • Connect to Power BI Desktop and Fabric semantic models
  • Accept the EULA interactively through the accept_eula tool

Limitations and notes

Back up a model before allowing an AI agent to make changes. Generated operations may be inaccurate or unexpected, and model data or metadata could appear in logs or responses. Take care when sharing chat sessions or connecting models that contain sensitive information.

The server is limited to modeling operations. Report pages and diagram layouts are outside its supported scope. Agent response quality also depends on the selected AI model; the project recommends a deep-reasoning model for these workflows.

Reviews

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Frequently Asked Questions about Power BI Modeling MCP Server

Power BI Modeling MCP Server is an MCP server that connects AI agents to Power BI Desktop models, Fabric semantic models, and Power BI Project files. Its main tools support creating and modifying model objects, bulk authoring operations, DAX execution and validation, best-practice work, and interactive EULA acceptance.

Install it through the Power BI Authoring MCP Visual Studio Code extension or register the npm package with an MCP client using `npx @microsoft/powerbi-modeling-mcp@latest --start`. Node.js is required for the npm method, and the EULA must be accepted before tool calls.

Connect by identifying a model in Power BI Desktop, a semantic model and workspace in Fabric, or the definition/TMDL folder inside a PBIP project. The agent can then use natural-language prompts to perform modeling operations.

Yes. Visual Studio Code is the recommended client setup when used with GitHub Copilot Chat and the Power BI Authoring MCP extension. The `powerbi-modeling-mcp` server must be visible and selected in Copilot's available tools.

No. Its scope is semantic model authoring, so it cannot modify report pages, diagram layouts, or other unsupported Power BI metadata. It can work with tables, columns, measures, relationships, security rules, and DAX queries.

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