PBIXRay MCP Server

Overview

The PBIXRay MCP Server bridges the gap between large language models and Power BI data assets by exposing a rich set of tools that can load, interrogate, and manipulate Power BI (.pbix) files through the Model Context Protocol. Developers who work with AI assistants can now query and analyze Power BI models directly from the assistant’s context, enabling a new class of data‑centric conversational workflows. Instead of manually opening Power BI Desktop or writing custom scripts, an LLM can invoke the server’s tools to retrieve tables, relationships, DAX measures, and even the underlying Power Query (M) code—all within a single conversation.

What Problem Does It Solve?

Power BI files are typically closed, binary artifacts that require specialized tooling to inspect. Traditional approaches involve opening the file in Power BI Desktop, exporting metadata, or writing custom scripts to parse the .pbix format. This server eliminates those friction points by providing a standardized, protocol‑based interface that any MCP‑compliant client can consume. It democratizes access to Power BI internals, allowing AI assistants to surface insights about data models, performance bottlenecks, or missing relationships without the user having to become a Power BI expert.

Key Features and Capabilities

• Model Exploration: List tables, retrieve metadata, calculate model size, and generate comprehensive summaries.
• Query Access: View Power Query (M) scripts, inspect M parameters, and explore DAX components such as calculated tables, measures, and columns.
• Structure Analysis: Retrieve schema details, analyze table relationships, and paginate through table contents.
• Configurable Toolset: Expose only the tools that are relevant or safe for a given environment, protecting sensitive data and simplifying the assistant’s interface.

Each tool is designed to return concise, structured responses that can be seamlessly integrated into an AI assistant’s reasoning chain.

Use Cases and Real‑World Scenarios

• Data Governance: An assistant can audit a Power BI model for compliance by examining relationships and data lineage.
• Performance Tuning: By retrieving model statistics and size, the assistant can suggest optimizations or identify bottlenecks.
• Rapid Prototyping: Developers can ask the assistant to list all DAX measures or fetch a table’s contents, speeding up exploratory data analysis.
• Automated Documentation: Generate summaries of a model’s structure and logic for knowledge bases or onboarding materials.

These scenarios illustrate how the server turns a static Power BI file into an interactive knowledge source.

Integration with AI Workflows

The server plugs directly into any MCP‑enabled client, such as Claude Desktop or other LLM platforms. By configuring the server’s command and arguments (e.g., via WSL on Windows), developers can expose Power BI capabilities as first‑class tools in the assistant’s toolkit. The assistant can then chain tool calls—loading a file, retrieving its schema, and querying specific DAX expressions—to answer complex user questions or automate repetitive tasks.

Unique Advantages

• Protocol‑First Design: Built on MCP, the server guarantees compatibility with a broad ecosystem of AI assistants without vendor lock‑in.
• Security by Design: The ability to selectively enable tools allows fine‑grained control over what data is exposed.
• Cross‑Platform Support: The recommended WSL setup ensures that developers on Windows can still leverage the full power of Linux‑based tooling.

In sum, the PBIXRay MCP Server transforms Power BI models from opaque artifacts into accessible, AI‑friendly resources, empowering developers to build smarter, data‑aware assistants that can navigate and interrogate business intelligence assets with ease.