[!重要] 在 Fabric 工作区中创作语义模型时，使用远程（托管）的 Power BI 创作 MCP 服务器。它无需本地安装，Microsoft管理更新。参见 Power BI 创作 MCP 服务器以比较远程和本地选项。

Power BI 创作 MCP 服务器实现了 MCP 规范，以实现 AI 代理与 Power BI 语义模型之间的无缝连接。

Power BI 创作 MCP 服务器 通过本地 MCP 服务器，为您的 AI 代理提供 Power BI 语义建模能力。这使得开发者和 AI 应用能够以全新方式与 Power BI 模型交互，从使用自然语言执行建模变更，到自主的 AI 代理开发工作流。

💡 你能做什么？

• ** 🔄 用自然语言构建和修改语义模型** - 告诉你的 AI 助手你需要什么，它就会利用这个 MCP 服务器创建、更新和管理表、列、度量、关系等…涵盖 Power BI Desktop 和 Fabric 语义模型。

✨ Power BI Authoring MCP Server

[!IMPORTANT] When authoring semantic models in a Fabric workspace, use the remote (hosted) Power BI Authoring MCP server. It requires no local installation, and Microsoft manages updates. See Power BI Authoring MCP server to compare the remote and local options.

The Power BI Authoring MCP Server implements the MCP specification to create a seamless connection between AI agents and Power BI semantic models.

The Power BI Authoring MCP Server brings Power BI semantic modeling capabilities to your AI agents through a local MCP server. This allows developers and AI applications to interact with Power BI models in entirely new ways, from using natural language to execute modeling changes to autonomous AI agentic development workflows.

💡 What can you do?

• 🔄 Build and Modify Semantic Models with Natural Language - Tell your AI assistant what you need, and it uses this MCP server to create, update, and manage tables, columns, measures, relationships, and more… across Power BI Desktop and Fabric semantic models.

• ⚡ Bulk Operations at Scale - AI applications can execute batch modeling operations on hundreds of objects simultaneously — bulk renaming, bulk refactoring, model translations, or model security rules - with transaction support and error handling, turning hours of repetitive work into seconds.

• ✅ Apply modeling best practices - Easily evaluate and implement modeling best practices against your model.

• 🤖 Agentic Development Workflows - Supports working with TMDL and Power BI Project files, enabling AI agents to autonomously plan, create, and execute complex modeling tasks across your semantic model codebase.

• 🔍 Query and Validate DAX - AI assistants can execute and validate DAX queries against your model, helping you test measures, troubleshoot calculations, and explore your data

📹 Watch the video for an end-to-end demo.

[!WARNING]

• Use caution when connecting an AI Agent to a semantic model. The underlying LLM may produce unexpected or inaccurate results, which could lead to unintended changes. Always create a backup of your model before performing any operations.
• LLMs might unintentionally expose sensitive information from the semantic model, including data or metadata, in logs or responses. Exercise caution when sharing chat sessions. See Data Privacy and LLM Providers.
• The Power BI Authoring MCP server can only execute modeling operations. It cannot modify other types of Power BI metadata, such as report pages or semantic model elements like diagram layouts.