{"id":1322,"date":"2026-02-16T12:40:52","date_gmt":"2026-02-16T07:10:52","guid":{"rendered":"https:\/\/blogs.infosys.com\/infosys-consulting\/?p=1322"},"modified":"2026-02-16T12:41:04","modified_gmt":"2026-02-16T07:11:04","slug":"from-semantic-models-to-ai-agents-an-introductory-guide-to-the-power-bi-mcp-server","status":"publish","type":"post","link":"https:\/\/blogs.infosys.com\/infosys-consulting\/ai\/from-semantic-models-to-ai-agents-an-introductory-guide-to-the-power-bi-mcp-server.html","title":{"rendered":"From Semantic Models to AI Agents: An Introductory Guide to the Power BI MCP Server"},"content":{"rendered":"<p>The Power BI MCP server is a standards-based bridge that lets AI assistants (e.g., GitHub Copilot, Claude, custom agents) understand, query, and modify Power BI semantic models. It allows natural-language data questions, automatic DAX generation, and workflows for model maintenance.<\/p>\n<p>In simple terms, think of the Power BI MCP server as a smart helper that connects Power BI with AI tools like Copilot or other assistants. It makes it easier for these AI tools to understand your data model, ask questions in plain language, and even help you create calculations automatically. Instead of handling everything on your own, this feature helps you get things done quicker and takes a lot of the repetitive work off your plate.<\/p>\n<h5>What does MCP mean in relation to Power BI?<\/h5>\n<p>MCP (Model Context Protocol) is basically an open standard that makes it easier for AI tools to connect with platforms like Power BI or other data servers. Instead of building custom integrations every time, MCP gives them a common way to talk to each other.<\/p>\n<p>In Power BI, you\u2019ll usually come across two types of MCP servers:<\/p>\n<p>\u2022 Remote MCP Server: This lets AI tools read your data model and respond to questions like, \u201cCan you show me the top 10 products by sales?\u201d<\/p>\n<p>\u2022 Modeling MCP Server: This one helps on the modeling side. It can assist in building or refining your data model \u2014 for example, correcting relationships between tables or adding new measures and calculations.<\/p>\n<h5>How it functions (briefly)<\/h5>\n<p>1. AI Assistant connects to Power BI: Your Power BI model is connected to tools such as Copilot or other AI agents.<\/p>\n<p>2. Power BI shares its structure: The server provides access to tools like calculation creation and displays to the AI which tables, columns, and measures are available.<\/p>\n<p>3. AI assists you in reaching your objective: The AI uses these tools to carry out your requests, such as &#8220;Check if my model follows best practices&#8221; or &#8220;Add a Month-over-Month growth calculation.&#8221;<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-1323 size-large\" src=\"https:\/\/blogs.infosys.com\/infosys-consulting\/wp-content\/uploads\/2026\/02\/Image-1_-How-MCP-Server-works-1024x682.png\" alt=\"\" width=\"1024\" height=\"682\" \/><\/p>\n<p>Image 1: How MCP Server works<\/p>\n<h5>What the MCP server can do<\/h5>\n<p>\u2022 Provide semantic model metadata so AI can understand it, or, to put it simply, see how your data model looks.<\/p>\n<p>\u2022 Create and run DAX queries according to the intent of natural language.<\/p>\n<p>\u2022 Execute modeling operations (modeling server): validate DAX, create or modify measures or columns, modify relationships, and assess best-practice checks.<\/p>\n<p>\u2022 Quicken monotonous processes like column renaming and error checking.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-1324 size-large\" src=\"https:\/\/blogs.infosys.com\/infosys-consulting\/wp-content\/uploads\/2026\/02\/Image-2_Create-connection-and-list-Power-BI-models-1024x663.png\" alt=\"\" width=\"1024\" height=\"663\" \/><\/p>\n<p>Image 2: Create connection and list Power BI models<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-1325 size-large\" src=\"https:\/\/blogs.infosys.com\/infosys-consulting\/wp-content\/uploads\/2026\/02\/Image-3_-Create-relationships-with-tables-new-and-old-1024x586.png\" alt=\"\" width=\"1024\" height=\"586\" \/><\/p>\n<p>Image 3: Create relationships with tables (new and old)<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-1326 size-large\" src=\"https:\/\/blogs.infosys.com\/infosys-consulting\/wp-content\/uploads\/2026\/02\/Image-4_-Create-Measures-984x1024.png\" alt=\"\" width=\"984\" height=\"1024\" \/><\/p>\n<p>Image 4: Create Measures<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-1327 size-large\" src=\"https:\/\/blogs.infosys.com\/infosys-consulting\/wp-content\/uploads\/2026\/02\/Image-5_What-MCP-server-can-do-1024x943.png\" alt=\"\" width=\"1024\" height=\"943\" \/><\/p>\n<p>Image 5: What MCP server can do<\/p>\n<h5>What is not done by the MCP server<\/h5>\n<p>\u2022 ETL\/Data prep: Power Query, pipelines, and external data engineering procedures are not replaced by it.<\/p>\n<p>\u2022 Report canvas authoring: This tool focuses on models and queries rather than creating or styling visuals.<\/p>\n<p>\u2022 Workspace governance and RLS setup: It is not responsible for managing gateways, tenant settings, RLS rules, or refresh schedules.<\/p>\n<p>\u2022 Guaranteed accuracy: Human review is crucial, particularly for model-changing operations, as LLM agents are prone to misinterpreting intent.<\/p>\n<p>&nbsp;<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-1329 size-large\" src=\"https:\/\/blogs.infosys.com\/infosys-consulting\/wp-content\/uploads\/2026\/02\/Image-6_Doesn_t-create-visualizations-1-1024x931.png\" alt=\"\" width=\"1024\" height=\"931\" \/><\/p>\n<p>Image 6: Doesn\u2019t create visualizations<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-1330 size-large\" src=\"https:\/\/blogs.infosys.com\/infosys-consulting\/wp-content\/uploads\/2026\/02\/Image-7_What-MCP-Server-can_t-do-1024x919.png\" alt=\"\" width=\"1024\" height=\"919\" \/><\/p>\n<p>Image 7: What MCP Server can\u2019t do<\/p>\n<h5>Big questions!<\/h5>\n<h4>Q1. Does MCP eliminate the need for a data scientist, data engineer, or data analyst?<\/h4>\n<p>In a nutshell, MCP enhances rather than replaces.<br \/>\n\u2022 Data analysts continue to create concise narratives, validate findings, and formulate business questions.\u2022 Data engineers handle pipelines, create modeling foundations, oversee governance, tune performance, and ensure data quality.<br \/>\n\u2022 MCP can assist data scientists in querying and validating metrics rapidly, but it does not replace statistical rigor. Data scientists still design experiments, feature engineering, and causal inference.<br \/>\nConsider MCP as a powerful tool for analytics teams, increasing reach and speeding up repetitive tasks while maintaining the importance of human expertise for accuracy, ethics, and stakeholder trust.<\/p>\n<h4>Q2. What does MCP bring to an organisation like Infosys?<\/h4>\n<p>\u00b7\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Faster model audits &amp; remediation.<\/p>\n<p>\u00b7\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 AI-ready consulting assets.<\/p>\n<p>\u00b7\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Governed extensibility.<\/p>\n<p>\u00b7\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Upskilling &amp; reuse for industry-specific playbooks.<\/p>\n<h4>Q3. What does MCP bring for Executives?<\/h4>\n<p>\u00b7\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Natural-language access to modeled truth.<\/p>\n<p>\u00b7\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Consistency &amp; trust.<\/p>\n<p>\u00b7\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Faster what-ifs with oversight.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-1331 size-large\" src=\"https:\/\/blogs.infosys.com\/infosys-consulting\/wp-content\/uploads\/2026\/02\/Image-8_-Key-Insights-1024x763.png\" alt=\"\" width=\"1024\" height=\"763\" \/><\/p>\n<h4>\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <strong>\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0Image 8: Key Insights<\/strong><\/h4>\n<h4>Q4. What does MCP bring for Data Analysts &amp; BI Developers?<\/h4>\n<p>\u00b7\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Time savings on DAX &amp; diagnostics.<\/p>\n<p>\u00b7\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Improved discoverability.<\/p>\n<p>\u00b7\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Agent workflows that are repeatable for jobs like naming conventions and translations.<\/p>\n<h5>Closing Thoughts<\/h5>\n<p>The Power BI MCP server provides a balanced way to bring AI-driven efficiency into analytics while keeping governance and human judgment intact. When it\u2019s backed by clear modeling guidelines and proper approval processes, it can really improve how teams at Infosys and similar organizations work together. You start seeing faster insights, smoother AI workflows, and cleaner, more structured models. And at the same time, you\u2019re not giving up oversight or control which is very important.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The Power BI MCP server is a standards-based bridge that lets AI assistants (e.g., [&hellip;]<\/p>\n","protected":false},"author":923,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[3],"tags":[478,479,362,477,476],"coauthors":[360,377,475,376],"class_list":["post-1322","post","type-post","status-publish","format-standard","hentry","category-ai","tag-ai-integration","tag-analytics-workflow","tag-business-intelligence","tag-mcp-server","tag-power-bi"],"acf":[],"_links":{"self":[{"href":"https:\/\/blogs.infosys.com\/infosys-consulting\/wp-json\/wp\/v2\/posts\/1322","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blogs.infosys.com\/infosys-consulting\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs.infosys.com\/infosys-consulting\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.infosys.com\/infosys-consulting\/wp-json\/wp\/v2\/users\/923"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.infosys.com\/infosys-consulting\/wp-json\/wp\/v2\/comments?post=1322"}],"version-history":[{"count":5,"href":"https:\/\/blogs.infosys.com\/infosys-consulting\/wp-json\/wp\/v2\/posts\/1322\/revisions"}],"predecessor-version":[{"id":1337,"href":"https:\/\/blogs.infosys.com\/infosys-consulting\/wp-json\/wp\/v2\/posts\/1322\/revisions\/1337"}],"wp:attachment":[{"href":"https:\/\/blogs.infosys.com\/infosys-consulting\/wp-json\/wp\/v2\/media?parent=1322"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.infosys.com\/infosys-consulting\/wp-json\/wp\/v2\/categories?post=1322"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.infosys.com\/infosys-consulting\/wp-json\/wp\/v2\/tags?post=1322"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/blogs.infosys.com\/infosys-consulting\/wp-json\/wp\/v2\/coauthors?post=1322"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}