Data & AI platform by Data Analytics
MCP and your Power BI semantic model: one reliable source for AI
A carefully designed MCP integration can let AI query your existing Power BI semantic model. Dashboards and AI can then use the same DAX measures, KPI definitions and relationships instead of a second calculation model alongside your reports. This requires an appropriate query layer and controlled access; MCP alone does not enforce Power BI security.
The examples on this page are hypothetical situations, not customer cases.
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01
From a question to a calculation in your model
Your semantic model captures the meaning of your figures: how revenue is calculated, which costs count towards margin and how customer, product and period relate. An AI application such as Claude, ChatGPT or an agent can invoke a bounded tool through a supported MCP client. The MCP server translates the permitted request into a model query. The model performs the calculation; AI explains the result. MCP and authentication support differ by application and configuration.
An appropriate query layer may use a supported Power BI query API or XMLA access. Suitability depends on the model, capacity, tenant settings, licensing and selected identity. Not every database connector queries the semantic model: direct SQL against underlying tables does not automatically use your DAX measures. Establish where the calculation actually happens first.
02
Reuse KPI definitions, including filter context
Example: a CFO asks for the gross margin of Belgian operations over the previous quarter. The integration selects an approved margin measure, the correct entity and an explicit period. The model calculates the result within those filters and its existing relationships. The answer states the measure, period and filters so you can compare it with your report. A revenue measure is not a margin measure; a missing currency choice can also produce a misleading answer.
Filter context from an open Power BI report does not automatically travel to an external AI chat. Have the tool process filters explicitly and check time definitions, totals, blanks and rounding. If no appropriate measure exists, the application should say so rather than inventing a new KPI formula. New business logic belongs in the managed model through the BI team, not silently in a prompt.
03
For BI teams, finance and management
For BI teams, this can make existing definitions more widely available without building a separate report page for each question. Finance can explore variances using agreed calculations. Management can investigate a dashboard figure further, for example by product group and month. These are possible applications, not proven results or a promise that your current environment already supports the integration.
Example: an agent drafts a monthly review using actual revenue and budget variance from existing measures. An employee checks the source, reference date and interpretation before sharing the report. A narrative about causes is not automatically substantiated by a number. Additional context and human review remain necessary.
04
Verify permissions, RLS and OLS
RLS limits which rows someone may see; OLS can restrict access to particular tables or columns. Actual enforcement depends on identity, role and the chosen query mechanism. Grant only necessary model permissions and check the role used by the integration. A broad technical account may see more than the end user. Do not assume their security transfers automatically; test allowed and forbidden questions, different users and direct tool calls.
Start with read-only tools, bounded results and query limits. Where appropriate, log who used which tool, on which model and with which filters, without unnecessarily storing sensitive results. Agree retention and log access. External AI may process retrieved results outside your organisation; explicitly address model selection, data minimisation and related agreements. Write actions and model changes are outside this read configuration and require separate permission and controls.
05
From existing reporting to a controlled trial
Start with one model and a few commonly used KPIs. The BI team confirms measures, definitions and filters; the owner determines who may receive which results. Compare tool results with Power BI under the same identity and filter context. Test missing context, source failures, freshness and unauthorised access. Define when an answer must stop and ask for clarification.
ENABLE is Data Analytics’ Data & AI platform for connecting and structuring business data and controlled access for dashboards, analysis and AI solutions. Discuss how your existing Power BI model could fit; this page does not establish the availability of a ready-made ENABLE connector. Data Analytics can explore the query layer, operating agreements and implementation checks with you. Book an ENABLE demo starting from your concrete model question, without introducing a second KPI truth.
Frequently asked questions
Are all DAX measures automatically available?
No. The query layer must actually query the model and support permitted measures and parameters. Availability and result behaviour must be tested for each model.
Does MCP automatically enforce Power BI security?
No. MCP is the connection protocol. Model permissions, identity, RLS and OLS must be correctly enforced and verified in the chosen query path.
Do we need to rebuild our model?
The starting point is reuse of your existing model. Missing definitions or model issues may require improvements; manage those in the model rather than separately in AI.
Can ChatGPT or Claude use this immediately?
That depends on the supported MCP client, authentication and your model environment. The integration must be configured and tested; this page is not a working connection.
How do we know the AI answer is correct?
Compare the same measure, identity, filters and period with Power BI. Show the source and freshness alongside the answer and review interpretations before acting.
Technical documentation
Discuss your question with Data Analytics
Which sources, users and checks does your application need? Discuss your question in an ENABLE demo.
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