Explanation2 min read

OData and MCP: what's the difference?

OData brings your data to Power BI and Excel, MCP brings it to ChatGPT and Claude. The difference in plain language, and when to choose which connection.

Auke Westra

By Auke Westra

Founder of DigiData

Practical guide. This article covers the steps, checks, and common issues.

Short answer

OData and MCP both make your business data available, but for different purposes. OData is the connection for reporting tools such as Power BI and Excel. MCP is the connection for AI assistants such as ChatGPT and Claude. At DigiData both use the same, automatically updated data, so you can simply use them side by side.

The short difference

  • OData is for reporting. Power BI and Excel use it to load your tables, so you can build dashboards that refresh automatically. Read more in what is OData?
  • MCP is for AI assistants. ChatGPT and Claude use it to fetch answers when you ask a question in plain language. Read more in what is an MCP server?

The same data, two ways to use it

DigiData retrieves your data from systems such as Exact Online, Twinfield and Exact Bouw and keeps it up to date automatically. Your Power BI report and your ChatGPT answer are based on the same numbers. No more debate about which figure is right.

When to choose what

You want...Choose
A fixed monthly report or dashboard in Power BIOData
To analyse your data in ExcelOData
To ask a quick question in ChatGPT or ClaudeMCP
Recurring analysis with fixed definitions, in Teams, Slack or by emailDigiData AI agent

You don't have to choose

With DigiData you use OData and MCP side by side. Many customers use Power BI for the monthly figures, and ChatGPT or the DigiData AI agent for the questions in between.

Summary

OData brings your data to your reports, MCP to your AI assistant. See the page OData or MCP or discover why teams choose DigiData AI.

Sources

Auke Westra

About Auke Westra

Founder of DigiData

Auke Westra is Founder of DigiData. He was responsible for clients' data and reporting and in 2025 began building an in-house data platform with his team. He writes about AI on business data, data definitions, Power BI and integrations.

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