Hi Folks,

Model Context Protocol(MCP) has quickly become one of the hottest topics in today’s AI landscape. The excitement around it is huge—not just within the Microsoft ecosystem, but across the entire industry, because it’s designed to be open and accessible to everyone.

Microsoft Power Platform is also moving fast, releasing its own MCPs. I’ve already been asked several times about the difference between them, so this post breaks down how the Dataverse MCP and the Power Apps MCP differ—and when you should use each one.

We know that Dataverse MCP is generally available last year. Now Microsoft announced the public preview of Power Apps MCP this month. So what’s the difference between the two, this post will help to discern the differences between two.

Although both use the Model Context Protocol (MCP), they serve different purposes and operate at different layers of the Power Platform.

Feature	Dataverse MCP	Power Apps MCP
Primary Role	Expose Dataverse as an MCP server so AI agents can query tables, records, and metadata	Allow Power Apps to use MCP to call external AI models or tools
Focus	Data access & operations	AI integration inside apps
Who Uses It	Developers building AI agents or copilots that need Dataverse data	App makers building Power Apps that need AI-driven logic

2. Direction of Integration

Direction	Dataverse MCP	Power Apps MCP
MCP Server	Yes — Dataverse acts as an MCP server	No
MCP Client	No	Yes — Power Apps acts as an MCP client
Meaning	AI tools connect into Dataverse	Power Apps connects out to AI tools

Dataverse MCP: AI → Dataverse Power Apps MCP: Power Apps → AI

3. What You Can Do

Dataverse MCP

• Query Dataverse tables
• Retrieve records
• Update or create data
• Use Dataverse as a tool inside Copilot Studio, VS Code GitHub Copilot, Claude Desktop, etc.

Power Apps MCP

• Call external AI models from inside a Power App
• Build AI-driven app logic
• Trigger workflows using AI reasoning

4. Typical Use Cases

Dataverse MCP

• Build a Copilot that answers questions using Dataverse data
• Let GitHub Copilot query Dataverse while coding
• Create AI agents that read/write CRM or ERP data

Power Apps MCP

• Add AI reasoning to a canvas or model-driven app
• Use external AI models to classify, summarize, or generate content
• Build intelligent forms or workflows

5. Relation to Connectors

Dataverse MCP is increasingly seen as a future alternative to connectors for AI-driven scenarios.

Power Apps MCP does not replace connectors — it extends apps with AI capabilities.

Summary

Category	Dataverse MCP	Power Apps MCP
Acts as	MCP Server	MCP Client
Used for	AI agents accessing Dataverse	Power Apps calling AI tools
Primary Benefit	Intelligent, standardized Dataverse access	AI-enhanced app logic
Typical Tools	Copilot Studio, GitHub Copilot, Claude	Canvas apps, model-driven apps

Decision Guide: When to Use Dataverse MCP vs Power Apps MCP

1. If you want AI to access Dataverse → Use Dataverse MCP

Choose Dataverse MCP when:

• You’re building a Copilot, AI agent, or LLM-powered tool that needs:
  • Dataverse tables
  • Records
  • Metadata
  • CRUD operations
• You want AI to reason over business data
• You want a standardized, connector-free way for AI to talk to Dataverse
• You’re integrating Dataverse with:
  • GitHub Copilot
  • Copilot Studio
  • Claude Desktop
  • Custom LLM agents

Typical scenarios

• My AI assistant should answer questions using CRM data.
• I want GitHub Copilot to autocomplete code based on Dataverse schema.
• I’m building an AI agent that updates Dataverse records.

If the AI is the one doing the work → Dataverse MCP.

2. If you want your Power App to call AI → Use Power Apps MCP

Choose Power Apps MCP when:

• You’re building a canvas or model-driven app that needs:
  • AI reasoning
  • AI-generated content
  • AI classification or summarization
• You want your app to call:
  • OpenAI models
  • Azure AI models
  • Custom MCP tools
• You want AI logic inside the app, not outside it

Typical scenarios

• My form should summarize customer notes using AI.
• My app should classify images or text using an external model.
• I want to call an LLM from a button in a canvas app.

3. If you need both directions → Use both

Some solutions need AI ↔ Dataverse ↔ Power Apps.

Example

• A Power App collects data
• AI agent (via Dataverse MCP) analyzes historical records
• Power App (via Power Apps MCP) calls AI to generate insights for the user

This is becoming a common pattern in enterprise AI.

4. Quick Decision Table

Goal	Use Dataverse MCP	Use Power Apps MCP
AI needs to read/write Dataverse	✅	❌
Power App needs to call AI	❌	✅
Replace connectors for AI-driven data access	✅	❌
Add AI reasoning inside app UI	❌	✅
Build AI copilots or agents	✅	❌
Build AI-enhanced business apps	❌	✅

Hope you have found this post useful….

Cheers,

PMDY