Julie Koesmarno, Author at Microsoft Power Platform Blog http://approjects.co.za/?big=en-us/power-platform/blog Innovate with Business Apps Mon, 06 Jul 2026 15:35:25 +0000 en-US hourly 1 https://wordpress.org/?v=6.9.5 Dataverse Is Your Agent Data Platform: Here’s What’s New in July 2026 http://approjects.co.za/?big=en-us/power-platform/blog/2026/07/06/dataverse-july2026/ Mon, 06 Jul 2026 15:35:22 +0000 Latest Dataverse improvements: expanding the plugin across more coding agent marketplaces, connecting agents to more tools through MCP, certifying partner MCPs for trusted adoption, and bringing internal MCPs under enterprise governance.

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AI is becoming a true coding partner, helping makers and developers build apps and agents faster on the same trusted data platform. This post outlines the latest Dataverse improvements behind that vision: expanding the plugin across more coding agent marketplaces, connecting agents to more tools through MCP, certifying partner MCPs for trusted adoption, and bringing internal MCPs under enterprise governance. 

Dataverse Plugin for Coding Agents: Marketplace Expansion 

The Dataverse plugin for coding agents brings the full power of Microsoft Dataverse directly into the developer’s coding environment. Instead of switching between browser tabs, documentation, and admin portals, developers can describe what they want in natural language and the plugin handles the rest. It intelligently routes each request through the right tool, whether that’s the Dataverse MCP server (see latest update), the Python SDK, PAC CLI, or the Dataverse CLI, so developers stay in flow and get production-grade results without needing to master every tool individually. Built on an open-source skill architecture, the plugin enforces least-privilege security, follows documented auth patterns, and respects existing Dataverse RBAC, making it safe for real enterprise environments from day one. See the Dataverse plugin for coding agents in action here.  

We are excited to announce the expansion of the Dataverse plugin into additional coding agent marketplaces, meeting developers where they already work. The plugin is now available for Claude, Cursor and GitHub Copilot. This means that whether a developer’s primary coding agent is GitHub Copilot, Claude or Cursor, they get the same Dataverse expertise: intelligent skill routing, enterprise-grade guardrails, and a consistent natural-language experience across every surface. This cross-platform availability reflects our commitment to making Dataverse accessible wherever agents are being built, and we will have support for more coding agents coming soon. 

The plugin is now available for Claude, Cursor and GitHub Copilot. This means that whether a developer's primary coding agent is GitHub Copilot, Claude or Cursor, they get the same Dataverse expertise: intelligent skill routing, enterprise-grade guardrails, and a consistent natural-language experience across every surface.

A Growing MCP Ecosystem Connected to the Systems You Already Run 

Model Context Protocol (MCP) servers give agents a common way to discover and use tools across systems: one standard connection model that helps any agent work with the right tool, in the right system, at the right time. Microsoft is building a rich MCP catalog designed around the systems enterprises already depend on — from productivity and developer experiences to business applications and partner platforms.

Catalog includes 60+ ready MCP servers.

The catalog includes 60+ ready MCP servers, and the customer promise is simple: start faster with ready-to-use MCPs, connect agents to familiar business systems, and use the same standard across Microsoft 365 Copilot, Copilot Studio, Azure AI Foundry, GitHub Copilot, and other MCP-compatible experiences. For example, the Dataverse MCP server is natively supported today in Copilot Studio, Azure AI Foundry, and other MCP-compatible clients. 

Certified MCPs: ISV Built MCPs that Customers Can Discover, Trust, and Govern 

For ISVs and partners, MCP certification creates a trusted route into the Microsoft ecosystem. Once certified, partner-built MCPs become easier for customers to discover, evaluate, and adopt, while signaling that the experience aligns with enterprise expectations around security, governance, and observability.

For ISVs and partners, MCP certification creates a trusted route into the Microsoft ecosystem. Once certified, partner-built MCPs become easier for customers to discover, evaluate, and adopt, while signaling that the experience aligns with enterprise expectations around security, governance, and observability. For customers, certified MCPs help reduce uncertainty: they can look to a growing ecosystem of partner capabilities designed to extend agents into specialized business scenarios, with clearer trust signals and a path toward governed adoption at scale. 

  1. Package your MCP for certification. Prepare a certification package that includes your MCP manifest (with the MCP endpoint URL), Tools JSON file, and Key Vault-backed authentication details for securely managing secrets. 
  1. Choose your certification offer type. Select the appropriate certification offer type ‘Apps and Agents for M365 and Copilot’ for your MCP and submit the package through Partner Center to make your MCP available across Microsoft agent experiences. 
  1. Publish across Microsoft experiences. Once certified, your MCP becomes available for customer adoption across supported Microsoft surfaces, including Copilot Studio and Azure AI Foundry, making it easier for customers to discover, trust, and use your MCP in enterprise AI solutions. 

Bring Your Own MCP: Your Internal Tools, Governed Like the Catalog  

Beyond the rich MCP catalog, Bring Your Own MCP enables organizations to connect their unique business systems and workflows to the agent ecosystem. If your organization has a custom tool, proprietary API, internal workflow, or industry-specific system, you can bring that MCP server into your own organization and make it available for agents under enterprise controls. The goal is to give customers flexibility without giving up governance: register the MCP once, make it discoverable for the right agent scenarios, and manage it with the same expectations for admin approval, visibility, and control. 

Dataverse agentic evolution: from experimentation to execution  

As AI becomes a coding partner, Dataverse gives makers and developers the trusted data platform to build apps and agents faster, with the business context, connected tools, and enterprise governance needed to move from experimentation to execution. Learn more:  

Dataverse MCP: Dataverse MCP Server: Understanding the New Tool Shape – Microsoft Power Platform Blog

Dataverse MCP preview docs: https://learn.microsoft.com/en-us/power-apps/maker/data-platform/data-platform-mcp-preview-tools 

Dataverse Plugin on Claude Marketplace announcement blog: https://devblogs.microsoft.com/powerplatform/dataverse-plugin-claude-marketplace/ 

For ISVs and partners, check out the MCP certification to creates a trusted route into the Microsoft ecosystem

Read the Bring Your Own MCP docs

Dataverse docs: https://learn.microsoft.com/en-us/power-apps/maker/data-platform/data-platform-intro 

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Dataverse Is Your Agent Data Platform: Here’s What’s New  http://approjects.co.za/?big=en-us/power-platform/blog/2026/05/05/dataverse-agent-data-platform/ Tue, 05 May 2026 16:30:00 +0000 Microsoft Dataverse is the agent data platform: the layer that gives agents not just data access, but real business understanding.

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Every organization building AI agents hits the same wall. Agents can access data, but they can’t understand the business. They retrieve records but miss context. They answer questions but don’t know your rules, your relationships, your processes. The bottleneck is no longer model access. It’s business context. Over the past six months, we’ve been building Microsoft Dataverse into the agent data platform: the layer that gives agents not just data access, but real business understanding. 

Agent Data Platform powered by Dataverse

Here’s what’s new for each persona: 

  • For business users, business data in Microsoft 365 Copilot. Your unified business data includes Dynamics 365 or custom apps built in Power Platform powered by Dataverse combined with Microsoft 365 data (i.e. emails, meetings, and documents) to deliver grounded, contextual answers.  
  • For makers, business skills describe a specific process. Skills are the detailed steps-by-step instructions involved, the information required, and the business rules that apply. Agents connected to the Dataverse MCP server discover relevant skills automatically and use them to complete tasks according to your organization’s standards.  
  • For developers, Dataverse Plugin for coding agents. Dataverse plugin is an open-source plugin that lets AI coding agents like Claude Code and GitHub Copilot build and manage Microsoft Dataverse solutions through natural language. Available on Claude Marketplace: install a plugin, say “connect to Dataverse,” and start building. 

Here’s what we shipped and why it matters. 

Dataverse in Microsoft 365 Copilot

Business data has been locked behind app-specific experiences. Business users context switch between Dynamics 365, Power Apps, Outlook, and Teams to piece together the full picture. What if Copilot could understand your business data the way your best people do? 

That’s now happening. In March, we announced Microsoft 365 Copilot embedded as an in-app sidecar experience within Power Apps, Dynamics 365 Sales, and Dynamics 365 Customer Service. Under the hood, we introduced a reasoning layer natively integrated in Microsoft 365 Copilot, reconciling enterprise data and work signals from across your apps to power the combination of critical sources of business data and insights: Microsoft 365 apps, Dynamics 365 apps, and Power Platform. Coming soon in early June, business data will be available across Microsoft 365 Copilot experiences in Copilot App on desktop, Teams, Outlook, Word, Excel, and PowerPoint.

What does this look like in practice? Ask Microsoft 365 Copilot “There’s new guidance about vendor selection. For overdue issue, please select which vendor to assign” and get a precise list grounded in your CRM records and email signals. No report building. No app switching. No guesswork. Let’s see this in action. 

By leveraging the intelligent semantic layer in Agentic AI powered Dataverse Search, Microsoft 365 Copilot experiences deliver answers using an adaptive reasoning process based on schema and keywords. This allows Microsoft 365 Copilot to understand tables and relationships and how to navigate them to get the right answers rather than doing just keyword search. 

The same proven unified semantic search index that powers global search in Power Apps also provides retrieval and grounding for Copilot, agents, and MCP tools. When your search gets better, every AI experience built on it gets better too. In this release, we’ve made the index faster, more real-time, and easier to manage: 

  • Up to 6× faster initialization. Turning on Dataverse search for a new environment now takes minutes, not hours. Your team gets started faster, so they can build more.  
  • Near real-time data freshness. Newly added or updated records appear in Copilot results within minutes. Copilot and agents are ground on current business data, not stale snapshots. 
  • Zero-disruption schema evolution. Adding or removing columns no longer pauses indexing. Schema changes refresh in the background while Dataverse Search keeps running. 
  • Visibility and control for admins. See exactly which tables are indexed, how much capacity each consumes, and download usage reports. Enable or disable indexing for Copilot and search independently, so you can scale AI workloads without impacting existing search behavior. 

One search index for Copilot, agents, and MCP. All grounded in the same governed business data in Dataverse. 

Business skills: teach agents how your organization works 

Your organization’s most valuable knowledge lives as tribal knowledge in people’s heads: the escalation path for a vendor issue, the approval steps for a sales proposal, the process to assign the right specialist to staff your project. Agents can’t access what isn’t simply written down. 

Business skills in Dataverse, now in public preview, captures your processes, policies, and domain expertise as natural-language instructions. Makers can write business skills in plain language or upload existing skills and govern them with built-in controls. The best part: any agent connected to the Dataverse MCP server discovers your skills automatically, whether it runs in Copilot Studio, GitHub Copilot, Azure AI Foundry, or any MCP-compatible client. Define once, apply everywhere – let’s see this in action.  

Velrada makes this real in a field service inspection scenario: 

“Velrada built Inspection Agent to help worksite supervisors and field workers track the maintenance status of their equipment – so they can trust the tools used to get the job done. The Inspection Agent uses business skills to perform an equipment inspection with the user. For an onsite HVAC inspection, the Inspection Agent will invoke the business skill to determine the questions to ask based on equipment class, checks the last inspection outcomes, and pull in context of any historic issues. The result: a conversational assessment that produces a consolidated inspection report on the HVAC unit’s condition and follow-up guidance for maintenance” 

— Matthew Pontel, General Manager of Applied AI, Velrada 

Learn more about business skills: Introducing business skills: Teach agents how your organization works  – Microsoft Power Platform Blog 

Dataverse plugin: coding agents now speak Dataverse 

Enterprise development is shifting from writing code to directing AI agents. Developers describe intent; coding agents orchestrate the right tools over governed business data. What used to require juggling APIs, CLIs, and documentation can now be expressed as a single prompt. 

The Dataverse Plugin for coding agents (in public preview) makes this real. Install one open-source plugin, and your coding agent gets full Dataverse fluency. Under the hood, the plugin packages four tools and knows which one to reach for:  

  • Python SDK for batch and scripted operations. 
  • PAC CLI for admin gestures like solution export and environment management. 

No manual setup. Describe your intent; the agent handles the orchestration. See this in action. 

Picture this: a platform developer needs to build a customer escalation tracker on Dynamics. With the Dataverse plugin for coding agents, they connect to their environment, create tables, define business skills, configure security roles, and deploy the solution, all through natural language in their coding agent. That’s modern development with coding agents. 

Get started: Install the Dataverse Plugin 

Dataverse agentic evolution: from experimentation to execution 

Six months ago, agents could access your data. Today, they understand your business: your schema, your processes, your rules. The wall between data access and business understanding is coming down: that’s the agent data platform. Today at EU Biz Apps Summit in Cologne, we’re showing all of this live. And we’re just getting started. At //Build in June, we’ll share what’s next. Learn more:  

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Build Agent 365-ready Adaptive Intelligence with Work IQ and Dataverse http://approjects.co.za/?big=en-us/power-platform/blog/2026/01/27/build-adaptive-intelligence/ Tue, 27 Jan 2026 16:42:36 +0000 Adaptive Intelligence, and it's now within reach. See how we build enterprise-grade agents that don't just automate—they think, adapt, and elevate work.

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What if your AI agents truly understood your business—your data, your workflows, your goals—and IT could still govern them at scale?

That’s the promise of Adaptive Intelligence, and it’s now within reach. In our recent Ignite session, Jason Huang and I walked through exactly how to build enterprise-grade agents that don’t just automate—they think, adapt, and elevate work. See this in action:

Why Adaptive Intelligence Matters

Security and governance are table stakes. The real question is: are your agents smart enough to be useful?

The real differentiator is intelligence. Agents that understand your business. That remember how you work. That act proactively, not reactively.

That’s Adaptive Intelligence. And it’s built on two foundations:

  1. Work IQ + Dataverse: Work IQ is the intelligence layer that gives agents context, memory, and inference. Dataverse extends Work IQ with trusted business data: giving agents the ability to reason over your structured enterprise data while staying inside governed boundaries. Together, they transform Dataverse from a system of record into an intelligent system of action.
  2. Agent 365: the control plane that makes agents enterprise-ready by default. It handles registry, access control, visualization, interoperability, and security—so IT doesn’t lose control as agents scale.

When Work IQ, Dataverse, and Agent 365 come together, agents don’t just automate. They think. They adapt. They elevate work.

How We Built It

The agent in our demo, Aligna, is an AI teammate for a fictitious construction company (Zava Construction). In the demo, a site coordinator chats with Aligna in Teams: “@Aligna, I’m at the Adatum site, log this plumbing issue, inform the client…” — and Aligna handles the rest.

Here’s how each component powers that workflow:

Step 1: Microsoft Agent Framework

Aligna is built on the Microsoft Agent Framework—it’s what enables the agent to receive the Teams prompt, decide which tools to call, and orchestrate the entire workflow. When the user describes the plumbing issue, the Agent Framework routes the request to the right tools (Dataverse MCP for logging, Mail MCP for communication) and manages the execution flow.

Step 2: Dataverse MCP

When the user says “log this plumbing issue,” Aligna uses Dataverse MCP (now in GA) to create the issue record directly in Dataverse—no forms, no app-switching. All business data (clients, contacts, projects, vendors) lives in Dataverse, and MCP provides the standardized interface for Aligna to read and write that data through natural language.

Step 3: Mail MCP Server

When the user says “inform the client,” Aligna uses the Mail MCP Server to draft and send the email—all within the same conversational flow. The client gets notified about the issue without the user ever leaving Teams.

Step 4: Agent 365 SDK

Every action Aligna takes—logging the issue, sending the email—is recorded via the Agent 365 SDK for compliance and audit. IT gets full observability into what the agent did, when, and why—without requiring extra instrumentation from developers.

Step 5: Dataverse SDK for Python

For developers building agents like Aligna, the Dataverse SDK for Python (in Public Preview) provides direct programmatic access to Dataverse—ideal for custom data operations, schema setup, batch processing, or integrating with Python-based ML pipelines. Also leveraged: Azure OpenAI for model inference

Turn Your Business Data into Agent Intelligence

The tools are here. The documentation is live. Now it’s your turn.

Start building agents that truly understand your business:

  1. Connect to your data — Use Dataverse MCP to give your agents instant access to business data. It’s GA and ready for production.
  2. Write in your language — Python developer? The Dataverse SDK for Python lets you prototype in minutes. .NET team? The Agent Framework has you covered.
  3. Make it enterprise-ready — Register with Agent 365 and your agent inherits identity, governance, and observability from day one.

Your competitors aren’t waiting. The agents your organization needs—agents that think, adapt, and elevate work—you can build them now.

Read More

Related Documentation:

Related Ignite & Blog Resources:

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Dataverse Knowledge in Copilot Studio: Multiline Text Columns and File Columns. http://approjects.co.za/?big=en-us/power-platform/blog/2025/08/11/agent-with-dataverse-knowledge/ Mon, 11 Aug 2025 14:00:00 +0000 Dataverse knowledge in Microsoft Copilot Studio’s latest update now with support for multi-line text and file columns

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Dataverse Knowledge takes center stage in Microsoft Copilot Studio’s latest update—with support for multi-line text and file columns, plus improved answer consistency. These enhancements make agents built in Copilot Studio more intuitive, insightful, and reliable—helping users uncover business-critical information even when it’s buried in long notes or attachments. 

Unlock Deeper Insights with Multiline Text Columns and File Columns in Dataverse Knowledge 

Agents built in Copilot Studio using Dataverse Knowledge can now intelligently search across multiline columns and file columns, making it easier than ever to find the information you need. Just ask in natural language, and these agents will surface the most relevant results—no matter where the data lives. Searching through long comments or attached files is now easier than ever with Dataverse Knowledge.  

Here are some examples you can try out: 

  • Which phones have the best reviews for creators?” 
  • “Show me the phone that’s a balance for storage and battery life” 
  • What are some reviews of Contoso phone?” 

and you’ll get the exact results you need—even if that information is buried inside a file or multiline text. 

Note: Dataverse Knowledge in Copilot Studio does not support images and tables in files and will only return results in the language of the content. For example, if a document is written in English, it must be searched using English terms. Multi-lingual/image/table search from within files will be included in a future update. 

Improved Answer Consistency with Dataverse Knowledge 

We know it can be frustrating to get different search results for the same question, especially when you rely on accurate information for your work. That’s why we’ve added a new behind-the-scenes update that makes sure your agents grounded in Dataverse Knowledge can produce the same reliable answer every time you repeat a search—even if you ask the same question at a different time. It’s perfect for common work tasks like checking support issues, reviewing contracts, or pulling reports. Consistency and trust in your results are now built right in! 

For example, a query such as – “find contracts expiring within the next 60 days” in compliance or legal review scenarios to demonstrate how accuracy and reliability are maintained for repeated business-critical queries across time. 

Note: This update requires no set up and should be available out of the box. 

With support for multi-line and file columns, improved answer consistency, and reliable caching, Dataverse Knowledge in Microsoft Copilot Studio is now more powerful than ever. These updates remove long-standing limitations and make it easier to surface business-critical insights—no matter where they’re hidden. 

Whether you’re building agents to handle support tickets, review contracts, or analyze feedback, Copilot Studio now gives you the tools to deliver faster, more accurate, and more consistent results:

  • Try natural language queries on long notes and files 
  • Experience consistent results with built-in caching  

See resources to learn more and get started:

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Dataverse MCP Server: A Game Changer for AI-Driven Workflows http://approjects.co.za/?big=en-us/power-platform/blog/2025/07/07/dataverse-mcp/ Mon, 07 Jul 2025 14:00:00 +0000 As AI becomes integral to business workflows, the Dataverse Model Context Protocol (MCP) Server offers a foundational approach to integrating large language models with enterprise data. Whether you’re building with Microsoft Copilot Studio, Claude desktop, or GitHub Copilot in VS Code, the Dataverse MCP Server unlocks a new level of integration between AI and data.

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As AI becomes integral to business workflows, the Dataverse Model Context Protocol (MCP) Server offers a foundational approach to integrating large language models with enterprise data. Whether you’re building with Microsoft Copilot Studio, Claude desktop, or GitHub Copilot in VS Code, the Dataverse MCP Server unlocks a new level of integration between AI and data.

What Is the Model Context Protocol (MCP)?

MCP is an open protocol that bridges large language model (LLM) applications with external data sources and tools. It acts as a bridge between AI assistants and enterprise data, enabling secure, standardized access to Dataverse resources. When Microsoft Dataverse acts as an MCP server, it enables intelligent, secure, and standardized access to your data—tables, records, and more—across a variety of MCP clients.

MCP is an open protocol that bridges large language model (LLM) applications with external data sources and tools

Why It Matters

Dataverse MCP Server isn’t just another connector—it’s a paradigm shift. Here’s why:

  • Unified AI-to-Data Access: MCP standardizes how LLMs like Copilot Studio agents, Claude, and GitHub Copilot interact with Dataverse. This means that your enterprise data is now fully extensible and platform agnostic.
  • Natural Language interface: Users can ask questions like “show me my contacts” or “apply 10% discount to Widget123 product” and get real-time response from your Dataverse environment. Under the hood, MCP clients translate these natural language requests and execute one or more built-in tools in Dataverse.
  • Powerful Tooling: Dataverse MCP Tools currently support built-in tools that allow users to insert or update data in tables, view tables and their description, read data from a table, search knowledge, view and execute prompts available in environment. See List of tools available in Dataverse MCP Server documentation for more details.
  • No SDKs, no custom APIs—just natural language and secure execution.
Dataverse MCP Server isn’t just another connector—it’s a paradigm shift.

MCP Clients are capable of determining the appropriate tools to use – so while the below image illustrates a workflow that an agent may take, the tools used by the MCP Client may vary from time to time.

MCP Clients are capable of determining the appropriate tools to use – image illustrates a workflow that an agent may take

Works Across Your Favorite MCP Hosts and Clients

Microsoft Copilot Studio

Connecting is as simple as adding the Dataverse MCP Server as a tool to your agent. No local setup required. You can immediately test commands like: “List tables in Dataverse”, “Describe table account”.

Using Dataverse MCP in Copilot studio is a compelling alternative to having agent makers using custom Dataverse connectors to manually create flows to store, update, or retrieve the data. Now, you as a maker, can simply add Dataverse MCP from the Tools tab inside an agent in Copilot Studio. Under the hood, when an agent receives user messages such as “What is the status of my support ticket #12345”, this translates to the agent calling the appropriate Dataverse MCP Tools such as determining the appropriate table to read via list_tables or describe_table, then read_query against that table.

Now makers can build dynamic, intelligent workflows with conversational agents that talk directly to Dataverse—no flows, no APIs, just prompts + tools!

Using Dataverse MCP in Copilot studio is a compelling alternative to having agent makers using custom Dataverse connectors to manually create flows to store, update, or retrieve the data

Claude Desktop

With a quick configuration update, Claude can tap into your Dataverse environment. You can even toggle which tools are available per MCP server, giving you full control.

Business users often has to rely on their IT team  to create dashboards. Now, with Dataverse MCP in Claude, the workflow is much streamlined. Here’s an example to illustrate it.

  • User can request in Claude: “Create a dashboard showing opportunities by region”
  • This translates to Claude identifying which table(s) opportunities are stored using list_tables or describe_tables tools, then using read_query to get the information for Claude then to perform a code-gen to render an interactive dashboard.

Dataverse MCP, thus, empowers business users to explore and interact with their business data stored in Dataverse conversationally—zero-code access to real-time, live insights and automation.

Claude can tap into your Dataverse environment

GitHub Copilot in VS Code

Reuse your Claude configuration or set up a new one. Once connected, you can interact with Dataverse directly from VS Code GitHub Copilot in Agent mode. For example: “store the attached csv file as Employee in Dataverse”. Under the hood, GitHub Copilot will automatically inspect the data and upload the data into the table – all achieved by invoking tools like list_tables, describe_table, and create_record tools to achieve this.  

Interact with Dataverse directly from VS Code GitHub Copilot in Agent mode

With Dataverse MCP, developers see improved productivity as they don’t need to open multiple portals or tools. Schema inspection, CRUD actions, and code generation happen inside the IDE!

⚠️ A Note on Preview Features

This is a preview capability—perfect for early adopters and innovators. While not yet production-ready, it’s a fantastic opportunity to explore, experiment, and provide feedback to shape the future of AI + data integration.

Coming Soon: Remote MCP Server + Full Table Operations!

We’re thrilled to announce that we’re bringing even more power and flexibility to Dataverse MCP! Starting end of July, we’re rolling out a Private Preview of two major capabilities:

  • Remote MCP Server – drastically simplify agent setup by just updating the environment URL, no complex configurations needed
  • Expanded Tooling – including long-awaited operations like create_table, update_table, and delete_table, enabling full control over your Dataverse schema through agents

If you’re as excited as we are and want early access, Click here to express your interest and be among the first to shape the future of agent-powered data platforms.

Final Thoughts

The Dataverse MCP Server represents a strategic evolution in how makers, developers, and data professionals interact with enterprise data. By enabling natural language access to Dataverse, it simplifies development and accelerates innovation across the Power Platform ecosystem and beyond.

Whether you’re designing data models, querying records, or building intelligent agents, MCP makes Dataverse the brain behind your AI.

Learn more:

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Data Agent Architecture powered by Microsoft Dataverse  http://approjects.co.za/?big=en-us/power-platform/blog/2025/06/16/data-agent-architecture-powered-by-microsoft-dataverse/ Mon, 16 Jun 2025 14:00:00 +0000 http://approjects.co.za/?big=en-us/power-platform/blog/?p=129673 Turning Hidden Data into Actionable Insights: Why Manual Processes Are Failing Your Business  In every organization, data fuels critical business processes. Yet, much of this data is trapped in formats and workflows that make it difficult to access, understand, and use effectively.

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Turning Hidden Data into Actionable Insights: Why Manual Processes Are Failing Your Business 

In every organization, data fuels critical business processes. Yet, much of this data is trapped in formats and workflows that make it difficult to access, understand, and use effectively. A common example is invoices arriving as PDF attachments via email—disconnected from the broader business data ecosystem. These files are hard to search, lack structured linkage to financial systems, and often require tedious manual intervention to process. 

For technical decision-makers, this isn’t just an operational headache—it’s a strategic liability. 

  • Manual data processing drains valuable resources, pulling skilled teams away from higher-value work. 
  • Data integrity suffers, increasing the risk of errors, missed payments, or compliance issues. 
  • Lack of discoverability means critical insights remain hidden, slowing down decision-making and reducing the agility of the business. 

In a data-driven world, relying on fragmented and manual workflows undermines the ability to scale, innovate, and stay competitive. The challenge is not having the data—it’s unlocking its potential efficiently and at scale. 

This post will explore how, with Microsoft Copilot Studio and Microsoft Dataverse, businesses can build intelligent agents that automatically turn fragmented data into structured, actionable insight. These AI-powered agents extract, validate, and enrich business data as it arrives, store it in Dataverse for reuse, and loop in humans only when needed. The result? Cleaner data, faster decisions, and a foundation for scalable, intelligent automation. 

Learn how Dataverse provides a secure, scalable, and agent-ready foundation for your data strategy in the Why Dataverse Overview

Figure 1: Built for Data Agents overview, with Dataverse as the underlining data platform for Agents. 

A Better Way: Activating Data with Autonomous Agents (with Dataverse at the Core) 

Modern businesses now have access to a more scalable, intelligent approach to data processing: Data Agent architectures powered by autonomous agents with human-in-the-loop oversight. 

What does this mean in practice? 

  • Autonomous agents handle repetitive data processing tasks intelligently: extracting, validating, and enriching data from unstructured sources such as emails, PDFs, tickets, and more. 
  • Dataverse serves as the unified data platform: offering a secure and consistent way to store business data—structured or unstructured—so it can be easily discovered, related, and used across business applications and workflows. 
  • Humans stay in the loop for oversight and decision-making: agents escalate exceptions, low-confidence matches, or contextual queries to human reviewers, who validate and finalize the data. 

The result: Intelligent, high-quality data delivered faster and more reliably, and centralized in Dataverse for seamless integration across business apps, analytics, and automation workflows. 

This architecture directly aligns with how Microsoft Copilot Studio agent flows work: orchestrated automation enables conversational agents (or flows) to autonomously process and route data, while intelligently involving human judgment when context or precision is crucial. With Dataverse at the heart, every interaction, enrichment, and validation feeds into a scalable, governed data platform—ensuring data isn’t just processed but activated for business value. 

While autonomous agents in Copilot Studio can operate independently using built-in tools, makers can enhance their capabilities further with tools like the Model Context Protocol (MCP). MCP isn’t required to build autonomous agents, but it opens up new possibilities for agents to process or store data in Dataverse. This bidirectional flow ensures AI solutions remain context-rich, action-oriented, and aligned with Microsoft’s broader commitment to openness and extensibility. 

Through integration with MCP, agents gain powerful data handling capabilities such as: 

  • Query: Discover table schemas and retrieve live Dataverse records via structured or natural-language queries; 
  • Knowledge/Search: Lets agents “chat” about data – they can search tables and answer questions contextually without brittle hand-coded logic; 
  • Upload (Create/Update): Insert new records or update existing ones in Dataverse, with built-in schema validation to maintain data integrity; 
  • Generate (Grounded AI): Run custom AI prompts grounded in real data (e.g. summarize a record or evaluate sentiment). 

Because the MCP server honors Dataverse’s data model and access controls, agents can safely reason over and act on enterprise data. In practice, developers can simply add a Model Context Protocol tool in Copilot Studio and point it to their Dataverse. The agent then automatically queries and updates that data as part of its workflow – for example, posting a generated summary back into a record. 

Figure 2: Shows adding the Model Context Protocol Server tool within Copilot Studio. 

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Get Started Building Intelligent Agents That Work for You 

As organizations move beyond basic automation, the next frontier isn’t just bots that complete tasks, it’s intelligent agents that understand, interact, and learn from business context. With Copilot Studio and Dataverse, you can create AI-powered agents that operate securely, respond to real-world triggers, and collaborate with humans to drive outcomes. 

We’ll walk through how to build and operationalize intelligent agents in six easy steps: 

Step 1: Trigger events from your business processes 

Agents can be triggered automatically based on business events—such as a new email, a service request, or a record added to a Dataverse table. These triggers, configured in Power Automate, initiate the agent’s workflow and response logic in Copilot Studio. 

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Step 2: Equip agents with intelligent tools 

Once triggered, the agent uses Copilot Studio capabilities to process requests: 

  • Knowledge Sources provide background information. 
  • Topics guide the structure of the conversation. 
  • Tools allow agents and MCP server(s) to perform tasks across systems. 
  • Conversation History maintains context for continuity. 
  • Instructions shape how the generative AI responds. 

Using these tools—along with Agent Flows and logic based on Model Context Protocol—agents can analyze data, perform multi-step actions, and interact meaningfully with users. 

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Step 3: Use Dataverse as an intelligent data layer 

Dataverse brings structure and intelligence to your business data—so your agents can retain context, access relevant records, and contribute to a broader operational view. It gives Copilot agents secure, real-time access to the records, relationships, and history they need to work smarter across your apps and processes. 

With native support for the MCP, agents can draw from and contribute to Dataverse as part of a broader knowledge network. It’s a trusted foundation for building agents that are grounded in data, aligned with workflows, and ready to scale. 

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Step 4: Enable autonomous agents with human oversight 

As agents become more capable, they also need to support human-in-the-loop scenarios. With conversation history and activity logs stored in Dataverse, business users can monitor agent performance, review outputs, and step in when escalation is needed—ensuring oversight, accountability, and trust. 

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Step 5: Coordinate workflows with the Agent Orchestrator 

Agent Orchestrator enables the user to coordinate more complex multi-step workflows by managing how and when tasks are executed across autonomous agents. For complex scenarios, it collects inputs from initial triggers, stores intermediate responses for reuse, and drives execution using Copilot Studio actions, Power Automate flows, or custom APIs. With built-in logic for queuing, task routing, and fallback handling, Agent Orchestrator ensures that each step is carried out by the most suitable agent—making it easier to scale intelligent, resilient automations across the organization. 

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Step 6: Govern secure access and responsible usage 

All agent interactions are secured through enterprise-grade governance controls: 

  • Role-Based Access Control (RBAC) ensures data access is scoped by role, table, and even row. Learn about RBAC. 
  • Secure agent data access with an organized security framework that integrates platform technology, regulatory compliance, and administrative oversight—following best practices for managing access, reducing risk, and ensuring responsible agent behavior. Overview of role-based security in Dataverse

By combining Copilot Studio, Dataverse, and Power Platform tools, enterprises can create intelligent digital workers that adapt to the business, work alongside humans, and scale with confidence. This is how modern enterprises move beyond simple automation—and into a future powered by AI-first, data-smart systems. 

For more information watch Ryan Cunningham and Evan Lew discuss how to Build agent-first solutions with Power Platform and Copilot Studio

Figure 3: Workflow highlighting how Autonomous Agents interact with human and agent oversight, with Dataverse at the core. 

Real world application 

Velrada’s PowerRoster solution is helping frontline organizations reimagine workforce scheduling—reducing complexity and enabling smarter, faster decisions. At the heart of this transformation is ShiftLens, a new capability built with Copilot Studio that uses autonomous agents and intelligent workflows to automate manual scheduling tasks. ShiftLens is designed for high-pressure, high-variability environments such as healthcare and hospitality. When absenteeism is logged, ShiftLens records the key details into Microsoft Dataverse, updates the roster, and recommends staffing changes for manager approval. 

By eliminating the daily scramble to find last-minute replacements, team leaders and managers can focus more on delivery and less on logistics. This intelligent orchestration not only improves operational efficiency but also contributes to better staff satisfaction and customer outcomes. The demo below shows ShiftLens in action at a fictional care home—highlighting how AI-powered scheduling is making frontline workforce management more proactive, resilient, and human-centered. 

Figure 4: Video showcasing Velrada’s ShiftLens Intelligent Rescheduling product, powered by Microsoft Copilot Studio and Dataverse 

Conclusion 

The cost of manual processing isn’t just time—it’s missed insights, slower decisions, and operational drag. Copilot Studio and Dataverse offer a smarter path forward: intelligent agents that not only automate work but understand your data, collaborate with your teams, and evolve with your business. 

This is how leading organizations are moving from scattered workflows to coordinated, AI-powered systems. Whether you’re streamlining frontline operations or scaling data-driven decisions, now is the time to rethink what your business could do with agents that learn, act, and improve—built on a secure, governed foundation. 

Learn more about Copilot Studio and Dataverse

Explore the resources below to take the next step with data agent architecture powered by Copilot Studio and Dataverse. 

From Microsoft Build 2025 

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