There are some great articles that explain how to integrate an MCP server built on Azure with a declarative agent created using Microsoft Copilot Studio. These approaches aim to extend the agent’s capabilities by supplying it with tools, rather than defining a fixed role. Here were some of the challenges w encountered: The agent's behavior can only be tested through the Copilot Studio web interface, which isn't ideal for iterative development. You don’t have control over which LLM is used as the orchestrator—for example, there's no way to specify GPT-4o. The agent's responses don’t always behave the same as they would if you were prompting the LLM directly. These limitations got me thinking: why not build the entire agent myself? At the same time, I still wanted to take advantage of the familiar Microsoft 365 Copilot interface on the frontend. As I explored further, I discovered that the Microsoft 365 Copilot SDK makes it possible to bring in your own custom-built agent.
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Here is the original article written in Japanese. There are some great articles that explain how to integrate an MCP server built on Azure with a declarative agent created using Mic...
Updated Aug 15, 2025
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