What is Model Context Protocol (MCP)?

MCP is an open protocol that standardizes how applications provide context to Large Language Models (LLMs), enabling seamless integration of diverse data sources and tools directly into AI models.

Does this tool provide a way to learn about MCP?

Yes, it includes a sample 'Jokes MCP server' that users can deploy and integrate for hands-on learning and practical application of the Model Context Protocol.

How does Copilot Studio Integration facilitate MCP use?

This tool simplifies the deployment of an MCP server (locally or to Azure Container Apps) and its integration with Microsoft Copilot Studio agents, Visual Studio Code, and GitHub Copilot for enhanced AI capabilities.

Copilot Studio Integration

Name: Copilot Studio Integration
Author: Nikhita196

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Facilitates the deployment and integration of a Model Context Protocol (MCP) server, enabling enhanced AI model capabilities within Microsoft Copilot Studio.

This tool serves as a comprehensive lab and template for deploying a Model Context Protocol (MCP) server and integrating it seamlessly with Microsoft Copilot Studio. It demonstrates how MCP, an open protocol defined by Anthropic, standardizes the way applications provide context to large language models, allowing makers to connect existing knowledge servers and APIs directly into Copilot Studio. By leveraging existing connector infrastructure, it ensures enterprise-grade security and governance controls while supporting real-time data access for AI-powered agents, bridging the gap between custom data sources and powerful AI capabilities.

主な機能

01Integrate MCP server with Visual Studio Code / GitHub Copilot

02Includes a sample Jokes MCP server for hands-on learning

030 GitHub stars

04Integrate MCP server with Microsoft Copilot Studio agents

05Deploy MCP server locally or to Azure Container Apps

06Leverages Power Platform connector infrastructure for enterprise security and governance (VNet, DLP)

ユースケース

01Connecting custom data sources and APIs to Microsoft Copilot Studio for richer AI interactions

02Developing and testing Model Context Protocol (MCP) servers for LLM integrations

03Providing real-time context to AI-powered agents in conversational AI applications