AI Agent’s Toolbox – Semantic Kernel meets MCP and Python

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​ In this episode, we continue our journey into the Semantic Kernel AI Agents Toolbox, focusing on how to build intelligent agents using MCP Servers and Python. Join us as Evan Mattson walks through three hands-on demos that showcase:

How MCP tools are invoked when constructing AI agents with Semantic Kernel.
Using the GitHub MCP Server
Using the Microsoft Learn MCP Server.
A practical look at how Azure AI Foundry fits into the picture.
Whether you’re just getting started or looking to deepen your understanding of Semantic Kernel and MCP, this episode offers practical insights and real-world examples to help you build more capable AI agents.

Please watch the part 1 “Building AI Agent Workflows with Semantic Kernel” here https://youtu.be/3JFKwerYj04

✅ Chapters:
00:00 Introduction
01:14 Whats MCP – Model Context Protocol
02:33 API Economy vs MCP Servers
05:27 How the AI Agent communicates with MCP Servers
07:53 Demo – How Function calling works! StreamableHTTP Microsoft Learning Plugin
15:59 Demo – GitHub MCP Server Integration with MCPStdioPlugin
18:32 Demo – Azure AI Foundry Integration
20:48 How to Contribute and Getting Started

✅ Resources:
Find the latest info about the open-source Semantic Kernel project at: https://github.com/microsoft/semantic-kernel and https://aka.ms/semantic-kernel

Addding MCP Plugins: Give agents access to MCP Servers | Microsoft Learn

MCP Samples: semantic-kernel/python/samples/concepts/mcp at main · microsoft/semantic-kernel

Getting Started with Agents: semantic-kernel/python/samples/getting_started_with_agents/azure_ai_agent/step09_azure_ai_agent_mcp.py at main · microsoft/semantic-kernel

SemanticClip repo: https://github.com/vicperdana/SemantiClip

📌 Let’s connect:
Jorge Arteiro | https://www.linkedin.com/in/jorgearteiro
Evan Mattson | https://www.linkedin.com/in/evanrmattson

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