An AI knowledge base/agent built with .Net 9, AntBlazor, Semantic Kernel, and Kernel Memory, supporting local offline AI large models. It can run offline without an internet connection. Supports Aspire for monitoring application data.

Sample for context-aware Agentic RaG, Q&A with multi-source verification, and self-curating knowledge base. Powered by Azure AI Foundry Agent Service, Azure AI Search with agentic retrieval and query rewrite, Semantic Kernel and LangGraph agents running in Azure Container Apps, and ready for Copilot Studio

Learn about Semantic Kernel, Microsoft's AI orchestration library. Build and interact with agents, plugins, and plans using various providers.

VexFS is a Linux kernel-native file system with built-in vector search and semantic memory. Designed for AI agents, RAG, and LLM workloads, it merges POSIX storage with vector-native indexing. Built in Rust, bootable via QEMU, and engineered for AGI infrastructure.

Demonstrates how to build a modern .NET web application that integrates with both Azure AI Foundry Agents and Semantic Kernel Agents.

Simple Agentic AI system that leverages Semantic Kernel to orchestrate end-to-end workflow between user (human) and an agent equipped with tools. Evaluate the system through built-in evaluation methods with the Azure AI Foundry SDK and the Azure AI Evaluation library.

Microsoft Semantic Kernel Quick-start is a 100% Microsoft starter kit for building agentic apps with C#, Blazor (Fluent UI), ASP.NET Core, and SQL Server—no JavaScript required. It delivers a Copilot-style chat client, built-in data tools, and automated Azure deployment for real-world AI on a familiar .NET stack.

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Multi-Agent AI Application(Python) that uses Semantic-Kernel along with Azure AI Agent Service in Azure Ai Foundry

This repository contains the code samples and practical implementations from the "CODE Presents" webinar "Building Intelligent Multi-Agent Systems with Microsoft's Semantic Kernel." The session demonstrates how to orchestrate collaborative AI agents in .NET, featuring persistent vector memory and MCP tool integration.

A multi-agent demo using Azure AI Foundry Agent Service and Semantic Kernel to build web applications. Playwright MCP is used for interactive testing and Azure Communication Services keeps the human in the loop with phone call integration.

Contains a collection of advanced C#/.NET/Python sample applications and tools for working with AI, Model Context Protocol (MCP), Semantic Kernel, Microsoft Agent Framework and Azure OpenAI. Each folder demonstrates a unique scenariofor building intelligent, multi-agent systems and testing model performance

An example of a multi-agent system built with Semantic Kernel

🤖🤝🤖AI agent orchestration patterns with Semantic Kernel and AutoGen. 💸Investment advisor scenario.

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Semantic Kernel Agents implemented with OpenAI AI Assistants

This project serves as an interactive tutorial series showcasing the integration of Azure Durable Functions with Semantic Kernel, enhanced with a Flask CLI frontend. Each part of the series introduces new functionalities, from simple Q&A agents to complex orchestrations, demonstrating the power of combining cloud computing with AI.

Empower your projects with Autonomous Multi-Agent Group Chats, seamlessly integrated with Copilot Agent Plugins using the cutting-edge Microsoft Semantic Kernel. Unlock the future of AI-driven collaboration and conversational intelligence with C#-powered solutions

This project demonstrates a proof of concept for building an AI agent using the Semantic Kernel Python SDK that interfaces with Grafana through a local MCP server.

Demonstration of Azure AI Agent with Bing Search grounding capabilities using Semantic Kernel. Migration guide from legacy Bing Search APIs

Forked and updated from https://github.com/MicrosoftLearning/MSLearn-Develop-AI-Agents-with-Azure-OpenAI-and-Semantic-Kernel-SDK.git

Agentic AI App with Semantic Kernel & C#

Agentic AI-powered calculator built with C#, Semantic Kernel & Clean Architecture.

Building an AI Agent with Blazor, C#, Semantic Kernel & ChatGPT

AI Agents built with Microsoft Semantic Kernel framework using Selector design patterns. Written in C#.

AI Agents built with Microsoft Semantic Kernel framework using a custom Plugin. Written in C#.

AI Agents built with Microsoft Semantic Kernel framework using Roundrobin design patterns. Written in C#.

Desktop AI agent: multi-chat, conversation branching, MCP servers, recursive sub-agents. Built with .NET 9, Avalonia, Semantic Kernel.

AI-Agent is a full-stack, intelligent assistant built with the Semantic Kernel Agent Framework. It combines a React + Tailwind frontend with an ASP.NET Core + Semantic Kernel backend to deliver a context-aware, extensible AI platform.

Agentic AI solution for exploring and reasoning over Databricks using Azure AI Foundry, Semantic Kernel, OpenAPI, and MCP with full observability and orchestration support.