Genai Eshop Semantic Kernel
Practical GenAI-Eshop application using Semantic Kernel, multi-agent orchestrations, Mcp tools, A2A Agents, Semantic Search, Aspire and more.
Installation
npx genai-eshop-semantic-kernelAsk AI about Genai Eshop Semantic Kernel
Powered by Claude Β· Grounded in docs
I know everything about Genai Eshop Semantic Kernel. Ask me about installation, configuration, usage, or troubleshooting.
0/500
Reviews
Documentation
π‘ Practical
GenAI-Eshopapplication using Semantic Kernel,multi-agent orchestrations,Mcp tools,A2A Agents,Semantic Searchand more.
[!NOTE] We migrated the
GenAI-Eshopapplication to use the microsoft/agent-framework instead of Semantic Kernel in the mehdihadeli/genai-eshop repository. You can check their differences in a practical application there.
[!NOTE] π₯ See my talk at JetBrains .NET Day 2025, where I explain Generative AI and demonstrate this practical example.
Features
- β Using microsoft/semantic-kernel for multi-agent orchestrations and AI related services
- β
Using
Qdrant Semantic Kernel Connectorfor storing vector data for doingSemantic Meaning SearchandHybrid Searchusing vector data and semantic kernel - β
Using Semantic Kernel
EmbeddingGeneratorbased on chosen providers likeOllama,AzureOpenAI, andOpenAIfor generating vector data for semantic search - β
Using Semantic Kernel
ChatCompletionbased on chosen providers likeOllama,AzureOpenAI, andOpenAIfor communicating with different models for generating responses - β
Using
Mcp toolsbased onhttpand json-rpc for calling endpoints in our Mcp server and calling third party tools by LLMs for Fine-grained functions - β
Using
Multi-Agent Orchestrationsforlocalandexternalagents communication using agentsparent child agent relationshipsand different Semantic KernelβsAgent Orchestration PatternslikeParent-Child,GroupChatandSequentialorchestration - β
Using
Agent2Agent Protocol (A2A)protocol based on http and json-rpc for calling and using external agents - β
Using
Vertical Slice Architectureas a high-level architecture - β
Using
Minimal APIsfor handling requests - β
Using
OpenTelemetryfor collectingLogs,MetricsandDistributed Traces - β
Using
.NET Aspirefor cloud-native application orchestration and enhanced developer experience
Architecture Diagram

Getting Started
Prerequisites
Install an IDE
You can use any of the following IDEs for development:
- JetBrains Rider (Recommended)
- Visual Studio 2022
- Visual Studio Code
Ensure the IDE includes support for .NET Core and plugins for C#.
Run Application
Aspire
Install the Aspire CLI tool:
# Bash
dotnet tool install -g Aspire.Cli
To run the application using the Aspire App Host and using Aspire dashboard in the development mode run following command:
aspire run
Note:The
Aspire dashboardwill be available at:https://localhost:17056andhttp://localhost:15234
Using Docker-Compose
# Start docker-compose
docker-compose -f .\deployments\docker-compose\docker-compose.yaml up -d
# Stop docker-compose
docker-compose -f .\deployments\docker-compose\docker-compose.yaml down
This command will run the required infrastructure for the application
Open the solution file genai-eshop-semantic-kernel.sln in your preferred IDE (e.g., Rider or Visual Studio).
Now you can run each microservice using the IDE.
License
The project is under MIT license.

