Business AI Integration Demo

This project demonstrates how to integrate AI capabilities into a typical business application with .NET Platform It showcases a common scenario where business events flow through the system and get processed, stored, and then made available for AI-powered interactions.

What This Project Shows

This is a hands-on learning project that combines:

• Event-driven architecture with Kafka for processing business data
• AI integration using Model Context Protocol (MCP) to interact with stored data
• Modern development practices with .NET Aspire for orchestration
• .NET Platform features for building AI applicatıon

The demo simulates a simple e-commerce flow where orders are generated, processed, and stored - then made accessible through an AI chat interface that can answer questions about the business data.

Projects

🎛️ Demo.Host (.NET Aspire Orchestrator)

The main orchestrator that manages all services and provides a unified development experience with observability and monitoring.

To run the complete demo:

dotnet run --project Demo.Host

Opens Aspire dashboard with unified logging, metrics, and service management

🚀 Kafka.Producer

Generates mock e-commerce order events to simulate real business activity.

Features:

• Creates realistic order data every 5-10 seconds
• Publishes events to the order-events Kafka topic

📥 Kafka.Consumer

Processes incoming order events and stores them in the database for later use.

Features:

• Consumes messages from Kafka topics
• Stores order and payment data in PostgreSQL
• Handles business logic like fee calculations

🧠 AI.Agent.Custom

A custom AI agent implementation(just some dummy agent) using Microsoft's Agent Framework, exposed as an MCP tool for learning and experimentation.

Features:

• Implements CustomAgent using Microsoft Agent Framework
• Maintains conversation context through persistent thread storage
• Thread state is preserved across application restarts in {BaseDirectory}/thread/agent_thread.json

Key Components:

• CustomAgent: Custom agent implementation with thread persistence
• CustomAgentThread: Thread management with JSON serialization/deserialization
• Thread reuse: Automatically loads existing threads on startup to maintain conversation history

🤖 MCP.Server

Provides AI tools that can access business data stored in the database and hosts the custom AI agent.

Features:

• Exposes business data through MCP protocol
• Hosts the CustomAgent as an MCP tool
• Allows AI to retrieve recent payments
• Caches frequently accessed data for performance

Listing Tools for MCP Server

curl -X POST https://localhost:5001/ \
  -H 'Content-Type: application/json' \
  -H 'Accept: application/json, text/event-stream' \
  -H 'MCP-Protocol-Version: 2025-06-18' \
  -d '{
    "jsonrpc":"2.0",
    "id":2,
    "method":"tools/list",
    "params":{}
  }'

Result

event: message
data: {
    "result": {
        "tools": [
            {
                "name": "get_random_number",
                "description": "Generates a random number between the specified minimum and maximum values.",
                "inputSchema": {
                    "type": "object",
                    "properties": {
                        "min": {
                            "description": "Minimum value (inclusive)",
                            "type": "integer",
                            "default": 0
                        },
                        "max": {
                            "description": "Maximum value (exclusive)",
                            "type": "integer",
                            "default": 100
                        }
                    }
                }
            },
            {
                "name": "accountant_does_financial_calculations",
                "description": "Accountant Agent that can perform financial calculations for net amounts for orders payments",
                "inputSchema": {
                    "type": "object",
                    "properties": {
                        "query": {
                            "description": "Input query to invoke the agent.",
                            "type": "string"
                        }
                    },
                    "required": [
                        "query"
                    ]
                }
            },
            {
                "name": "get_recent_payments",
                "description": "Returns recent payment transactions from the payment system",
                "inputSchema": {
                    "type": "object",
                    "properties": {
                        "count": {
                            "description": "Number of payments",
                            "type": "integer",
                            "default": 7
                        }
                    }
                }
            }
        ]
    },
    "id": 2,
    "jsonrpc": "2.0"
}

💬 MCP.Host

A web interface where users can chat with AI about their business data.

Features:

• Interactive chat interface
• AI can answer questions about business related data such payments
• Connects to external AI models through GitHub Models

Architecture

                            ┌─────────────────┐
                            │   🎛️Demo.Host   │
                            │  (.NET Aspire)  │
                            │ - Orchestration │
                            │ - Observability │
                            │ - Configuration │
                            └─────────────────┘
                                     │
                                     │ manages development environment
                                     ▼
 ─────────────────────────────────────────────────────────────────────────────────────────────────────────
              ┌─────────────────┐                    ┌───────────────────┐     PostgreSQL
              │     Producer    │                    │      Consumer     │   ┌─────────────┐
              │                 │                    │                   │   │   Orders    │
              │ - Order Events  │                    │ - Event Processing│──►│   Table     │
              │ - Mock Data     │                    │ - Business Logic  │   │             │
              │ - Publishing    │                    │ - Data Storage    │   ├─────────────┤
              └─────────────────┘                    └───────────────────┘   │  Payments   │
                     │                                         ▲  │          │   Table     │
                     │                                         │  │          ├─────────────┤
                     │                                         │  │          │   Fees      │
                     │                                         │  │          │   Table     │
                     │           ┌─────────────────┐           │  │          └─────────────┘
                     │           │     Kafka       │           │  │                │
                     │           │                 │           │  │                │
                     └─────────► │ - Topics        │ ──────────┘                   │
                                 │   - order-events│                               │
                                 │                 │                               │
                                 └─────────────────┘                  provides data│
                                                                                   │ 
                                                                                   │
┌──────────────────┐                                                               │ 
│     AI.Agent     │                                                               │     
│  (CustomAgent)   │                                                               │
│                  │                                                               │ 
│ - Agent Framework│                                                               │
│ - Thread State   │───────┐                                                       │ 
│ - Persistence    │       │Agent used as a tool                                   │
└──────────────────┘       │                                                       │ 
                           │                                                       │
                           │                                                       │
                           |                                                       │
              ┌─────────────────┐                                                  │
              │    MCP.Server   │                                                  │
              │                 │◄─────────────────────────────────────────────────┘
              │ - Business APIs │                 
              │ - Data Caching  │                 
              │ - MCP Tools     │                  
              │ - Agent Hosting │                 
              └─────────────────┘───┐                 
                       │            │                                 
                       │            │                                 
                       │            │     ┌─────────────────┐         
                       │            └────►│   Cache(Valkey) │
                       │                  │                 │
                       │                  │                 │
                       │                  └─────────────────┘   
                       │
                       │
                       │ MCP protocol
                       ▼
              ┌─────────────────┐        External AI      
              │   MCP.Host(web) │   ┌─────────────────┐
              │                 │───│  GitHub Models  │
              │ - Web Interface │   │                 │
              │ - AI Integration│   │ - LLMs          │
              │ - Chat Features │   │                 │
              └─────────────────┘   └─────────────────┘

How It Works

1. Data Generation: The Producer generates realistic order events with some payment info also. And publishes the order event to a Kafka topic.

2. Event Processing: The Consumer processes events from given Kafka topic and stores business data. Also some mock fancy business operation is done. And all related data is inserted into PostgreSQL database.

3. AI Access: An MCP Server exposes business data through standardized APIs within .NET Platform. It is a remote MCP endpoint. .NET Platform has a template to create a minimal MCP Server: dotnet new mcpserver

4. User Interaction: Users chat with AI through the web interface to get insights about their business data. Based on one of .NET templates: dotnet new aichatweb For this demonstration, gpt-4o-mini is used via GitHub Models

• In this view within a given simple prompt, host application can understand which MCP tool to be invoked and get_recent_payments tool is called remotly.
• MCP server's get_recent_payments returns just some data from a database.
• Host application uses the result from MCP server to generate more responsive and effective result for given prompt.

This demonstrates a practical approach to building AI-powered business applications using modern development tools and patterns with .NET.

References

• https://learn.microsoft.com/en-us/dotnet/ai/
• https://learn.microsoft.com/en-us/agent-framework/overview/agent-framework-overview