Quickstart Streaming Agents

Streaming Agents on Confluent Cloud Quickstart

[](https://www.confluent.io/get-started/?utmcampaign=tm.pmmcd.q4fy25-quickstart-streaming-agents&utmsource=github&utmmedium=demo)

Build real-time AI agents with Confluent Cloud Streaming Agents. This quickstart includes three hands-on labs:

Lab Description

Lab1 - Price Matching Orders With MCP Tool Calling NEW! Now using new Agent Definition (CREATE AGENT) syntax. Price matching agent that scrapes competitor websites and adjusts prices in real-time.

Lab2 - Vector Search & RAG Vector search pipeline template with retrieval augmented generation (RAG). Use the included Flink documentation chunks, or bring your own documents for intelligent document retrieval.

Lab3 - Agentic Fleet Management Using Confluent Intelligence End-to-end boat fleet management demo showing use of Agent Definition, MCP tool calling, vector search, and anomaly detection.

Lab4 - Public Sector Insurance Claims Fraud Detection Using Confluent Intelligence Real-time fraud detection system that autonomously identifies suspicious claim patterns in disaster insurance claims applications using anomaly detection, pattern recognition, and LLM-powered analysis.

Prerequisites

Required accounts & credentials:

• [](https://www.confluent.io/get-started/?utmcampaign=tm.pmmcd.q4fy25-quickstart-streaming-agents&utmsource=github&utmmedium=demo)
• LLM Provider: AWS Bedrock API keys OR Azure OpenAI keys - or BYOK

Required tools:

• Confluent CLI - must be logged in
• Docker - for Lab1 & Lab3 data generation only
• Git
• Terraform
• uv
• AWS CLI or Azure CLI tools for generating API keys

Installation commands (Mac/Windows) Mac:

brew install uv git python && brew tap hashicorp/tap && brew install hashicorp/tap/terraform && brew install --cask confluent-cli docker-desktop && brew install awscli # or azure-cli

Windows:

winget install astral-sh.uv Git.Git Docker.DockerDesktop Hashicorp.Terraform ConfluentInc.Confluent-CLI Python.Python

🚀 Quick Start

1. Clone the repository and navigate to the Quickstart directory:

git clone https://github.com/confluentinc/quickstart-streaming-agents.git
cd quickstart-streaming-agents

2. Auto-generate AWS Bedrock or Azure OpenAI keys:

# Creates API-KEYS-[AWS|AZURE].md and auto-populates them in next step
uv run api-keys create

1. One command deployment:

uv run deploy

That's it! The script will autofill generated credentials and guide you through setup and deployment of your chosen lab(s). > [!NOTE] > > See the [Workshop Mode Setup Guide](./assets/pre-setup/Workshop-Mode-Setup.md) for details about auto-generating API keys and tips for running demo workshops.

Directory Structure

quickstart-streaming-agents/
├── terraform/                          
│   ├── core/                           # Shared Confluent Cloud infra for all labs
│   ├── lab1-tool-calling/              # Lab1-specific infra
│   ├── lab2-vector-search/             # Lab2-specific infra
│   └── lab3-agentic-fleet-management/  # Lab3-specific infra
│   └── lab4-pubsec-fraud-agents        # Lab4-specific infra
├── deploy.py                           # Start here with uv run deploy
└── scripts/                            # Python utilities invoked with uv

Cleanup

# Automated
uv run destroy

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Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: confluentinc
• Source: confluentinc/quickstart-streaming-agents
• License: Apache-2.0
• Homepage: https://confluent.io/product/streaming-agents/

Install and usage instructions live in the source repository linked above.