Streaming Agents on Confluent Cloud Quickstart

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.

Prerequisites

Required accounts & credentials:

• 
• LLM Provider: AWS Bedrock API keys OR Azure OpenAI keys - or BYOK
• Lab1 & Lab3: Zapier remote MCP server (Setup guide)

Note: SSE endpoints are now deprecated by Zapier. If you previously created an SSE endpoint, you'll need to create a new Streamable HTTP endpoint and copy the Zapier token instead. See the Zapier Setup guide for updated instructions.

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

3. 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 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
├── deploy.py                           # Start here with uv run deploy
└── scripts/                            # Python utilities invoked with uv

[NEW!] Streamlined architecture:

• No heavyweight AWS/Azure Terraform providers needed - just LLM API keys generated with one command
• MongoDB is now pre-configured: No need to set up your own MongoDB Atlas cluster anymore - we provide MongoDB endpoints with read-only credentials, pre-populated with vectorized documents so you can get started faster

Cleanup

# Automated
uv run destroy

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