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<!--Delete sections as needed --> ## Description rename GH cagent repo URL, repo has been renamed to docker/docker-agent ## Reviews <!-- Notes for reviewers here --> <!-- List applicable reviews (optionally @tag reviewers) --> - [ ] Technical review - [ ] Editorial review - [ ] Product review --------- Signed-off-by: Guillaume Tardif <guillaume.tardif@gmail.com>
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| Lab: Getting Started with Docker Agent | Lab: Getting Started with Docker Agent | Build intelligent multi-agent teams with Docker Agent and Docker in this hands-on interactive lab. | Hands-on lab: Create, share, and orchestrate intelligent AI agents using Docker Agent, MCP Toolkit, and Docker. | AI, Docker, docker agent, agents, multi-agent, MCP Toolkit, lab, labspace |
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This lab walks you through building intelligent agents with Docker Agent. You'll learn beginner agent concepts, then build sophisticated multi-agent teams that handle complex real-world tasks. Learn how to create, share, and orchestrate AI agents with Docker.
What you'll learn
- Create simple agents with Docker Agent
- Use built-in generic agentic tools for common tasks
- Integrate MCP servers from the MCP Toolkit
- Share agents using the Docker Registry
- Build multi-agent systems for complex workflows
- Use Docker Model Runner with Docker Agent (preview)
Modules
| # | Module | Description |
|---|---|---|
| 1 | Introduction | Overview of Docker Agent and intelligent agent concepts |
| 2 | Getting Started | Create your first agent with Docker Agent |
| 3 | Using Built-in Tools | Leverage the generic agentic tools in Docker Agent |
| 4 | Using MCP | Integrate MCP servers from the MCP Toolkit |
| 5 | Sharing Agents | Package and share agents via Docker Registry |
| 6 | Introduction to Sub-agents | Build multi-agent systems with sub-agent orchestration |
| 7 | Conclusion | Summary and next steps |
Prerequisites
- Latest version of Docker Desktop
- Basic familiarity with Docker
Launch the lab
Start the labspace:
$ docker compose -f oci://dockersamples/labspace-cagent up -d
Then open your browser to http://localhost:3030.