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title	ADK Python Tutorial
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ADK Python Tutorial: Production-Grade Agent Engineering with Google's ADK

Learn how to use google/adk-python to build, evaluate, and deploy modular AI agent systems with strong tooling, session controls, and production rollouts.

Why This Track Matters

ADK is one of the most complete open-source agent frameworks for teams that need code-first flexibility plus disciplined operations.

This track focuses on:

• shipping your first ADK agent quickly
• designing multi-agent systems with predictable runner behavior
• integrating tools, MCP, and confirmation gates safely
• evaluating and deploying ADK projects in production settings

Current Snapshot (auto-updated)

• repository: google/adk-python
• stars: about 21.3k
• GitHub release reference: v2.8.0 (checked 2026-08-31; release metadata on GitHub)

Mental Model

flowchart LR
    A[User Goal] --> B[ADK Agent Graph]
    B --> C[Runner Invocation Lifecycle]
    C --> D[Tools and MCP Calls]
    D --> E[Session and Memory Services]
    E --> F[Evaluation and Deployment]

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Chapter Guide

Chapter	Key Question	Outcome
01 - Getting Started	How do I install ADK and run my first agent quickly?	Working baseline
02 - Architecture and Runner Lifecycle	How does ADK execute invocations and persist state?	Reliable mental model
03 - Agent Design and Multi-Agent Composition	How do I structure scalable agent systems?	Strong composition patterns
04 - Tools, MCP, and Confirmation Flows	How do I add external capabilities safely?	Safe integration baseline
05 - Sessions, Memory, and Context Management	How do I manage short-term and long-term context?	Better state design
06 - Evaluation, Debugging, and Quality Gates	How do I measure agent quality and catch regressions?	Evaluation workflow
07 - Deployment and Production Operations	How do I ship ADK agents to production?	Production rollout plan
08 - Contribution Workflow and Ecosystem Strategy	How do I contribute and extend ADK responsibly?	Contributor readiness

What You Will Learn

• how to design ADK agent projects from local dev to production
• how to build reliable tool/MCP workflows with confirmation controls
• how to run evaluation loops and enforce quality gates
• how to align with ADK's contribution and ecosystem patterns

Source References

• ADK Repository
• ADK README
• ADK Documentation
• ADK Quickstart
• ADK Contributing Guide
• ADK Samples

Related Tutorials

• Mastra Tutorial
• Agno Tutorial
• MCP Servers Tutorial
• AutoGen Tutorial

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Start with Chapter 1: Getting Started.

Navigation & Backlinks

• Start Here: Chapter 1: Getting Started
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Full Chapter Map

1. Chapter 1: Getting Started
2. Chapter 2: Architecture and Runner Lifecycle
3. Chapter 3: Agent Design and Multi-Agent Composition
4. Chapter 4: Tools, MCP, and Confirmation Flows
5. Chapter 5: Sessions, Memory, and Context Management
6. Chapter 6: Evaluation, Debugging, and Quality Gates
7. Chapter 7: Deployment and Production Operations
8. Chapter 8: Contribution Workflow and Ecosystem Strategy

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