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google-adk-python

Build, evaluate, and deploy AI agents with Google ADK Python.

Updated Mar 19, 2026
Search Tags:#python#ai#multi-agent#mcp#adk#a2a#vertex-ai
One-click install
npx skills add https://github.com/congthang12312/Sentinel-AI-test --skill google-adk-python-congthang12312
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: google-adk-python
Source: https://github.com/congthang12312/Sentinel-AI-test/tree/main/.agent/skills/google-adk-python
Command: npx skills add https://github.com/congthang12312/Sentinel-AI-test --skill google-adk-python-congthang12312

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Builds, tests, and deploys AI agents using Google's ADK Python to streamline multi-agent workflows.

Core Features & Use Cases

  • Multi-agent systems with A2A protocol
  • MCP tool integration and workflow orchestration
  • State, memory, and artifact management for persistent context
  • Vertex AI deployment and evaluation support

Quick Start

Install the google-adk-python package and follow the samples to bootstrap a simple agent.

Frequently Asked Questions about google-adk-python

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build and deploy multi-agent systems with Google ADK Python?▼

You can build and deploy multi-agent systems with Google ADK Python by using its built-in samples to bootstrap agents, orchestrate workflows, and deploy directly to Vertex AI or GKE.

Can I integrate MCP tools into AI agents using Google ADK Python?▼

Yes, Google ADK Python supports MCP tool integration, allowing you to connect external tools and orchestrate complex workflows within your multi-agent systems for research or production contexts.

Does Google ADK Python support state and memory management for persistent context?▼

Google ADK Python includes built-in state, memory, and artifact management features to maintain persistent context across multi-agent workflows during complex task execution.

How do I evaluate AI agents deployed to Vertex AI using Google ADK Python?▼

Google ADK Python provides native evaluation support for AI agents deployed to Vertex AI, allowing you to assess multi-agent workflows and tool integration performance in production environments.

What is the best way to structure Python packages for multi-agent systems using A2A protocol?▼

The best way to structure Python packages for A2A multi-agent systems is to follow ADK agent structure standards, ensuring proper packaging and supporting references for callbacks and tool integration.

Do I need Python packaging knowledge to use Google ADK Python for AI agent development?▼

Yes, you need basic Python packaging knowledge because ADK requires adhering to agent structure standards and packaging prerequisites to successfully build and deploy multi-agent workflows.

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