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ck:google-adk-python

Develop and deploy AI agents with Google ADK Python.

1|Updated Jun 16, 2026
Search Tags:#ai agent#google cloud#multi-agent system#google adk#vertex ai
One-click install
npx skills add https://github.com/TNHoang2708/Gym_Ver2 --skill ck-google-adk-python-tnhoang2708
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ck:google-adk-python
Source: https://github.com/TNHoang2708/Gym_Ver2/tree/main/.claude/skills/google-adk-python
Command: npx skills add https://github.com/TNHoang2708/Gym_Ver2 --skill ck-google-adk-python-tnhoang2708

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires google-adk, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill solves the problem of building, evaluating, and deploying AI agents, specifically for Google's Agent Development Kit (ADK) Python.

Core Features & Use Cases

  • Agent Development: Facilitates the creation of AI agents with various functionalities like multi-agent systems, A2A protocol, MCP tools, and Vertex AI deployment.
  • Workflow Management: Offers the ability to manage and orchestrate complex workflows for AI agents.
  • Evaluation and Deployment: Enables the evaluation of AI agents and their deployment on Google Cloud Run, Vertex AI Agent Engine, or GKE.

Quick Start

Install the google-adk package and create an agent using the following command:

pip install google-adk
uv sync --all-extras

Example agent creation in Python:

from google.adk import Agent

root_agent = Agent(
    name="assistant",
    model="gemini-2.5-flash",
    instruction="You are a helpful assistant.",
    description="General assistant agent.",
    tools=[get_weather],
)

Frequently Asked Questions about ck:google-adk-python

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

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

To build multi-agent systems with Google ADK Python, use the Agent class to define root agents and orchestrate complex workflows. You can configure models like Gemini, set instructions, and attach tools to create functional AI agents for Google Cloud Platform.

Can I deploy AI agents to Vertex AI Agent Engine using Google ADK?▼

Yes, you can deploy AI agents to Vertex AI Agent Engine using Google ADK. The framework supports deployment to Google Cloud Run, Vertex AI Agent Engine, and GKE, enabling scalable evaluation and execution of your multi-agent systems.

What is the best way to integrate MCP tools into a Google ADK agent?▼

The best way to integrate MCP tools into a Google ADK agent is by passing the tool functions directly into the Agent constructor's tools parameter. This allows your AI agent to execute custom logic and interact with external systems during its workflow.

Does Google ADK Python support the A2A protocol for agent communication?▼

Yes, Google ADK Python supports the A2A protocol for agent communication. This allows you to build and manage complex multi-agent systems where agents interact and orchestrate workflows with each other on Google Cloud Platform.

What do I need to set up before developing AI agents with Google ADK?▼

Before developing AI agents with Google ADK, you need a Python environment with the google-adk package installed. You also need access to Google Cloud Platform for Vertex AI deployment and model access, such as Gemini.

Are there limitations when orchestrating complex workflows with Google ADK Python?▼

Orchestrating complex workflows with Google ADK Python requires careful management of multi-agent systems and MCP tools. Limitations may arise from Vertex AI model quotas and the complexity of maintaining A2A protocol communication across large deployments.

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