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google/adk-python

📈 Trending19,705PythonAudience · developerComplexity · 4/5ActiveLicenseSetup · moderate

TLDR

Python framework for building AI agents that can break down goals into steps, use tools like web search, and work autonomously toward completing tasks.

Mindmap

mindmap
  root((repo))
    What it does
      AI agent builder
      Multi-step planning
      Tool integration
      Agent coordination
    Key features
      Code-first approach
      Built-in debug UI
      CLI evaluation tool
      Cloud deployment
    Use cases
      Research assistants
      Customer service bots
      Code execution pipelines
      Autonomous workflows
    Tech stack
      Python
      Gemini models
      Google Cloud
    Audience
      AI developers
      Backend engineers

Things people build with this

USE CASE 1

Build an automated research assistant that searches the web, reads articles, and synthesizes findings into reports.

USE CASE 2

Create a customer service bot that handles multi-step support requests by routing to specialist agents.

USE CASE 3

Deploy a code-execution pipeline where an AI agent writes, tests, and debugs code autonomously.

USE CASE 4

Set up a multi-agent system where coordinator agents delegate tasks to specialized sub-agents.

Tech stack

PythonGeminiGoogle CloudA2A protocol

Getting it running

Difficulty · moderate Time to first run · 30min

Requires Google Cloud credentials and Gemini API key setup.

Use freely for any purpose including commercial. Keep the notice and disclose changes to the patent grant.

In plain English

Google's Agent Development Kit (ADK) is a Python framework for building AI agents, programs that can receive a goal, break it into steps, use tools like web search or code execution, and work toward completing that goal autonomously. The problem it addresses is that creating capable AI agents is complex: you need to coordinate between AI models, define what tools they can use, handle multi-step conversations, and manage how multiple agents hand off tasks to each other. ADK takes a code-first approach, meaning you define your agent's behavior directly in Python rather than through a visual interface or configuration wizard. A single agent is defined by pointing to an AI model (it works well with Google's Gemini models but is model-agnostic), giving it instructions, and attaching tools it can call, like a web search function. Multi-agent systems go further: you can create a coordinator agent with specialist sub-agents nested inside it, and the framework handles routing tasks to the right agent automatically. It also ships with a built-in development UI for testing and debugging agent behavior, a command-line tool for running evaluations against test sets, and supports deployment to Google Cloud's infrastructure. It can also participate in agent-to-agent communication with other services via the A2A protocol. ADK is installed via pip and is suited for developers who want to build sophisticated AI workflows, automated research assistants, customer service bots, code-execution pipelines, or any task that benefits from an AI that can plan and act over multiple steps.

Copy-paste prompts

Prompt 1
Show me how to create a simple agent in ADK that can search the web and summarize results.
Prompt 2
How do I set up a multi-agent system in ADK where a coordinator delegates tasks to specialist agents?
Prompt 3
Walk me through using ADK's built-in UI to test and debug an agent's behavior before deployment.
Prompt 4
How can I deploy an ADK agent to Google Cloud and enable it to communicate with other services?
Prompt 5
Create an example of an ADK agent that executes code and iterates based on test results.
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Generated 2026-05-18 · Model: sonnet-4-6 · Verify against the repo before relying on details.