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adk-python
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adk-python

Active·★ 21.8k·Apache-2.0·Updated 2026-10-08
★ Most Popular★ Trending★ Essential

Agent Development Kit (ADK) is Google's open-source, code-first framework for building, evaluating and deploying AI agents. It applies ordinary software engineering practices to agents: you define agents, tools and orchestration in Python, test them, version them and deploy them like any other service. ADK is optimised for Gemini but is model-agnostic and deployment-agnostic, and it is also available for Java, Kotlin, Go and TypeScript.

Version 2.0 adds a graph-based workflow runtime for deterministic flows with routing, fan-out and fan-in, loops, retries, state and human-in-the-loop steps, plus a Task API for structured delegation between agents. You can compose specialised agents into hierarchies, give them pre-built tools, custom functions, OpenAPI specs or MCP tools, guard sensitive tools with explicit confirmation, and even define agents without code through Agent Config. A built-in web UI (`adk web`) helps you test, debug and evaluate agents, and deployment targets include Cloud Run and Vertex AI Agent Engine.

Getting started: requires Python 3.11+. Install with `pip install google-adk` (Google recommends its constraints files for dependency safety), create an agent, then run `adk web` to try it in the browser.

#AI Agents#Python#Framework#Multi-Agent Systems#Agent Development#Coding
$ Install
$ pip install google-adk
↗ Visit site★ GitHub
01

Features

01Rich Tool Ecosystem
02Code-First Development
03Agent Config
04Modular Multi-Agent Systems
05Deploy Anywhere
02

Why choose it

+Code-first design that fits normal testing, versioning and CI practices.
+Graph workflows, a Task API and multi-agent hierarchies cover both deterministic and autonomous patterns.
+Built-in dev UI and evaluation tooling.
+Available in five languages, model-agnostic, and Apache-2.0 licensed.
03

Trade-offs

!The deployment story and many integrations lean towards Google Cloud (Cloud Run, Vertex AI Agent Engine).
!Version 2.0 introduces new concepts, so older 1.x tutorials may need adjusting.
!Dependency management needs care; Google recommends installing with its constraints files.
04

Compatibility

Gemini
Optimized
Verified via docs
Vertex AI Agent Engine
Supported
Verified via docs
Cloud Run
Supported
Verified via docs
A2A Protocol
Integrated
Verified via docs
Any LLM
Model Agnostic
Verified via docs
Any Deployment Platform
Deployment Agnostic
Verified via docs
05

Quick start

1
$ pip install google-adk
06

Use cases

↳Building and deploying sophisticated AI agents from simple tasks to complex systems.
↳Orchestrating complex agent workflows with flexibility and control.
↳Designing and implementing scalable modular multi-agent systems.
07

How it compares

≈vs Microsoft Agent Framework: both target production agents with graph workflows; Agent Framework centres on .NET and Python with Azure hosting, ADK on Python and four other languages with Google Cloud deployment.
≈vs Pydantic AI: Pydantic AI focuses on a typed agent loop and structured output; ADK provides a broader toolkit including a workflow runtime, dev UI and evaluation.
≈vs CrewAI: CrewAI is built around role-based crews; ADK offers lower-level building blocks and tighter Google ecosystem integration.
08

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On this page
01Features02Why choose it03Trade-offs04Compatibility05Quick start06Use cases07How it compares08Alternatives
Stats
GitHub Stars★ 21.8k
Last commit1d ago
StatusActive
LicenseApache-2.0
CategoryMulti-Agent
Trend (30d)
+0.8k↑ 4.8%
Links
Documentation↗Discussion↗Issues↗Releases↗

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