Agent Development Kit (ADK)

One-Minute Overview#

ADK is a flexible and modular framework that applies software development principles to AI agent creation. It is designed to simplify building, deploying, and orchestrating agent workflows, from simple tasks to complex systems. While optimized for Gemini, ADK is model-agnostic, deployment-agnostic, and compatible with other frameworks.

Core Value: Provides ultimate flexibility and control through code-first development, enabling developers to build, evaluate, and deploy sophisticated AI agent systems.

Quick Start#

Installation Difficulty: Medium - Requires basic Python knowledge and understanding of AI/LLM concepts, with simple pip installation available

# Stable Release (Recommended)
pip install google-adk

# Development Version
pip install git+https://github.com/google/adk-python.git@main

Is this suitable for me?

• ✅ Building complex AI systems: Need to build multi-agent systems where each agent specializes in specific tasks
• ✅ Need flexibility and control: Want to define agent logic, tools, and orchestration directly through code
• ✅ Google ecosystem integration: Require deep integration with Google services and Gemini models
• ❌ Simple task automation: For simple single-task agents, ADK might be overly complex

Core Capabilities#

1. Rich Tool Ecosystem - Solving Limited Capabilities#

• Utilize pre-built tools, custom functions, OpenAPI specs, MCP tools or integrate existing tools to give agents diverse capabilities Actual Value: No need to build features from scratch, quickly extend agent capabilities, especially with tight integration with Google ecosystem

2. Code-First Development - Solving Rigidity Issues#

• Define agent logic, tools, and orchestration directly in Python for ultimate flexibility, testability, and versioning Actual Value: Familiar programming approach for developers, enabling version control, testing, and integration into existing workflows

3. Agent Config Feature - Solving No-Code Needs#

• Build agents without code through the Agent Config feature Actual Value: Allows non-programmers to participate in agent design, accelerating prototyping and simple agent development

4. Tool Confirmation Flow - Solving Execution Safety Issues#

• A tool confirmation flow (HITL) that can guard tool execution with explicit confirmation and custom input Actual Value: Enhances safety of AI agent operations, especially with human supervision for sensitive operations

5. Modular Multi-Agent Systems - Solving Scalability Issues#

• Design scalable applications by composing multiple specialized agents into flexible hierarchies Actual Value: Enables building complex AI systems where different agents focus on different tasks and work collaboratively

Technology Stack & Integration#

Development Language: Python Main Dependencies: Google Cloud services, Vertex AI, FastAPI Integration Method: SDK/Library

Ecosystem & Extension#

• Plugins/Extensions: Has an adk-python-community repository with community-contributed tools, third-party service integrations, and deployment scripts
• Integration Capability: Supports A2A protocol integration for remote agent-to-agent communication, can work with various models and services

Maintenance Status#

• Development Activity: Actively maintained with a bi-weekly release cycle for stable versions
• Recent Updates: Recently added custom service registration, session rewind functionality, and new code executor
• Community Response: Active community including Reddit community group and regular community meetings

Commercial & Licensing#

License: Apache 2.0

• ✅ Commercial Use: Allowed
• ✅ Modification: Allowed
• ⚠️ Restrictions: Requires inclusion of copyright and license notice

Documentation & Learning Resources#

• Documentation Quality: Comprehensive
• Official Documentation: Available with complete guides
• Example Code: Rich examples provided, including single agent and multi-agent system definitions
• Development UI: Built-in development UI to help test, evaluate, debug, and showcase agents