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Google ADK

Build and deploy multi-agent systems with a modular SDK

Agent Development Kit (ADK) is a framework for developers building AI agents and multi-agent workflows. It supports Python, TypeScript, Go, and Java, and is designed to run across different models and deployment setups.

API
Integrations
Multi-Agent
B2B
For Developers
Hybrid
Model Agnostic
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About

What It Is

Agent Development Kit (ADK) is a developer framework for building, orchestrating, and deploying AI agents. It is aimed at software teams and developers who want to create agentic systems that can range from simple workflows to more complex multi-agent architectures.

What to Know

ADK appears strongest as an engineering framework rather than a consumer-facing agent app. It is built for structured orchestration, tool use, evaluation, and deployment, which makes it useful if you are assembling production agents with external...

Key Features
Multi-agent workflow orchestration with sequential, parallel, and loop agents
LLM-driven dynamic routing via agent transfer
Python, TypeScript, Go, and Java support
Tool integration for search, code execution, custom functions, and third-party libraries
Can use other agents as tools
Use Cases
Building production multi-agent systems for software products
Creating agent workflows that combine tools, APIs, and custom code
Deploying orchestrated agents in cloud or containerized environments
Agenticness: Adaptive Collaborator

Proposes and executes multi-step plans with your approval.

High evidence
Last evaluated: Apr 3, 2026
This tool has strong action capabilities but limited safety controls. Use with appropriate oversight.

Dimension Breakdown

Action Capability
Autonomy
Adaptation
State & Memory
Safety

Categories

Pricing
  • Pricing not publicly available: No pricing details were found on the crawled page.
Details
AddedApril 3, 2026
RefreshedApril 3, 2026
Quick Facts
DeploymentHybrid (cloud + self-hosted)
AutonomySemi-autonomous
Model supportMulti-model
Team supportSmall team
Pricing modelSubscription
Interfaceapi
Sources

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Open Source
API
Memory
+3

Documentation for the Xet content-addressed storage protocol and its reference implementations. It is aimed at developers building clients or tools that upload and download data from Hugging Face Hub using Xet.

MetaGPT assigns different roles to LLMs to simulate a software team. It can turn a short requirement into artifacts like user stories, requirements, APIs, and code repositories.

Chrome Extension
Code Execution
File Access
+5

ElizaOS is an open-source platform for building, deploying, and managing AI agents. It includes a CLI, web UI, and plugin-based architecture so you can run agents locally and extend them with integrations and custom logic.

Integrations
Multi-Agent
B2B
+4
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