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The AI Agent Tools Directory — Built for Builders. Discover, compare, and choose the best AI agent tools and builder resources.

  1. Home
  2. Tools
  3. Google Agent Development Kit (ADK)
AI Agent Builders🔴Developer
G

Google Agent Development Kit (ADK)

Google's open-source framework for building, evaluating, and deploying multi-agent AI systems with Gemini and other LLMs.

Starting atFree
Visit Google Agent Development Kit (ADK) →
💡

In Plain English

Google's toolkit for building AI agents that can use Google's AI models, tools, and services.

OverviewFeaturesPricingUse CasesLimitationsFAQSecurityAlternatives

Overview

Google Agent Development Kit (ADK) is an open-source framework designed to simplify the development of AI agents and multi-agent systems. Built by Google's DeepMind and Cloud teams, ADK provides a flexible and modular architecture that lets developers build agents powered by Gemini models or any LLM through LiteLLM integration. The framework emphasizes composability — agents can be combined into teams, pipelines, and hierarchies to tackle complex multi-step tasks.

ADK includes a rich set of built-in tools for Google Search, code execution, function calling, and RAG retrieval, plus seamless integration with MCP (Model Context Protocol) servers for extending agent capabilities. The framework provides structured agent types including LLM-powered agents, workflow agents (sequential and parallel), and custom agents, allowing developers to mix and match patterns.

A standout feature is ADK's built-in evaluation system that lets you test agent performance with metrics for trajectory accuracy, tool usage, and response quality. The development experience includes a local web UI for debugging agent interactions in real time, making it easier to understand and improve agent behavior.

ADK deploys natively to Google Cloud's Vertex AI Agent Engine for production workloads, but supports containerized deployment anywhere via Cloud Run. Session state management and memory persistence are handled through pluggable backends. The framework is production-tested at Google scale and represents Google's answer to frameworks like LangChain and CrewAI.

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Key Features

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Build hierarchical agent teams with sequential, parallel, and loop-based workflows. Agents can delegate to sub-agents and coordinate complex tasks.

Use Case:

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Test agent performance with trajectory accuracy, tool usage metrics, and response quality scoring — critical for production-grade agent development.

Use Case:

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Natively supports Model Context Protocol servers, allowing agents to use any MCP-compatible tool without custom integration code.

Use Case:

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Ships with a web-based debugging interface for testing agent interactions, inspecting tool calls, and understanding agent decision-making in real time.

Use Case:

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Optimized for Gemini but works with any LLM through LiteLLM, including Claude, GPT-4, and open-source models via Ollama.

Use Case:

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Deploy directly to Google Cloud's Vertex AI Agent Engine with managed scaling, security, and monitoring — or containerize for any environment.

Use Case:

Pricing Plans

Free

Free

forever

  • ✓All features
  • ✓API access
  • ✓Community support

Ready to get started with Google Agent Development Kit (ADK)?

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Best Use Cases

🎯

Building multi-agent systems

Building multi-agent systems with Gemini models

⚡

Teams needing built-in evaluation for agent quality

Teams needing built-in evaluation for agent quality

🔧

Google Cloud-native agent deployments

Google Cloud-native agent deployments

🚀

Rapid prototyping with local debugging UI

Rapid prototyping with local debugging UI

Limitations & What It Can't Do

We believe in transparent reviews. Here's what Google Agent Development Kit (ADK) doesn't handle well:

  • ⚠Python-only SDK
  • ⚠Gemini-optimized features don't all transfer to other models
  • ⚠Vertex AI deployment adds cloud costs
  • ⚠Multi-agent debugging can be complex

Pros & Cons

✓ Pros

  • ✓First-party Google support with Gemini optimization
  • ✓Excellent built-in evaluation and testing tools
  • ✓Native MCP protocol support
  • ✓Local web UI for development and debugging
  • ✓Production-tested at Google scale

✗ Cons

  • ✗Best experience tied to Google Cloud ecosystem
  • ✗Newer than LangChain — smaller third-party ecosystem
  • ✗Python-only currently
  • ✗Gemini-optimized features may not work with all models

Frequently Asked Questions

How does Google ADK compare to LangChain?+

ADK is more opinionated with built-in eval, local UI, and structured agent types, while LangChain is more flexible but requires more assembly. ADK has native MCP support and Google Cloud integration.

Can I use ADK with non-Google models?+

Yes. ADK supports any LLM through LiteLLM integration, including Anthropic Claude, OpenAI GPT-4, and open-source models. Some Gemini-specific features may not be available.

Does ADK require Google Cloud?+

No. ADK runs locally for development and can be containerized for any deployment target. Vertex AI integration is optional but provides managed hosting.

What is the Agent Engine in Vertex AI?+

Agent Engine is Google Cloud's managed service for deploying ADK agents at scale with built-in monitoring, auto-scaling, and enterprise security features.

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Comparing Options?

See how Google Agent Development Kit (ADK) compares to CrewAI and other alternatives

View Full Comparison →

Alternatives to Google Agent Development Kit (ADK)

CrewAI

AI Agent Builders

CrewAI is an open-source Python framework for orchestrating autonomous AI agents that collaborate as a team to accomplish complex tasks. You define agents with specific roles, goals, and tools, then organize them into crews with defined workflows. Agents can delegate work to each other, share context, and execute multi-step processes like market research, content creation, or data analysis. CrewAI supports sequential and parallel task execution, integrates with popular LLMs, and provides memory systems for agent learning. It's one of the most popular multi-agent frameworks with a large community and extensive documentation.

LangGraph

AI Agent Builders

Graph-based stateful orchestration runtime for agent loops.

AutoGen

Multi-Agent Builders

Open-source framework for creating multi-agent AI systems where multiple AI agents collaborate to solve complex problems through structured conversations, role-based interactions, and autonomous task execution.

Strands Agents

AI Agent Builders

AWS open-source SDK for building AI agents in Python with model-driven tool orchestration and built-in conversation memory.

OpenAI Agents SDK

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Official OpenAI SDK for building production-ready AI agents with GPT models and function calling.

View All Alternatives & Detailed Comparison →

User Reviews

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Quick Info

Category

AI Agent Builders

Website

google.github.io/adk-docs/
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