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Agent Development Kit (ADK)

FreeAPISelf-HostedAgentic

Summary

Google's code-first framework for building multi-agent systems with structured context management and deep Vertex AI integration.

ADK treats agent development like software engineering: sessions, memory, and tool outputs are versioned and assembled as code artifacts, making them compatible with standard CI/CD pipelines and Git workflows. It's built for teams deploying to Google Cloud infrastructure who need precise control over agent behavior rather than abstraction layers. The framework costs nothing and handles automatic filtering of irrelevant events to reduce noise in multi-agent interactions. The main catch is that while technically model-agnostic, ADK is optimized for Gemini models and Google Cloud deployment; development builds may include experimental features from trunk code.

Bottom line: *Choose this if your team lives in Google Cloud and values code-driven reproducibility; avoid if you need multi-cloud portability or prefer configuration-over-code patterns.*

Pricing Plans

Free
Free Tier
No limits; open-source software can be freely deployed anywhere

Open Source

Free

Self-hosted open-source framework with no licensing costs

  • Python, TypeScript, Go, and Java support
  • Multi-agent system orchestration
  • Built-in development UI and evaluation tools
  • Code-first agent development
  • Model-agnostic architecture
  • Community support and contributions

View full pricing on google.github.io →

Pricing may have changed since last verified. Check the official site for current plans.

Community Performance Report Card

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Best For: Developers building production-grade multi-agent systems with precise control, Teams needing code-first agent development with version control and CI/CD integration, Organizations deploying to Google Cloud infrastructure (Vertex AI, Cloud Run, GKE), Projects requiring model flexibility with support for Gemini, Anthropic, Meta, and other models, Applications combining multiple specialized agents in hierarchical workflows

Community Benchmarks Community

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  • Context is treated like source code with structured assembly of sessions, memory, tool outputs, and artifacts, automatic filtering of irrelevant events, summarization of older turns, lazy-loading of artifacts, and token usage tracking to keep agents fast, efficient, and reliable by default
  • Multi-language support with Python, TypeScript, Go, and Java implementations
  • Model-agnostic and compatible with other frameworks while optimized for Gemini
  • Built-in development UI for testing, evaluating, debugging, and showcasing agents
  • When deploying to Google Cloud, agents inherit managed infrastructure, built-in authentication, Cloud Trace observability, and enterprise-grade security without code changes
  • Optimized primarily for Google Cloud deployment and Gemini models, though model-agnostic capabilities exist
  • Development version builds directly from latest code commits may contain experimental changes or bugs not present in stable release

Community Reviews

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About

Platforms
Python, TypeScript, Go, and Java
Languages
Python
API Available
Yes
Self-Hosted
Yes
Last Updated
2026-04-21T21:16:36.827Z

Best For

Who it's for

  • Developers building production-grade multi-agent systems with precise control
  • Teams needing code-first agent development with version control and CI/CD integration
  • Organizations deploying to Google Cloud infrastructure (Vertex AI, Cloud Run, GKE)
  • Projects requiring model flexibility with support for Gemini, Anthropic, Meta, and other models
  • Applications combining multiple specialized agents in hierarchical workflows

What it does well

  • Build intelligent agents using Large Language Models that understand natural language, reason, plan, generate responses, and dynamically decide how to proceed or which tools to use
  • Control execution flow of multiple agents in predefined patterns (sequence, parallel, or loop) for structured processes needing predictable execution
  • Accomplish complex, multi-step processes with a managed, repeatable task structure that can run hands-off with minimal human input, including automatic task initiation, iterative AI model requests, context management, tool calls, parallel jobs, and failure handling
  • Build multi-agent systems with hierarchical agent composition and delegation
  • Deploy AI agents to production with built-in observability, tracing, and enterprise-grade security

Integrations

Pre-built tools (SearchCode Execution)Model Context Protocol (MCP) tools3rd-party libraries (LangChainLlamaIndex)and other agents as tools (LangGraphCrewAI)

Discussion Community

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Frequently Asked Questions

Is Agent Development Kit (ADK) free?
Yes — Agent Development Kit (ADK) is fully free to use. There is no paid tier.
Is Agent Development Kit (ADK) open source?
No — Agent Development Kit (ADK) is a closed-source tool. Source code is not publicly available.
Does Agent Development Kit (ADK) have an API?
Yes. Agent Development Kit (ADK) exposes a developer API. See the official documentation at https://google.github.io for details.
Can I self-host Agent Development Kit (ADK)?
Yes. Agent Development Kit (ADK) supports self-hosting on your own infrastructure.
When was Agent Development Kit (ADK) released?
Agent Development Kit (ADK) was first released in 2025.
What platforms does Agent Development Kit (ADK) support?
Agent Development Kit (ADK) is available on: Python, TypeScript, Go, and Java.

Hours Saved & ROI Stories Community

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Agent Development Kit (ADK)