Google Agent Development Kit

Google Agent Development Kit (ADK) is an open-source framework for building, evaluating, and deploying AI agents. It is best suited to developers who want to define agent behavior in code and choose among multiple languages, models, and deployment environments. Its range is compelling, but Agent Config has narrower model and language support than the wider framework.

Overview

ADK combines explicit, graph-based workflows with adaptive AI reasoning, so developers can set deterministic steps without giving up model-led decisions. Agents can also be arranged in hierarchies and delegate work to specialized agents. This makes ADK a strong fit for applications with distinct tasks or controlled workflows; it is less compelling for someone seeking a ready-made agent product rather than a framework to build with.

The framework supports Gemini, adapters for other model providers, and locally running models. Its integrations catalog covers MCP, Google Cloud, databases, search, observability, and third-party services. That breadth can help teams connect agents to existing systems, but Agent Config currently supports only Gemini and requires Python. Teams using another model or language should not assume that feature shares ADK’s broader compatibility.

Key features

ADK spans building, debugging, evaluation, and deployment. Developers can create multi-turn evaluation datasets and run evaluations locally through the CLI or development UI. Evaluating exchanges across multiple turns is useful when an agent’s behavior depends on context, rather than only on its response to a single prompt.

Live agents support bidirectional text and audio streaming, while session context management and integration points for longer-term memory services support conversations that need continuity. ADK also includes a visual agent builder, knowledge grounding, and human handoff. These capabilities broaden its use beyond code-defined workflows, though the framework’s central advantage remains the control it gives developers over how agents are built.

Deployment options include Google Cloud Agent Runtime, Cloud Run, GKE, other container-friendly infrastructure, and local Docker or Podman environments. This range suits teams with different hosting needs. Security guidance addresses identity and authorization, input and output guardrails, sandboxed code execution, and network controls; it gives developers areas to consider when designing an agent, rather than removing the need to implement appropriate protections.

Installation instructions cover Python, TypeScript, Go, Java, and Kotlin. Community resources are available, but Google and the ADK team do not support the content in external community resources, so teams should account for that boundary when relying on community help.

Pricing

ADK is open source and its free plan costs nothing. There is no paid framework tier described. Free access to the framework does not mean every deployment is cost-free: model use or cloud services may require separate access or billing.

This pricing suits developers who want to build without paying for the framework itself, including teams evaluating or self-hosting agents. The trade-off is that costs tied to chosen models and infrastructure sit outside that free framework price.

Platforms

ADK supports API, Linux, macOS, Windows, web, and self-hosted use. Combined with its language options and container-friendly deployment paths, that makes it adaptable to varied development and hosting setups. The practical fit still depends on the chosen model and services, and Agent Config’s Python requirement is a notable exception to the wider language support.

Who it's for

ADK is a good choice for developers and teams building agents that need structured workflows, delegated tasks, evaluation, voice interaction, or control over deployment. It is particularly suitable when model and infrastructure flexibility matter, and the team can work directly with a framework. It is a poorer fit for users who want an out-of-the-box agent experience or depend on Agent Config with a non-Gemini model or a language other than Python.

Pros and cons

• Pros: Five supported languages and adapters for other providers, including locally running models, give teams options beyond Gemini.
• Pros: Multi-agent hierarchies, graph workflows, and local multi-turn evaluation support both structured development and iterative assessment.
• Pros: Multiple deployment targets, including local containers and Google Cloud services, let teams choose where agents run.
• Cons: Agent Config is limited to Gemini and Python, constraining teams that would otherwise benefit from the framework’s broader model and language support.
• Cons: Free framework access does not cover potentially separate model or cloud service charges.
• Cons: Google and the ADK team do not support content in external community resources, which may matter to teams depending on community help.

Alternatives

For a broader selection, browse AI Agent Platforms.

Microsoft Copilot is a freemium option with a free plan and web, desktop, and mobile platforms; consider it when you want a user-facing product rather than a developer framework.

Vellum offers a free plan and a $30 a month Mighty plan; consider it if you prefer a freemium alternative with a defined paid tier.

Camunda offers a free self-managed development plan for local development and testing, as well as a free trial; consider it when that self-managed development path is the priority.

Flowise has a free plan capped at two flows and assistants, 100 predictions per month, and 5MB storage; consider it when a defined free usage allowance suits your needs.

Houston has a free personal workspace for up to three people, with limited usage and more than 1,000 integrations; consider it when a small team wants that integration range.

Retool offers a free plan and a Team plan priced at $10 a month per builder and $5 a month per internal user; consider it when that builder-and-user pricing model fits your team.

SmythOS has a free plan for one seat and a Builder plan at $39 a month with 100 fast API calls per day; consider it when those published plan limits match your expected use.

Agentforce Vibes offers a free option through Salesforce Foundations; consider it if you want to explore that alternative.

Verdict

Choose ADK if you are a developer who wants a free, code-oriented framework with broad language, workflow, evaluation, and deployment support. Its strongest reason to choose it is the ability to shape and assess agents across varied models and hosting environments; its main reason to look elsewhere is the Agent Config restriction, alongside separate potential model and cloud costs.