Google ADK alternatives: 5 agent frameworks compared
Updated By Agent Radar5 min read
Short answer
Google ADK alternatives compared: LangGraph, Pydantic AI, OpenAI Agents SDK, Microsoft Agent Framework and Mastra, with licenses and who each fits.
Top pick: LangGraph. MIT-licensed orchestration runtime for stateful, long-running agents built as explicit graphs with checkpoints.
Quick comparison
| Pick | License | Pricing | Source |
|---|---|---|---|
| 1.LangGraph | MIT | The library is MIT. LangChain sells hosted deployment and observability separately; no price is quoted here. | langchain-ai/langgraph on GitHub |
| 2.Pydantic AI | MIT | MIT library. You pay your model provider; Pydantic's Logfire observability is a separate product. | pydantic/pydantic-ai on GitHub |
| 3.OpenAI Agents SDK | MIT | The SDK is MIT. Model and hosted tool calls use OpenAI's standard token and tool pricing. | openai/openai-agents-python on GitHub |
| 4.Microsoft Agent Framework | MIT | MIT and free to install from PyPI or NuGet. You pay your model provider, or Azure if you host on Microsoft Foundry. | microsoft/agent-framework on GitHub |
| 5.Mastra | Apache-2.0 (ee/ directories under a separate license) | Most code is Apache-2.0; anything in ee/ directories is under Mastra's enterprise license. No price is quoted here. | mastra-ai/mastra on GitHub |
Most people looking for a Google ADK alternative want one of three things: less dependence on Gemini and Google Cloud, a different programming model (graphs or typed functions instead of ADK's agents and workflow nodes), or a framework in a language their product already uses. Each points to a different pick.
First: what ADK gives you today
adk-python is Apache-2.0. The v2.14.0 release, published November 7, 2026, made sandboxed execution environments (local, E2B, Daytona) and the A2A integration stable and added multi-run evaluation with adk eval --num_runs. Google also maintains ADK repositories for TypeScript, Go and Java. If built-in evals, sandboxes and a deployment path to Agent Engine are why you chose ADK, the alternatives below will make you assemble more of that yourself.
Pick by what you want to change
| You want | Start with | What you give up |
|---|---|---|
| Explicit, checkpointed agent state | LangGraph | ADK's built-in eval CLI and Agent Engine path |
| Typed, plain-Python agents | Pydantic AI | Built-in sandbox environments |
| A small SDK on OpenAI models | OpenAI Agents SDK | Gemini-first features such as live audio |
| .NET or the Azure stack | Microsoft Agent Framework | Google Cloud integrations |
| A TypeScript-native framework | Mastra | One license across every package |
The order is editorial, not a benchmark. We did not run speed or quality tests.
LangGraph: when you need control over state
LangGraph is MIT-licensed (langchain-ai/langgraph); the latest stable release we saw is 1.2.20, published November 5, 2026. You model the agent as a graph with checkpoints, which suits long-running agents that pause for human approval or resume after failure. For the detailed trade-offs, read LangGraph vs Google ADK.
Pydantic AI: typed Python, less framework
Pydantic AI is MIT-licensed and model-agnostic; v2.66.0 shipped November 4, 2026. It fits teams who want validated inputs and outputs and an agent that reads like ordinary Python. You give up ADK's stable sandbox environments and eval CLI. See Pydantic AI vs Google ADK.
OpenAI Agents SDK: the OpenAI-side equivalent
The OpenAI Agents SDK (openai/openai-agents-python) is MIT. Its latest stable tag is v0.24.0 from October 15, 2026; the November builds are alphas, which we skip. Pick it when your models and hosted tools already live on OpenAI. It is as tied to OpenAI as ADK is to Google, so it is a vendor swap rather than an escape from vendors.
Microsoft Agent Framework: Python and .NET
Microsoft Agent Framework is MIT and succeeds Semantic Kernel. It released dotnet-1.28.0 on November 6, 2026 and python-1.24.0 on October 30. Pick it when part of your team writes C# or you deploy on Microsoft Foundry.
Mastra: TypeScript first
Mastra is a TypeScript framework for agents and workflows; @mastra/core 1.82.0 shipped November 4, 2026. Most of the code is Apache-2.0, but anything under ee/ directories uses a separate enterprise license, so check the packages you import. If you want to stay with ADK in TypeScript, Google's adk-js is the other route.
Who should stay on ADK
Stay if you deploy on Google Cloud, use Gemini live audio, or rely on the eval tooling and sandbox environments that 2.14.0 just made stable. Do check the three breaking changes in that release before upgrading. Agno is another option in this space; we compared the two in adk-python vs Agno. If you are also weighing LangChain itself or the OpenAI SDK, see LangChain alternatives, OpenAI Agents alternatives and Pydantic AI vs LangGraph. More frameworks are in the Frameworks category.
Versions and licenses checked November 7, 2026 against GitHub. Releases move quickly, so verify the linked pages before you commit.
The picks
MIT-licensed orchestration runtime for stateful, long-running agents built as explicit graphs with checkpoints.
Pros
- Explicit graph state and checkpointing for agents that pause, resume and need human review.
- Model-agnostic, with no default tie to one cloud.
Cons
- More boilerplate than ADK for a simple single-agent tool loop.
- No built-in equivalent of ADK's Agent Engine deployment target on Google Cloud.
Pricing The library is MIT. LangChain sells hosted deployment and observability separately; no price is quoted here.
MIT-licensed, model-agnostic Python framework for typed agents, from the Pydantic team.
Pros
- Typed inputs, outputs and dependencies validated with Pydantic models.
- Plain Python feel with a small API surface.
Cons
- Fewer built-in deployment targets and sandbox environments than ADK 2.14.
- Graph-style multi-agent workflows take more of your own design.
Pricing MIT library. You pay your model provider; Pydantic's Logfire observability is a separate product.
OpenAI's MIT-licensed Python SDK for multi-agent workflows with handoffs, guardrails and tracing.
Pros
- Small API: agents, handoffs, guardrails and built-in tracing.
- Closest fit if your models and hosted tools are already on OpenAI.
Cons
- Most natural with OpenAI models, the mirror image of ADK's Gemini lean.
- Latest stable is v0.24.0 from October 15, 2026; newer builds are alphas.
Pricing The SDK is MIT. Model and hosted tool calls use OpenAI's standard token and tool pricing.
MIT-licensed Python and .NET framework for agents and multi-agent workflows, the successor to Semantic Kernel.
Pros
- First-class .NET support alongside Python.
- Natural deployment path for teams on Azure and Microsoft Foundry.
Cons
- Tilted toward the Microsoft cloud the way ADK is tilted toward Google Cloud.
- Python and .NET release on separate version tracks, so check both changelogs.
Pricing MIT and free to install from PyPI or NuGet. You pay your model provider, or Azure if you host on Microsoft Foundry.
TypeScript framework for agents, workflows and AI applications, with the AgentController loop in @mastra/core.
Pros
- TypeScript-native, for teams whose product is a Node or web app.
- Agents and workflows live in the same package.
Cons
- Check the license per package because of the ee/ carve-out.
- ADK also ships a TypeScript port (adk-js), so Mastra is not the only TS option.
Pricing Most code is Apache-2.0; anything in ee/ directories is under Mastra's enterprise license. No price is quoted here.
Questions
What is Google ADK?
The Agent Development Kit is Google's open-source, code-first toolkit for building, evaluating and deploying agents. adk-python is Apache-2.0, and Google also publishes ADK repositories for TypeScript, Go and Java. The latest Python release covered here is v2.14.0, published November 7, 2026.
Is there an open-source alternative to Google ADK?
All five picks are open source. The GitHub API reports MIT for LangGraph, Pydantic AI, the OpenAI Agents SDK and Microsoft Agent Framework. Mastra's license file puts most code under Apache-2.0 and ee/ directories under a separate license.
Google ADK vs LangGraph: which should I pick?
Pick ADK if you want built-in evaluation, sandboxed execution environments and a deployment path to Google Cloud's Agent Engine. Pick LangGraph if you want explicit graph state, checkpoints and no default cloud. Our longer comparison is LangGraph vs Google ADK.
Does Google ADK only work with Gemini?
No, but it leans that way. adk-python includes non-Gemini model paths, for example an Anthropic integration and a LiteLLM dependency, while its live audio and Agent Engine features are built around Google's stack.
Which Google ADK alternative is best for TypeScript?
Mastra is the TypeScript-native pick in this list. If you like ADK itself, Google's adk-js repository is a TypeScript port of the same toolkit.