Comparison

Updated October 25, 2026

· ~2 min read

Agent Frameworks in 2026: LangGraph vs OpenAI Agents SDK vs Claude Agent SDK vs Strands vs Google ADK

AI Agents
LangGraph
OpenAI Agents SDK
Claude Agent SDK
Strands Agents
Bedrock AgentCore

An agent framework decides how you write the loop (model calls, tool calls, state, hand-offs between agents) and a runtime decides where that loop runs safely. In 2026 the two have separated cleanly. Frameworks compete on programming model; runtimes like Amazon Bedrock AgentCore, generally available since October 2025, run agents built with any of them, with session isolation, executions of up to eight hours, identity, memory, a gateway that turns APIs and Lambda functions into MCP tools, and OpenTelemetry-compatible observability.

So pick a framework for how your team wants to write agents, and a runtime for how you need to operate them.

At a glance

LangGraph

OpenAI Agents SDK

Claude Agent SDK

Strands Agents

Google ADK

From

LangChain

OpenAI

Anthropic

AWS (open source)

Google

Style

Explicit graph of nodes and edges

Agents, tools, hand-offs

Model-driven loop with hooks and subagents

Model-driven loop

Agents and workflows

State and resume

Built-in checkpointing

Sessions

Sessions and compaction

Session managers

Sessions

MCP

Via adapters

Supported

Native, including in-process servers

Supported

Supported

Models

Any

OpenAI first; others via providers

Claude — via Anthropic, Bedrock or Vertex

Bedrock first; others via providers

Gemini first; others via providers

Runs on AgentCore

Yes

Yes

Yes

Yes

Yes

What AgentCore adds, whichever you choose

Frameworks leave the production problems to you: isolating one user's session from another's, holding credentials to act on a user's behalf, giving agents tools without hand-writing integrations, and seeing what an agent actually did. AgentCore packages those: Runtime (isolated sessions, up to eight-hour executions, Agent-to-Agent protocol), Gateway (APIs, Lambda functions and existing MCP servers as tools, with IAM or OAuth), Identity (OAuth vaulting and acting on behalf of users), Memory, Observability (CloudWatch dashboards, OpenTelemetry to Langfuse, LangSmith, Arize Phoenix, Datadog and others), and Policy, which checks every tool call against rules before it runs. In June 2026 AWS added AgentCore harness, which stands up a production agent with two API calls.

Which should you use?

Question 1 of 2

Is the agent a structured workflow with branches, approvals and resumable state?

Our verdict

Use LangGraph when the agent is a genuine workflow — branches, loops, human approvals, long-running state you need to inspect and resume — because explicit graphs and checkpointing make that tractable. Use the Claude Agent SDK when the agent is mostly a capable model with tools, especially MCP tools, and you want the same harness that powers Claude Code. Use the OpenAI Agents SDK for the quickest path to tool use and hand-offs between agents. Use Strands Agents on AWS for a model-driven loop with first-class Bedrock support and AWS's own maintenance. Use Google ADK if you are building on Google's stack. Then run whichever you chose on AgentCore Runtime, Lambda or ECS — the framework does not lock you to a runtime.

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Get an agent into production on AWS

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As of October 25, 2026. Provided as is, for general information, and accurate to the best of our knowledge on the date shown. Not legal, compliance, tax, financial or other professional advice. Prices, limits and vendor services change; check current vendor documentation before relying on anything here. Terms of use.