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Choosing an Agent SDK

Last verified: 2026-07-30

The decision

You're building an agent. Which framework do you reach for?

The candidates

SDK Vendor Best for Watch out for
OpenAI Agents SDK OpenAI OpenAI-only stacks, handoffs, guardrails Lock-in to OpenAI models
Anthropic Claude Agent SDK Anthropic Long-horizon agents, computer use, file sandboxing Anthropic-only
LangGraph LangChain Stateful multi-agent graphs, complex orchestration Steeper learning curve
CrewAI CrewAI Role-based multi-agent, rapid prototyping Less control over execution
AutoGen Microsoft Async multi-agent, event-driven Heavier; .NET heritage shows
Google ADK Google Vertex-native, Google Workspace integration Google-cloud-centric
Pydantic AI Pydantic Type-safe structured outputs, minimal abstraction Less out-of-the-box agent logic
Instructor jxnl Pure structured output extraction Not an agent framework
LlamaIndex LlamaIndex RAG-first; agents as a secondary concern Less polished for pure-agent work
Mastra Mastra TypeScript-native, Vercel-style TS-only
Vercel AI SDK Vercel Streaming UIs in Next.js TS-only, less backend depth

The decision tree

graph TD
    A[Need an agent framework?] -->|No, just structured output| B[Instructor or Pydantic AI]
    A -->|Yes| C{Single vendor?}
    C -->|OpenAI| D[OpenAI Agents SDK]
    C -->|Anthropic| E[Claude Agent SDK]
    C -->|Multi-vendor| F{Need stateful multi-agent graphs?}
    F -->|Yes| G[LangGraph]
    F -->|No| H{Team preference?}
    H -->|Python, simple| I[CrewAI]
    H -->|Python, type-safe| J[Pydantic AI]
    H -->|TypeScript| K[Mastra or Vercel AI SDK]
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Default recommendation

If you don't know, pick OpenAI Agents SDK (Python) for greenfield work in 2026. It's the simplest path to a production agent. Switch to LangGraph when you need durable, multi-agent state machines.

References