BEST AI FRAMEWORKS

Vercel AI SDK

Essential

The standard for TypeScript AI apps. Unified provider API, streaming, tool calling, structured output, and React hooks - all in one package.

• -Unified API across OpenAI, Anthropic, Google
• -Built-in streaming with React hooks (useChat, useCompletion)
• -Structured output with Zod schemas
• -Multi-step agent loops with tool calling
• -50K+ GitHub stars

Mastra

The TypeScript-native agent framework. Batteries-included primitives for agents, tools, memory, durable workflows, RAG, evals, and tracing - built for Node.js apps.

• -TypeScript-native throughout - typed tools, schemas, workflow steps
• -Durable workflows with branching, loops, and persistence
• -Built-in RAG pipelines, evals, and tracing
• -Local testing in Mastra Studio
• -Integrates with Next.js, Express, Hono, and MCP

LangChain / LangGraph

The most popular LLM framework overall. Massive ecosystem with 100K+ GitHub stars. LangGraph adds stateful multi-agent workflows.

• -100K+ GitHub stars - largest community
• -LangGraph for stateful, graph-based agent workflows
• -RAG with any vector store
• -LangSmith for observability and tracing
• -Integrations with every model provider and tool

OpenAI Agents SDK

Lightweight and minimal. Agent handoffs, guardrails, and tracing without heavy abstractions. Successor to the Swarm experiment.

• -Minimal abstractions - agents are simple Python objects
• -Built-in agent-to-agent handoffs
• -Input/output guardrails
• -Native tracing and observability
• -Streaming support

Claude Agent SDK

Anthropic's SDK for production agent systems. Native tool use, guardrails, and orchestration designed for Claude models.

• -Native Claude tool use - no wrapper layers
• -Auto-generated tool schemas from Python functions
• -Agent-to-agent handoffs
• -Input/output validation guardrails
• -Designed for production reliability