Vercel AI SDK

The Vercel AI SDK is a free, open-source TypeScript toolkit built by the team behind Vercel and Next.js for building AI-powered applications and agents. It gives JavaScript and TypeScript developers a single, unified API for generating text, structured data, and tool calls across any model provider, from OpenAI and Anthropic to Google, xAI, and dozens more. Instead of writing separate integration code for every provider you might switch to, you call the same functions and swap the model string. The SDK also ships framework-agnostic UI hooks for React, Vue, and Svelte, so streaming chat interfaces come with far less boilerplate. For developers shipping production AI features fast, it removes the provider lock-in and repetitive plumbing that used to slow every new integration down.

How Vercel AI SDK works

The AI SDK organizes itself into a few main pieces, each solving a different part of building an AI application. You install only the pieces your project needs.

• AI SDK Core: A unified API with functions like generateText, generateObject, and streamText that work identically no matter which model provider you call. Switching from GPT to Claude is a one-line change.
• Structured output: The generateObject and streamObject functions constrain a model’s response to a schema you define, so you get validated, typed data back instead of parsing free-form text.
• Tool calling: Functions you register become tools the model can call mid-conversation. The streamText function automatically handles multi-step tool loops, so the model can call a tool, read the result, and keep reasoning without you managing the loop by hand.
• AI SDK UI: Framework-agnostic hooks, like useChat and useObject, that wire a streaming model response directly into a React, Vue, or Svelte component with minimal setup.
• AI SDK Harnesses: A uniform HarnessAgent API for running established coding agent harnesses, such as Claude Code and Codex, inside the same streaming and UI primitives as the rest of the SDK.
• Model Context Protocol (MCP): Native support for connecting your agent to external MCP-compliant tools and data sources without writing custom adapters.

What you can build with Vercel AI SDK

• Multi-provider chatbot: Ship a chat interface with useChat and swap between OpenAI, Anthropic, and Google models with one line of code, useful for testing which model performs best for your use case without rewriting your app.
• Internal knowledge base with RAG: Combine AI SDK Language Model Middleware with a vector store to retrieve relevant documents before generating an answer, and enforce guardrails on what the model can and cannot say.
• Natural language database queries: Let users ask questions in plain English and use generateObject to turn them into validated SQL queries against a Postgres database, cutting out manual query writing for non-technical users.
• Generative UI dashboard: Stream structured data directly into React components as the model generates it, so users see charts, tables, or cards render progressively instead of waiting for a full response.
• Multi-step research agent: Register web search and file-reading tools, then let streamText handle the multi-step loop of searching, reading, and synthesizing a final answer without you managing each round trip.
• Voice-enabled assistant: Pair the SDK’s transcription and speech functions with a chat agent to build a voice interface that transcribes user speech, generates a response, and speaks it back.