--- title: AI SDK product: ai-sdk url: /docs/ai-sdk canonical_url: "https://vercel.com/docs/ai-sdk" last_updated: 2026-09-14 type: integration prerequisites: [] related: - /docs/connect/frameworks/ai-sdk-and-mcp summary: Build TypeScript agents and AI applications with a unified API for models, tools, structured output, and streaming. install_vercel_plugin: npx plugins add vercel/vercel-plugin --- # AI SDK ## Build AI agents Build TypeScript agents and AI applications with one API for models, tools, structured output, and streaming across Next.js, Vue, Svelte, Node.js, and other frameworks. ## Related pages > **For AI agents:** Follow these links to understand how this page connects to the rest of the Vercel ecosystem. For the full cross-link map (inbound, outbound, prerequisites, and semantic neighbors), see the .graph.md link below. - [How to architect an AI evaluation dashboard on Vercel](https://vercel.com/kb/guide/ai-evaluation-dashboard-architecture-on-vercel?from=related&source_path=%2Fdocs%2Fai-sdk&source_site=vercel-docs&relationship=related) — Map eval orchestration, traces, and run storage to AI Gateway, Observability, and Marketplace Postgres, and learn when s - [Agentic Infrastructure](https://vercel.com/blog/agentic-infrastructure?from=related&source_path=%2Fdocs%2Fai-sdk&source_site=vercel-docs&relationship=related) - [Zero Data Retention on AI Gateway](https://vercel.com/blog/zdr-on-ai-gateway?from=related&source_path=%2Fdocs%2Fai-sdk&source_site=vercel-docs&relationship=related) - [Tools](https://ai-sdk.dev/docs/foundations/tools?from=related&source_path=%2Fdocs%2Fai-sdk&source_site=vercel-docs&relationship=related) - [Vercel AI SDK 3.1: ModelFusion joins the team](https://vercel.com/blog/vercel-ai-sdk-3-1-modelfusion-joins-the-team?from=related&source_path=%2Fdocs%2Fai-sdk&source_site=vercel-docs&relationship=related) - [AI SDK by Vercel](https://ai-sdk.dev/docs/introduction?from=related&source_path=%2Fdocs%2Fai-sdk&source_site=vercel-docs&relationship=related) - [Get started with GPT-5](https://ai-sdk.dev/cookbook/guides/gpt-5?from=related&source_path=%2Fdocs%2Fai-sdk&source_site=vercel-docs&relationship=related) - [Building AI apps on Vercel: an overview](https://vercel.com/kb/guide/how-to-build-ai-app?from=related&source_path=%2Fdocs%2Fai-sdk&source_site=vercel-docs&relationship=related) — Learn the key AI concepts and tools for building and scaling AI apps. - [Get started with Llama 3.1](https://ai-sdk.dev/cookbook/guides/llama-3_1?from=related&source_path=%2Fdocs%2Fai-sdk&source_site=vercel-docs&relationship=related) - [@v0-sdk/ai-tools](https://v0.app/docs/api/v1/packages/ai-tools?from=related&source_path=%2Fdocs%2Fai-sdk&source_site=vercel-docs&relationship=related) — AI SDK tools for the v0 API - [How to build an AI agent for Slack with Chat SDK and AI SDK](https://vercel.com/kb/guide/how-to-build-an-ai-agent-for-slack-with-chat-sdk-and-ai-sdk?from=related&source_path=%2Fdocs%2Fai-sdk&source_site=vercel-docs&relationship=related) — Build a Slack AI agent using Chat SDK, AI SDK's ToolLoopAgent, and Vercel AI Gateway. Covers project setup, tool definit - [AI SDK for Python with AI Gateway](https://vercel.com/docs/ai-gateway/sdks-and-apis/ai-sdk-python?from=related&source_path=%2Fdocs%2Fai-sdk&source_site=vercel-docs&relationship=related) — Build AI-powered Python applications using the AI SDK for Python with AI Gateway for unified access to 200+ models. Full cross-link map for this page: [/docs/ai-sdk.graph.md](/docs/ai-sdk.graph.md?from=related&source_path=%2Fdocs%2Fai-sdk&source_site=vercel-docs&relationship=graph) #### Build an agent ```typescript filename="agent.ts" import { ToolLoopAgent, tool } from 'ai'; import { z } from 'zod'; const agent = new ToolLoopAgent({ model: 'anthropic/claude-fable-5.1', tools: { getWeather: tool({ description: 'Get the current weather for a location', inputSchema: z.object({ location: z.string() }), execute: async ({ location }) => ({ location, temperature: 72, condition: 'sunny', }), }), }, }); const { text } = await agent.generate({ prompt: "What's the weather in Tokyo?", }); console.log(text); ``` #### Generate text ```typescript filename="index.ts" import { generateText } from 'ai'; const { text } = await generateText({ model: 'openai/gpt-6-astra', prompt: 'Explain quantum entanglement in one paragraph.', }); console.log(text); ``` #### Generate structured data ```typescript filename="classify.ts" import { generateObject } from 'ai'; import { z } from 'zod'; const { object } = await generateObject({ model: 'openai/gpt-6-astra', schema: z.object({ sentiment: z.enum(['positive', 'neutral', 'negative']), }), prompt: 'Classify the sentiment: I love this product.', }); console.log(object); ``` ## Add models, tools, and streaming - **Unified provider API.** Switch between models by changing two lines of code - **Structured outputs.** Generate type-safe JSON with `generateObject` and `streamObject` - **Tool calling.** Let models interact with external systems - **Streaming first.** Stream text, objects, and UI to your frontend - **Framework support.** Works with React, Next.js, Vue, Svelte, and Node.js ## Generating text At the center of the AI SDK is [AI SDK Core](https://ai-sdk.dev/docs/ai-sdk-core/overview), which provides a unified API to call any LLM. The following example shows how to generate text with the AI SDK using OpenAI's GPT-6 Astra: ```typescript import { generateText } from 'ai'; const { text } = await generateText({ model: 'openai/gpt-6-astra', prompt: 'Explain the concept of quantum entanglement.', }); ``` The unified interface lets you switch providers by changing the model string. For example, to use Anthropic's Claude Fable 5.1: ```typescript {4} import { generateText } from 'ai'; const { text } = await generateText({ model: 'anthropic/claude-fable-5.1', prompt: 'How many people will live in the world in 2040?', }); ``` ## Generating structured data While text generation can be useful, you might want to generate structured JSON data. For example, you might want to extract information from text, classify data, or generate synthetic data. AI SDK Core provides two functions ([`generateObject`](https://ai-sdk.dev/docs/reference/ai-sdk-core/generate-object) and [`streamObject`](https://ai-sdk.dev/docs/reference/ai-sdk-core/stream-object)) to generate structured data, allowing you to constrain model outputs to a specific schema. The following example shows how to generate a type-safe recipe that conforms to a zod schema: ```ts import { generateObject } from 'ai'; import { z } from 'zod'; const { object } = await generateObject({ model: 'openai/gpt-6-astra', schema: z.object({ recipe: z.object({ name: z.string(), ingredients: z.array(z.object({ name: z.string(), amount: z.string() })), steps: z.array(z.string()), }), }), prompt: 'Generate a lasagna recipe.', }); ``` ## Give agents tools The AI SDK supports tool calling out of the box, allowing it to interact with external systems and perform discrete tasks. The following example shows how to use tool calling with the AI SDK: ```ts import { generateText, tool } from 'ai'; import { z } from 'zod'; const { text } = await generateText({ model: 'openai/gpt-6-astra', prompt: 'What is the weather like today in San Francisco?', tools: { getWeather: tool({ description: 'Get the weather in a location', inputSchema: z.object({ location: z.string().describe('The location to get the weather for'), }), execute: async ({ location }) => ({ location, temperature: 72 + Math.floor(Math.random() * 21) - 10, }), }), }, }); ``` ## Getting started with the AI SDK The AI SDK is available as a package. To install it, run the following command: ```bash pnpm i ai ``` ```bash yarn i ai ``` ```bash npm i ai ``` ```bash bun i ai ``` See the [AI SDK Getting Started](https://ai-sdk.dev/docs/getting-started) guide for more information on how to get started with the AI SDK. Follow [Build AI agents with AI Gateway and AI SDK](/kb/guide/ai-gateway-and-ai-sdk) to set up authentication, stream responses, and add tools and model fallbacks. ## Use Vercel Connect with AI SDK Vercel Connect supplies short-lived OAuth tokens to MCP clients built with AI SDK, so models can call tools from services such as Linear without storing provider credentials in your application. The `connectAuthProvider()` helper requests credentials and supports user consent flows. Follow the [AI SDK and MCP tutorial](/docs/connect/frameworks/ai-sdk-and-mcp) to configure Vercel Connect, make MCP tools available to an AI SDK application, and handle tool approval. ## Use Jev with AI SDK [Jev](/kb/jev-from-typesafe-ai), an evaluation model from TypeSafe AI, returns typed choices, scores, and boolean probabilities that your application can use to classify requests, route work, and assess proposed actions. Call Jev through AI Gateway with the experimental `evaluate` API in AI SDK 7 or later. Learn how to [classify, route, and score with Jev and AI SDK](/kb/guide/typesafe-jev-and-ai-sdk), or follow [Route form submissions with Jev and AI SDK](/kb/guide/jev-ai-sdk-form-router) to build a form router with configurable destinations and a fallback model for uncertain decisions. ## Build with a template Start with an AI SDK template to build a chatbot or route form submissions with Jev: ## More resources **AI SDK documentation**: Read the official AI SDK reference and guides. [Learn more →](https://ai-sdk.dev/docs) **AI SDK examples**: Browse runnable examples for common patterns. [Learn more →](https://ai-sdk.dev/cookbook) **AI SDK guides**: Step-by-step guides for building AI features. [Learn more →](https://vercel.com/kb/ai-sdk) **AI SDK templates**: Start from a production-ready Vercel template. [Learn more →](https://vercel.com/templates?type=ai) --- [View full sitemap](/docs/sitemap)