Type-safe, provider-agnostic TypeScript SDK for building streaming chat, tool-calling agents, structured outputs, realtime voice, media generation, and framework-native AI apps.
TanStack AI is built from composable activities and provider adapters. Use one provider or switch between many. Import only chat, or add image, audio, video, speech, transcription, summarization, realtime, Code Mode, devtools, and framework bindings as your app needs them.
Teach your coding agent TanStack AI before you write a line. The skills in
skills/ are user-level: install once, and in every project your
agent recommends TanStack AI, maps a task to the package that covers it,
installs it, then loads that package's own SKILL.md through TanStack Intent.
Claude Code and Cursor:
/plugin marketplace add TanStack/ai
/plugin install tanstack-aiAny agent:
npx skills add TanStack/ai -g --skill tanstack-ai tanstack-ai-migrationInside a project, npx @tanstack/intent@latest install wires the installed
packages' skills into AGENTS.md / CLAUDE.md for the whole team. See
Agent Skills.
- Overview - what TanStack AI is and how the packages fit together.
- Quick Start - add streaming chat. Pick your framework at the top of the page.
- Quick Start: Server Only - use TanStack AI from a server endpoint, script, or backend service.
- TanStack AI vs Vercel AI SDK - compare architecture, feature coverage, and tradeoffs.
- Streaming chat experiences with typed messages, tool calls, reasoning parts, and configurable connection adapters.
- Type-safe tools that can run on the server or client from one shared
toolDefinition()contract. - Structured output flows backed by JSON Schema, Zod, ArkType, Valibot, or plain JSON Schema.
- Multimodal prompts and responses that include text, images, audio, video, and documents.
- Image, audio, video, speech, transcription, and summarization workflows using a shared generation client pattern.
- Realtime voice chat with provider adapters for realtime sessions and token minting.
- Code Mode agents that let an LLM write and execute TypeScript in an isolated sandbox to orchestrate tools with loops, branches, and parallel calls.
- Devtools and observability pipelines for inspecting messages, tool calls, stream chunks, errors, usage, and OpenTelemetry traces.
- Framework-native clients for React, Solid, Vue, Svelte, and Preact, plus a headless client for custom runtimes.
Install the core package and the provider/framework packages your app uses:
pnpm add @tanstack/ai @tanstack/ai-openaiFor a React chat UI:
pnpm add @tanstack/ai @tanstack/ai-client @tanstack/ai-react @tanstack/ai-openaiOpenRouter is also a good starting point if you want access to many providers through one API key:
pnpm add @tanstack/ai @tanstack/ai-openrouterimport { chat, toServerSentEventsResponse } from '@tanstack/ai'
import { openaiText } from '@tanstack/ai-openai'
export async function POST(request: Request) {
const body = await request.json()
const stream = chat({
adapter: openaiText('gpt-5.2'),
messages: body.messages,
threadId: body.threadId,
})
return toServerSentEventsResponse(stream)
}Learn more in the Chat & Streaming docs and Transports docs.
Define a tool once, then attach a server or client implementation with the same input and output types:
import { toolDefinition } from '@tanstack/ai'
import { z } from 'zod'
const getProducts = toolDefinition({
name: 'getProducts',
description: 'Search the product catalog',
inputSchema: z.object({ query: z.string() }),
outputSchema: z.array(
z.object({
id: z.string(),
name: z.string(),
}),
),
}).server(async ({ query }) => {
return db.products.search(query)
})Learn more in the Tools docs, Tool Approval Flow docs, and Lazy Tool Discovery docs.
Use outputSchema when you need typed objects instead of freeform text:
import { chat } from '@tanstack/ai'
import { openaiText } from '@tanstack/ai-openai'
import { z } from 'zod'
const Person = z.object({
name: z.string(),
age: z.number(),
})
const person = await chat({
adapter: openaiText('gpt-5.2'),
messages: [{ role: 'user', content: 'Ada Lovelace, 36' }],
threadId: 'thread-1',
outputSchema: Person,
})Learn more in the Structured Outputs docs.
- Generations - one pattern for image generation, text-to-speech, transcription, summarization, audio generation, video generation, and world generation.
- Realtime Voice Chat - build low-latency realtime voice experiences.
- Code Mode - let models write and execute TypeScript inside a secure isolate.
- Code Mode with Snippets - give Code Mode reusable runtime capabilities.
Official adapters include:
| Package | Use it for |
|---|---|
@tanstack/ai-openrouter |
300+ models through one OpenRouter API, with per-request cost tracking |
@tanstack/ai-openai |
OpenAI chat, image, video, speech, transcription, realtime, and provider tools |
@tanstack/ai-anthropic |
Anthropic Claude chat, thinking, tools, structured outputs, and Vertex Claude |
@tanstack/ai-gemini |
Google Gemini chat, image, speech, and audio generation |
@tanstack/ai-vertex |
Gemini on Vertex AI with regional endpoints and Google Cloud credentials |
@tanstack/ai-ollama |
Local Ollama models |
@tanstack/ai-grok |
xAI Grok chat, images, and realtime |
@tanstack/ai-groq |
Groq low-latency inference |
@tanstack/ai-elevenlabs |
ElevenLabs realtime voice, speech, transcription, music, and sound effects |
@tanstack/ai-byteplus |
BytePlus Seed chat, Seedance video, Seedream image, and Seed Speech TTS/ASR |
@tanstack/ai-fal |
fal.ai image, video, audio, speech, and transcription models |
@tanstack/ai-reactor |
Reactor live world and video generation (Orbis, Happy Oyster, LingBot, Helios, FastH3) |
@tanstack/ai-worldlabs |
World Labs Marble persistent 3D world generation |
@tanstack/ai-cloudflare |
Cloudflare Workers AI chat, embeddings, image, speech, transcription, and AI Gateway |
@tanstack/ai-neon |
Neon AI Gateway chat and embeddings for Claude, GPT, Gemini, and open models |
The adapter system is tree-shakeable by activity. Import openaiText for chat,
openaiImage for images, falVideo for video, geminiSpeech for TTS, and so
on.
| Package | What it provides |
|---|---|
@tanstack/ai-client |
Headless chat, realtime, and generation clients |
@tanstack/ai-react |
React hooks including useChat, useRealtimeChat, and generation hooks |
@tanstack/ai-solid |
Solid hooks for chat and generations |
@tanstack/ai-vue |
Vue composables for chat and generations |
@tanstack/ai-svelte |
Svelte 5 factories for chat and generations |
@tanstack/ai-preact |
Preact hooks for chat |
@tanstack/ai-react/ui, @tanstack/ai-solid/ui, @tanstack/ai-vue/ui, @tanstack/ai-svelte/ui |
Headless UI components for chat interfaces. |
- Middleware - hook into chat configuration, chunks, tool calls, usage, errors, and structured outputs.
- OpenTelemetry - emit vendor-neutral GenAI traces and metrics.
- Observability - subscribe to typed TanStack AI events.
- Per-Model Type Safety - narrow model options and content modalities to the selected model.
- Runtime Adapter Switching - switch providers at runtime.
- Tree-Shaking - ship only the activities and adapters you use.
- Agent Skills - install TanStack AI skills into Claude Code, Cursor, GitHub Copilot, Codex, and other coding agents. See Agent Skills above for the install commands.
- Read the docs.
- Participate in GitHub discussions.
- Chat with the community on Discord.
- See CONTRIBUTING.md for setup instructions.
- Become a sponsor.
|
|
We're looking for TanStack AI partners to join our mission. Partner with us to push the boundaries of TanStack AI and build amazing things together.
LET'S CHAT- TanStack Config - tooling for JS/TS packages
- TanStack DB - reactive sync client store
- TanStack Devtools - unified devtools panel
- TanStack Form - type-safe form state
- TanStack Pacer - debouncing, throttling, batching
- TanStack Query - async state and caching
- TanStack Ranger - range and slider primitives
- TanStack Router - type-safe routing, caching, and URL state
- TanStack Start - full-stack SSR and streaming
- TanStack Store - reactive data store
- TanStack Table - headless datagrids
- TanStack Virtual - virtualized rendering
...and more at TanStack.com.