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vercel-ai-sdk

Integrate Vercel AI SDK APIs, UI hooks, and streaming into TypeScript projects.

2|Updated Dec 30, 2025
Search Tags:#middleware#streaming#vercel#telemetry#tool-calling#ai-sdk
One-click install
npx skills add https://github.com/CaiZongyuan/Expo-TanstackDB-ElectricSQL --skill vercel-ai-sdk-caizongyuan
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: vercel-ai-sdk
Source: https://github.com/CaiZongyuan/Expo-TanstackDB-ElectricSQL/tree/main/.claude/skills/vercel-ai-sdk
Command: npx skills add https://github.com/CaiZongyuan/Expo-TanstackDB-ElectricSQL --skill vercel-ai-sdk-caizongyuan

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

The Vercel AI SDK provides a unified toolkit for building AI-powered applications, enabling developers to quickly integrate streaming, tool calling, and multi-provider workflows into TypeScript/JavaScript projects.

Core Features & Use Cases

  • Unified APIs & UI: Access core APIs (generateText, streamText) and UI hooks (useChat, useCompletion) for cohesive development across frontend and backend.
  • Tool Calling & Structured Data: Define and execute tools with schema-based inputs, supporting structured data generation and tool-driven workflows.
  • Streaming & Telemetry: Build responsive experiences with real-time streaming and observability via telemetry and OpenTelemetry integration.
  • MCP & Middleware: Connect to MCP servers and compose language model middleware for guardrails, caching, and routing.
  • End-to-End Examples: Provides end-to-end guidance from prompts to UI rendering, including testing and tooling patterns.

Quick Start

  1. Install the Vercel AI SDK packages and related providers.
  2. Create a minimal API using streamText and toUIMessageStreamResponse to stream responses.
  3. Build a UI using useChat or useCompletion with a transport that points to your API, then start streaming AI messages.

Use the vercel-ai-sdk skill to rapidly bootstrap AI-powered apps with streaming, tooling, and multi-provider patterns.

Frequently Asked Questions about vercel-ai-sdk

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I stream AI responses in a TypeScript application?▼

To stream AI responses, use the Vercel AI SDK's `streamText` API on the backend and the `useChat` UI hook on the frontend to render real-time messages via a configured transport.

What is the best way to implement tool calling with structured data?▼

Tool calling with structured data is implemented by defining tools with schema-based inputs and executing them through core APIs to support structured generation and tool-driven workflows.

Can I use middleware for caching and routing with language models?▼

Yes, you can compose language model middleware to apply guardrails, implement caching, and manage routing across different providers within your AI application architecture.

Does the Vercel AI SDK support telemetry and observability?▼

The SDK supports observability through built-in telemetry and OpenTelemetry integration, allowing you to monitor streaming responses and application performance effectively.

How do I connect to MCP servers using the Vercel AI SDK?▼

You can connect to MCP servers directly through the SDK's provider management capabilities, enabling multi-provider workflows and external tool integration for AI applications.

What do I need to build an AI chat UI from scratch?▼

Building an AI chat UI requires installing SDK packages, creating a streaming API endpoint, and using UI hooks like `useChat` or `useCompletion` with a transport pointing to your API.

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