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@ai-sdk/mcp

The **Model Context Protocol (MCP) client** for the [AI SDK](https://ai-sdk.dev/docs) lets you connect to MCP servers and use their tools with AI SDK functions like `generateText` and `streamText`.

Links

README

From the repo.

hero illustration

AI SDK

The AI SDK is a provider-agnostic TypeScript toolkit designed to help you build AI-powered applications and agents using popular UI frameworks like Next.js, React, Svelte, Vue, Angular, and runtimes like Node.js.

To learn more about how to use the AI SDK, check out our API Reference and Documentation.

Installation

You will need Node.js 22+ and npm (or another package manager) installed on your local development machine.

npm install ai

Skill for Coding Agents

If you use coding agents such as Claude Code or Cursor, we highly recommend adding the AI SDK skill to your repository:

npx skills add vercel/ai

Unified Provider Architecture

The AI SDK provides a unified API to interact with model providers like OpenAI, Anthropic, Google, and more.

By default, the AI SDK uses the Vercel AI Gateway to give you access to all major providers out of the box. Just pass a model string for any supported model:

const result = await generateText({
  model: 'anthropic/claude-opus-5.5', // or 'openai/gpt-6-astra', 'google/gemini-3.8-flash', etc.
  prompt: 'Hello!',
});

You can also connect to providers directly using their SDK packages:

npm install @ai-sdk/openai @ai-sdk/anthropic @ai-sdk/google
import { anthropic } from '@ai-sdk/anthropic';

const result = await generateText({
  model: anthropic('claude-opus-5-5'), // or openai('gpt-6-astra'), google('gemini-3.8-flash'), etc.
  prompt: 'Hello!',
});

Usage

Generating Text

import { generateText } from 'ai';

const { text } = await generateText({
  model: 'openai/gpt-6-astra', // use Vercel AI Gateway
  prompt: 'What is an agent?',
});

Generating Structured Data

import { generateText, Output } from 'ai';
import { z } from 'zod';

const { output } = await generateText({
  model: 'openai/gpt-6-astra',
  output: Output.object({
    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.',
});

Agents

import { ToolLoopAgent } from 'ai';

const sandboxAgent = new ToolLoopAgent({
  model: 'openai/gpt-6-astra',
  system: 'You are an agent with access to a shell environment.',
  tools: {
    shell: openai.tools.localShell({
      execute: async ({ action }) => {
        const [cmd, ...args] = action.command;
        const sandbox = await getSandbox(); // Vercel Sandbox
        const command = await sandbox.runCommand({ cmd, args });
        return { output: await command.stdout() };
      },
    }),
  },
});

UI Integration

The AI SDK UI module provides a set of hooks that help you build chatbots and generative user interfaces. These hooks are framework agnostic, so they can be used in Next.js, React, Svelte, and Vue.

You need to install the package for your framework, e.g.:

npm install @ai-sdk/react

Agent @/agent/image-generation-agent.ts

import { openai } from '@ai-sdk/openai';
import { ToolLoopAgent, InferAgentUIMessage } from 'ai';

export const imageGenerationAgent = new ToolLoopAgent({
  model: 'openai/gpt-6-astra',
  tools: {
    generateImage: openai.tools.imageGeneration({
      partialImages: 3,
    }),
  },
});

export type ImageGenerationAgentMessage = InferAgentUIMessage<
  typeof imageGenerationAgent
>;

Route (Next.js App Router) @/app/api/chat/route.ts

import { imageGenerationAgent } from '@/agent/image-generation-agent';
import { createAgentUIStreamResponse } from 'ai';

export async function POST(req: Request) {
  const { messages } = await req.json();

  return createAgentUIStreamResponse({
    agent: imageGenerationAgent,
    messages,
  });
}

UI Component for Tool @/component/image-generation-view.tsx

import { openai } from '@ai-sdk/openai';
import { UIToolInvocation } from 'ai';

export default function ImageGenerationView({
  invocation,
}: {
  invocation: UIToolInvocation<ReturnType<typeof openai.tools.imageGeneration>>;
}) {
  switch (invocation.state) {
    case 'input-available':
      return <div>Generating image...</div>;
    case 'output-available':
      return <img src={`data:image/png;base64,${invocation.output.result}`} />;
  }
}

Page @/app/page.tsx

'use client';

import { ImageGenerationAgentMessage } from '@/agent/image-generation-agent';
import ImageGenerationView from '@/component/image-generation-view';
import { useChat } from '@ai-sdk/react';

export default function Page() {
  const { messages, status, sendMessage } =
    useChat<ImageGenerationAgentMessage>();

  const [input, setInput] = useState('');
  const handleSubmit = e => {
    e.preventDefault();
    sendMessage({ text: input });
    setInput('');
  };

  return (
    <div>
      {messages.map(message => (
        <div key={message.id}>
          <strong>{`${message.role}: `}</strong>
          {message.parts.map((part, index) => {
            switch (part.type) {
              case 'text':
                return <div key={index}>{part.text}</div>;
              case 'tool-generateImage':
                return <ImageGenerationView key={index} invocation={part} />;
            }
          })}
        </div>
      ))}

      <form onSubmit={handleSubmit}>
        <input
          value={input}
          onChange={e => setInput(e.target.value)}
          disabled={status !== 'ready'}
        />
      </form>
    </div>
  );
}

Templates

We've built templates that include AI SDK integrations for different use cases, providers, and frameworks. You can use these templates to get started with your AI-powered application.

Community

The AI SDK community can be found on the Vercel Community where you can ask questions, voice ideas, and share your projects with other people.

Contributing

Contributions to the AI SDK are welcome and highly appreciated. However, before you jump right into it, we would like you to review our Contribution Guidelines to make sure you have smooth experience contributing to AI SDK.

Authors

This library is created by Vercel and Next.js team members, with contributions from the Open Source Community.

Collected info

  • Language: TypeScript
  • Source updated: 8/30/2026

Config for your environment

Replace {MCP_ENDPOINT_URL} with this MCP’s endpoint URL (from its repo or docs above). No API key — you connect directly.

Tool

OS

Config file: ~/.cursor/mcp.json

{
  "mcpServers": {
    "mcp-server": {
      "url": "{MCP_ENDPOINT_URL}"
    }
  }
}

Paste into mcpServers in the config file. Restart Cursor after saving.

If this MCP is also published on mcpchannel.ai, you can subscribe from Browse and use the gateway config there instead.