How to Use the Inworld AI MCP in Vercel AI SDK

Q: Can Inworld AI and Vercel AI SDK handle streaming audio?

Yes. You can use the synthesizespeechstream tool to push audio directly into your frontend stream. This ensures minimal latency for your users.

Q: How are tools managed in Vercel AI SDK?

You retrieve the tool list from the MCP server using mcpClient.tools(). These tools are then mapped into the SDK's native tool definition format.

Bring lifelike character voices and real-time audio synthesis to your Vercel AI SDK frontends.

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Connect Inworld AI MCP to Vercel AI SDK

Create your Vinkius account to connect Inworld AI to Vercel AI SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Inworld AI with Vercel AI SDK

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Real-time voice streaming for Vercel AI SDK

Stream audio directly into your React or Next.js components without waiting for massive downloads. Using `synthesize_speech_stream`, you pipe raw audio chunks through your edge functions to keep the UI snappy. Your users hear the character speak the moment the first packet arrives. It removes the laggy experience that ruins most browser-based voice interfaces.

Dynamic character orchestration

Manage your agent's personality and logic using `create_router` and `update_router`. You can swap character behaviors mid-conversation based on user input or state changes in your app. This keeps your agent logic decoupled from your frontend codebase. When you need to change how an agent responds, you just update the router config via the MCP server.

Custom voice creation on the fly

Design unique character personas by passing text prompts to `design_voice`. You can also use `clone_voice` if you have specific audio samples you need to replicate for a brand-consistent experience. These voices persist in your workspace. Your agent can switch between them using `get_voice` to match the tone of the specific dialogue being generated.

Setup guide

Set up Inworld AI MCP in Vercel AI SDK

Prerequisites

Node.js 18+ and a TypeScript project
ai + @modelcontextprotocol/sdk packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies

Run npm install ai @modelcontextprotocol/sdk plus your preferred model provider (e.g. @ai-sdk/openai).
2

Create the Streamable HTTP transport

Use StreamableHTTPClientTransport with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and use tools

Call mcpClient.tools() to auto-discover all Inworld AI tools. Pass them directly to generateText() or streamText() — no manual schema definitions needed.
4

Works with any model provider

Swap openai("gpt-4o") for any AI SDK provider — Anthropic, Google, Mistral. The MCP tools work identically across all supported models.

index.ts

import { experimental_createMCPClient as createMCPClient } from "ai";
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

const transport = new StreamableHTTPClientTransport(
  new URL("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
);

const mcpClient = await createMCPClient({ transport });
const tools = await mcpClient.tools();

const { text } = await generateText({
  model: openai("gpt-4o"),
  tools,
  prompt: "List recent Inworld AI transactions",
});

console.log(text);
await mcpClient.close();

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Common questions about Inworld AI MCP in Vercel AI SDK

Install the MCP client package and initialize it with your server endpoint. You then pass the tools directly into the `generateText` or `streamText` functions provided by the SDK.

Yes. You can use the `synthesize_speech_stream` tool to push audio directly into your frontend stream. This ensures minimal latency for your users.

It does. The MCP server is designed to work over standard HTTP transports which are compatible with Vercel edge runtime environments.

You retrieve the tool list from the MCP server using `mcpClient.tools()`. These tools are then mapped into the SDK's native tool definition format.

Your audio samples and character voice data are stored within your private workspace. The MCP server only processes the specific requests you initiate.

Use it with your favorite AI tools

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