How to Use the iFLYTEK Open Platform / 讯飞开放平台 MCP in Vercel AI SDK

Q: How do I stream iFLYTEK Open Platform / 讯飞开放平台 audio outputs using Vercel AI SDK?

You call texttospeech through the SDK's streaming text or tool-calling functions. The server processes the text and returns the audio URL or raw bytes. You then pipe this payload directly into an HTML5 audio element on your frontend.

Q: Can Vercel AI SDK handle Chinese translation with iFLYTEK Open Platform / 讯飞开放平台?

Yes, you pass the translate tool directly to your SDK's model configuration. Your agent detects the source language and triggers the translation tool, returning the translated string to the stream.

Pipe real-time voice synthesis and Chinese NLP from the iFLYTEK Open Platform MCP Server directly into your Vercel AI SDK frontend.

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Connect iFLYTEK Open Platform / 讯飞开放平台 MCP to Vercel AI SDK

Create your Vinkius account to connect iFLYTEK Open Platform / 讯飞开放平台 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 iFLYTEK Open Platform / 讯飞开放平台 with Vercel AI SDK

Ask AI about this MCP

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Stream speech to text with Vercel AI SDK

`speech_to_text` transcribes incoming audio streams and pushes the raw text directly to your user's viewport. You hook this tool up to your Vercel AI SDK client, and it starts feeding text chunks to the browser without waiting for a full audio file to upload. This setup prevents UI lockups during long audio sessions. Because it bypasses typical mid-tier server bottlenecks, your application handles heavy audio files while keeping the client interface responsive.

Generate voice assets on Edge Functions

`text_to_speech` converts written text into natural-sounding audio files inside your edge runtime. This MCP Server handles the connection to the Chinese voice engine, allowing your Vercel AI SDK application to generate voice outputs near your users. You deploy this setup to Vercel's global network without hitting cold-start penalties. The lightweight payload execution ensures that voice synthesis starts in milliseconds, keeping your global users engaged.

Extract and analyze images in your chat window

`ocr_general` reads text from uploaded images and feeds it to your active chat thread. Your Vercel AI SDK client processes documents on the fly, immediately sending the extracted text to downstream tools like `summary_generation` or `translate`. You build interfaces where users drop a Chinese invoice and get an English summary instantly. This MCP setup handles the heavy lifting of image parsing and translation, updating the UI state as each step completes.

Setup guide

Set up iFLYTEK Open Platform / 讯飞开放平台 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 iFLYTEK Open Platform / 讯飞开放平台 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 iFLYTEK Open Platform / 讯飞开放平台 transactions",
});

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by iFLYTEK Open Platform / 讯飞开放平台. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about iFLYTEK Open Platform / 讯飞开放平台 MCP in Vercel AI SDK

You call `text_to_speech` through the SDK's streaming text or tool-calling functions. The server processes the text and returns the audio URL or raw bytes. You then pipe this payload directly into an HTML5 audio element on your frontend.

Yes, you pass the `translate` tool directly to your SDK's model configuration. Your agent detects the source language and triggers the translation tool, returning the translated string to the stream.

It runs with low overhead because the heavy lifting happens on Vinkius's isolated infrastructure. Your edge functions only manage the lightweight HTTP requests, keeping your execution costs down.

Vinkius handles the authentication handshake for you. You configure one endpoint token in your Vercel environment variables, and the platform manages the iFLYTEK API keys automatically.

Your audio files, document images, and text strings pass through Vinkius's ephemeral sandbox to the iFLYTEK API. No files are stored permanently on Vinkius servers, and the sandbox is destroyed immediately after processing.

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