How to Use the Determ MCP in Vercel AI SDK

Q: How do I register the Determ MCP tools within the Vercel AI SDK?

Install @ai-sdk/mcp and call createMCPClient pointing to your Vinkius endpoint. Pass the tools from mcpClient.tools() directly into your generateText or streamText function calls, and always call mcpClient.close() when the execution finishes.

Q: How do I find my current API limits and usage stats?

Your agent can run getaccountmetadata to check your current account plan, query limits, and active usage metrics. This helps you monitor your consumption before launching heavy automated runs.

Stream live media spikes directly to your Next.js app using the Determ MCP Server with Vercel AI SDK.

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Connect Determ MCP to Vercel AI SDK

Create your Vinkius account to connect Determ 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 Determ with Vercel AI SDK

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Real-time media sentiment streaming with Vercel AI SDK

The `get_query_sentiment_summary` tool lets you stream real-time emotional breakdowns directly to your user interface. Stop making your users wait for heavy analytics dashboards to load. When you wire this MCP Server into your streaming frontend, the AI client pulls raw sentiment numbers and renders the breakdown block-by-block. Your UI updates as the tokens arrive, showing positive and negative spikes without awkward loading spinners.

Instant deep-dives on high-reach coverage

Using `list_recent_high_reach_mentions` allows your AI client to isolate high-impact brand coverage instantly. When a major outlet mentions your brand, you need to act fast. This integration lets your AI client isolate the biggest stories instantly, skipping the noise of low-authority blogs and focusing your attention where the actual eyeballs are. Once the AI flags a critical article, it runs `get_mention_details` to pull the full text and technical metadata.

Targeted keyword hunting inside your streams

The `search_mentions_by_keyword` tool lets your agent filter through active monitoring streams without pulling down heavy, irrelevant datasets. Sometimes you need to find a specific competitor mention inside a massive pile of PR data. Your agent can run this tool to filter through active monitoring queries. You pull the specific match, grab the context, and show it to the user. Because this is built on top of the Vercel AI SDK, you can easily clean up the text in real-time, highlighting the exact keyword matches in your React components.

Setup guide

Set up Determ 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 Determ 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 Determ 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 Determ. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

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Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

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place for every integration

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Common questions about Determ MCP in Vercel AI SDK

Install `@ai-sdk/mcp` and call `createMCPClient` pointing to your Vinkius endpoint. Pass the tools from `mcpClient.tools()` directly into your `generateText` or `streamText` function calls, and always call `mcpClient.close()` when the execution finishes.

Yes, that is the main benefit of this setup. The SDK streams the text output of `get_query_sentiment_summary` as it is generated, letting you render live UI components on the fly without waiting for the full payload.

No, the server runs on Vinkius's high-speed infrastructure, meaning your edge functions only handle the lightweight streaming connection. This setup prevents timeouts and keeps your UI highly responsive.

Your agent can run `get_account_metadata` to check your current account plan, query limits, and active usage metrics. This helps you monitor your consumption before launching heavy automated runs.

Your monitoring queries and raw mention text never persist on Vinkius. Every call to `get_mention_details` runs in an ephemeral, isolated V8 sandbox that is destroyed immediately after your request finishes, keeping your market research confidential.

Use it with your favorite AI tools

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