How to Use the Bringg MCP in Vercel AI SDK

Q: How do I connect Bringg tools to my Vercel AI SDK project?

Install @ai-sdk/mcp and instantiate the client with your Vinkius endpoint. You then pass mcpClient.tools() directly to streamText to let your agent manage fleets.

Q: Can the Vercel AI SDK handle live Bringg driver updates?

Yes. By calling gettasktimeline through the MCP Server, your frontend streams real-time status changes directly to the customer's viewport.

Q: Does the Vercel AI SDK support manual driver assignment in Bringg?

Absolutely. Your agent uses assigndrivertotask to instantly override automatic scheduling and bind a courier to a specific delivery.

Q: Does this MCP integration manage inactive connections?

Always call mcpClient.close() when your execution finishes. This prevents memory leaks and keeps your Edge Functions running lean.

Stream Bringg delivery logistics directly into your React or Next.js UI using the Vercel AI SDK.

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Connect Bringg MCP to Vercel AI SDK

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

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Dispatch deliveries live via Vercel AI SDK

`create_delivery_task` lets your application spawn new courier orders instantly. Your agent calls this tool to generate a delivery task in the Bringg Delivery Hub. The user sees the order status populate on their screen as the Edge Function handles the request. If plans change, the agent invokes `cancel_task_dispatch` to pull the order from the schedule. This direct integration eliminates the lag of traditional polling setups.

Track drivers and timelines in your frontend

`get_task_timeline` pulls the exact breadcrumb path of any active courier. The Vercel AI SDK streams this chronological log to the browser, letting customers watch their delivery progress live. By pairing this with `list_fleet_drivers`, your application maps out who is on the road. You get a clear view of your active workforce without building custom tracking APIs.

Override automated routing with this MCP Server

`assign_driver_to_task` gives your support agent the power to bypass automated dispatch algorithms. When an emergency delivery comes in, the agent assigns a specific driver to the task immediately. Users watch the assignment happen on their dashboard without waiting for a page reload. It makes manual dispatching feel like a natural conversation.

Setup guide

Set up Bringg 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 Bringg 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 Bringg 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 Bringg. 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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Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

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place for every integration

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Common questions about Bringg MCP in Vercel AI SDK

Install `@ai-sdk/mcp` and instantiate the client with your Vinkius endpoint. You then pass `mcpClient.tools()` directly to `streamText` to let your agent manage fleets.

Yes. By calling `get_task_timeline` through the MCP Server, your frontend streams real-time status changes directly to the customer's viewport.

Absolutely. Your agent uses `assign_driver_to_task` to instantly override automatic scheduling and bind a courier to a specific delivery.

Always call `mcpClient.close()` when your execution finishes. This prevents memory leaks and keeps your Edge Functions running lean.

Your customer CRM data and driver locations run inside isolated V8 sandboxes. Every MCP transaction handles these delivery details ephemerally, ensuring no personal info is stored on our servers.

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