How to Use the Aptabase (Mobile Analytics) MCP in Vercel AI SDK

Q: Can Vercel AI SDK stream responses while Aptabase (Mobile Analytics) logs events?

Yes. The sendevent tool operates asynchronously. Your Next.js frontend keeps rendering the streamed response while the telemetry fires off in the background.

Track app telemetry in real-time while streaming UI updates directly through your Vercel AI SDK frontend.

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Connect Aptabase (Mobile Analytics) MCP to Vercel AI SDK

Create your Vinkius account to connect Aptabase (Mobile Analytics) 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 Aptabase (Mobile Analytics) with Vercel AI SDK

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Stream Aptabase telemetry into React

The `send_event` tool fires asynchronously in the background while your Vercel AI SDK edge function continues streaming text to the client. Users hate waiting for loading spinners. When your application logs an action, it needs to happen fast. You get immediate visibility into how people interact with your generative features. Hook this MCP Server into your setup, and you capture every prompt, click, and completion without blocking the main rendering thread. The integration handles the network request to the analytics provider silently.

Native tool calling with Vercel AI SDK

Passing `send_event` directly to your generation functions requires zero boilerplate. Fetch the configuration using `mcpClient.tools()` and drop it right into your API call. The agent decides when a specific user interaction warrants tracking based on the context of the conversation. Maybe someone asks a complex question that triggers a specialized UI component. The model calls the tool to log that specific component render in Aptabase. You track feature adoption without writing manual event listeners across your React tree.

Asynchronous tracking at the edge

Processing `send_event` calls asynchronously ensures your analytics requests never add latency to the response. Analytics requests usually slow down time-to-first-token. That kills the magic of an instant generative reply. Because this integration processes everything in the background, your application fires off the telemetry and immediately moves on. Build Next.js or SvelteKit apps that actually understand how they get used. You capture the exact performance metrics of your features, sending custom data payloads to Aptabase while keeping your UI snappy.

Setup guide

Set up Aptabase (Mobile Analytics) 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 Aptabase (Mobile Analytics) 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 Aptabase (Mobile Analytics) transactions",
});

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Aptabase. 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 Aptabase (Mobile Analytics) MCP in Vercel AI SDK

Install @ai-sdk/mcp and initialize your client with createMCPClient. Point the HTTP transport URL to your Vinkius endpoint. Then pass mcpClient.tools() directly into streamText or generateText.

Yes. The send_event tool operates asynchronously. Your Next.js frontend keeps rendering the streamed response while the telemetry fires off in the background.

It does. The HTTP transport protocol plays perfectly with edge runtimes. You can log custom events directly from your edge-deployed AI routes.

No manual mapping is required. The SDK reads the tool definitions directly from the server. Just remember to call mcpClient.close() when your route finishes executing.

Vinkius runs the integration inside an ephemeral V8 Isolate Sandbox. Your custom events and app usage data pass through a zero-trust environment. The server spins up, routes the payload to Aptabase, and instantly destroys the execution context.

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