How to Use the LTV:CAC Calculator MCP in Vercel AI SDK
Get real-time financial metrics for your Vercel AI SDK frontends.
Works with every AI agent you already use
…and any MCP-compatible client
Connect LTV:CAC Calculator MCP to Vercel AI SDK
Create your Vinkius account to connect LTV:CAC Calculator to Vercel AI SDK — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.
Gemini
Key Capabilities
Stream LTV:CAC data into your UI.
Need to show users complex calculations live? You can call `calculate_cac` and stream the results directly into a React or Next.js component. The user sees the Cost per Channel calculation appear instantly, without waiting for a loading spinner. The tool also handles LTV modeling using `calculate_ltv`. Since your agent streams output, you'll get immediate feedback on customer value as soon as the data is processed.
Determine profitability ratios in real-time.
The core of this MCP is determining if acquisition efforts make sense. After calculating LTV and CAC separately, calling `evaluate_profitability` gives you a final verdict on the LTV:CAC ratio. This makes building interactive financial dashboards simple. You write the client-side logic; Vercel AI SDK handles streaming the calculated metrics to your users.
Visualize acquisition cost by channel.
If you're dealing with multiple marketing sources, this MCP accepts a JSON array of channels. You pass it into `calculate_cac` and get immediate data on total spend versus new customers acquired for each source. This real-time visibility is perfect for client-facing tools where the user needs to see exactly how much money was spent and what that translates to.
Set up LTV:CAC Calculator MCP in Vercel AI SDK
Prerequisites
- Node.js 18+ and a TypeScript project
-
ai+@modelcontextprotocol/sdkpackages - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
npm install ai @modelcontextprotocol/sdkplus your preferred model provider (e.g.@ai-sdk/openai). - 2
Create the Streamable HTTP transport
Use
StreamableHTTPClientTransportwith 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 LTV:CAC Calculator tools. Pass them directly togenerateText()orstreamText()— 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.
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 LTV:CAC Calculator transactions",
});
console.log(text);
await mcpClient.close();Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by LTV:CAC Calculator API. 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 LTV:CAC Calculator MCP in Vercel AI SDK
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