How to Use the Marchex MCP in Vercel AI SDK

Q: How do I pass Marchex tools to Vercel AI SDK?

Call mcpClient.tools() and drop the output directly into generateText or streamText. The SDK maps them automatically.

Q: Can I stream Marchex call analytics into Next.js?

Yes. Using streamText pushes the results straight to the client. The user sees the numbers appear instantly.

Q: Does Vercel AI SDK support OAuth for Marchex accounts?

You can pass an authProvider when setting up the MCP client. This handles user-specific authentication before any tools execute.

Build live telecom dashboards with Vercel AI SDK pulling real-time call tracking metrics.

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Connect Marchex MCP to Vercel AI SDK

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

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Perplexity

Stream Marchex data via Vercel AI SDK

You want to show marketing managers their inbound call volume. Hooking up `search_calls` and `get_call_analytics` through your AI client means the data flows directly into your React components. No waiting for a massive payload to resolve. The UI updates as the language model processes the metrics. Users watch the dashboard populate live. That beats a loading spinner every time.

Live Campaign Monitoring

Static reports are dead. When you pass `list_campaigns` and `get_campaign_details` to the LLM, it can generate dynamic views of active marketing spend. Your frontend agents can filter these lists on the fly. A user types a question about Q3 performance, and the system pulls the exact campaign IDs needed to answer it.

Account Provisioning Interfaces

Building a custom portal requires surfacing raw inventory. Exposing `list_numbers` and `list_accounts` gives your Vercel frontend the hooks it needs to display available tracking lines. You keep the backend logic simple. The MCP protocol handles the tool execution, while your application focuses purely on rendering the results.

Setup guide

Set up Marchex 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 Marchex 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 Marchex 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 Marchex. 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 Marchex MCP in Vercel AI SDK

Call `mcpClient.tools()` and drop the output directly into `generateText` or `streamText`. The SDK maps them automatically.

Yes. Using `streamText` pushes the results straight to the client. The user sees the numbers appear instantly.

You can pass an `authProvider` when setting up the MCP client. This handles user-specific authentication before any tools execute.

The SDK throws an error that you can catch in your UI layer. You should always build fallback states for network failures.

Vinkius runs the MCP Server in an ephemeral V8 Isolate Sandbox. Your call details and tracking numbers are processed in memory and destroyed immediately after the response.

Use it with your favorite AI tools

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