Vercel AI SDK

1. 1

   Create the client once and pass its tools to generateText or streamText.

   TypeScriptCopy

   import { experimental_createMCPClient as createMCPClient, generateText } from "ai";
   import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp.js";
   
   const mcp = await createMCPClient({
     transport: new StreamableHTTPClientTransport(new URL("https://api.zomler.com/mcp"), {
       requestInit: { headers: { Authorization: `Bearer ${process.env.ZOMLER_API_KEY}` } },
     }),
   });
   
   const { text } = await generateText({
     model: "anthropic/claude-fable-5-1",
     tools: await mcp.tools(),
     prompt: "Compare @example and @sample on Instagram.",
   });
   await mcp.close();

One tool per platform, plus capabilities and check_balance, at https://api.zomler.com/mcp. Every answer is the envelope: what was measured, when, what was left out and why, and what it cost. Fresh fetches spend credits; anything already held is free.

Keys are created under API keys in the dashboard, where each one's calls and spend are listed. Revoking a key stops this client on its next call. The same key also calls the REST API.

All clients