How to Use the Metricool MCP in Vercel AI SDK

Q: How do I stream Metricool data using Vercel AI SDK?

Install @ai-sdk/mcp and initialize the MCP client with your Vinkius HTTP endpoint. Pass the tools from mcpClient.tools() into streamText to let your agent call getunifiedsummary and stream social metrics directly to your React frontend.

Build real-time marketing dashboards that stream live social data directly into your React components using the Vercel AI SDK.

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Connect Metricool MCP to Vercel AI SDK

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

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Stream live social performance straight to your UI

Your Vercel AI SDK setup can pull immediate performance metrics without making users stare at a blank loading screen. By calling `get_unified_summary`, the agent fetches cross-channel performance and streams the raw numbers directly into your Next.js page. This means you build interfaces where social metrics render step-by-step. If a client needs a quick breakdown, the MCP server feeds the data to your UI components immediately instead of waiting for a massive API payload to finish downloading.

Build interactive social planners with Vercel AI SDK

Stop building complex forms for social media scheduling. Let your users talk to your app to organize their calendar by exposing `get_social_planner` directly to your model. The model reads the existing schedule and updates queue gaps in real-time. Your user sees their updated calendar populate on screen instantly as the Vercel AI SDK streams the tool responses.

Instant multi-platform analytics on the edge

Deploy your marketing tools to Vercel Edge Functions and run rapid lookups across networks. This MCP server lets your model call `get_instagram_analytics` and `get_linkedin_analytics` in a lightweight edge runtime. You do not need to manage heavy SDKs for five different social networks. One Vinkius endpoint handles the connection, giving your edge-deployed agent clean JSON payloads instantly.

Setup guide

Set up Metricool 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 Metricool 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 Metricool 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 Metricool. 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

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Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

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One

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Common questions about Metricool MCP in Vercel AI SDK

Install `@ai-sdk/mcp` and initialize the MCP client with your Vinkius HTTP endpoint. Pass the tools from `mcpClient.tools()` into `streamText` to let your agent call `get_unified_summary` and stream social metrics directly to your React frontend.

Yes, the MCP client is fully compatible with Edge runtimes. Because Vinkius hosts the actual integration, your edge code stays lightweight while accessing tools like `get_facebook_analytics` and `get_twitter_analytics` without timeout issues.

The SDK executes tool calls sequentially or in parallel based on your model's decisions. When pulling heavy data via `list_published_posts`, configure standard backoff in your fetch options to avoid hitting platform limits.

No, you only need one Vinkius token. The server handles the underlying authentication for all profiles returned by `list_metricool_profiles`, so your code stays clean.

Vinkius runs the server inside an isolated V8 sandbox. Your Metricool credentials and draft posts never persist on disk, and data fetched via `get_profile_details` exists only in memory during the execution of that specific tool call.

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