How to Use the Loomly MCP in Vercel AI SDK

Q: How do I connect the Loomly MCP Server to my Vercel AI SDK project?

Install the packages using npm install ai @ai-sdk/mcp in your project. Initialize the connection with createMCPClient using your Vinkius HTTP endpoint, then pass the tools from mcpClient.tools() directly to streamText. Always call mcpClient.close() when the execution finishes to prevent memory leaks in Edge Functions.

Q: How does the Vercel AI SDK handle Loomly authentication?

You configure OAuth or API tokens using the authProvider option during the client setup. Vinkius manages the underlying token exchange securely, so your frontend code never handles raw credentials.

Q: Can my users preview media assets before posting?

Yes. Your application uses listmediaassets to pull image and video URLs, which the SDK streams directly into your UI components. Users see the exact media attached to their drafts in real-time.

Build real-time social media dashboards using the Vercel AI SDK to stream live Loomly post edits directly to your users.

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Connect Loomly MCP to Vercel AI SDK

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

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Stream live post drafts to your frontends

The `create_new_post` tool lets your Vercel AI SDK application generate and publish social media drafts directly within a React or Next.js UI. Instead of waiting for a complete API payload, your users watch the post copy, scheduling times, and channels render live on screen as the model writes them. This immediate visual feedback cuts down on manual copy-pasting into social schedulers. By pairing this tool with `list_calendars`, your interface displays available queues instantly, allowing users to select the right channel before the streaming generation even finishes.

Interactive calendar views via MCP Server tools

The `list_calendar_posts` tool retrieves scheduled content queues that your Vercel AI SDK client renders into interactive calendar components. Because this MCP Server runs in a sandboxed environment on Vinkius, you pull live campaign schedules without exposing your master API keys to the client side. Your frontend handles the raw data stream to paint visual timelines in real-time. Combining this with `get_calendar_details` ensures your UI always matches the exact timezone and channel configurations of the target Loomly account.

Live comment feeds with zero loading spinners

The `list_post_interactions` tool pulls incoming comments and replies directly into your streaming chat interface. Your Vercel AI SDK setup feeds these interactions to the model, which drafts replies that stream back to the user for instant approval. You close the loop using `get_post_details` to verify the original context before committing any replies. This eliminates the delay of traditional polling, making community management feel like a live chat app.

Setup guide

Set up Loomly 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 Loomly 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 Loomly 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 Loomly. 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

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

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Real-time monitoring

Live

visibility into every interaction

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

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Loomly MCP in Vercel AI SDK

Install the packages using `npm install ai @ai-sdk/mcp` in your project. Initialize the connection with `createMCPClient` using your Vinkius HTTP endpoint, then pass the tools from `mcpClient.tools()` directly to `streamText`. Always call `mcpClient.close()` when the execution finishes to prevent memory leaks in Edge Functions.

Yes, this integration works perfectly with Edge Functions because it communicates over standard HTTP. The Vercel AI SDK handles the streaming connection efficiently without requiring heavy Node.js runtimes.

You configure OAuth or API tokens using the `authProvider` option during the client setup. Vinkius manages the underlying token exchange securely, so your frontend code never handles raw credentials.

Yes. Your application uses `list_media_assets` to pull image and video URLs, which the SDK streams directly into your UI components. Users see the exact media attached to their drafts in real-time.

All requests run inside isolated V8 sandboxes that destroy themselves immediately after execution. Your social accounts, post drafts, and calendar metadata are never stored or logged on Vinkius servers, ensuring complete zero-trust security.

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