How to Use the Ayrshare MCP in Vercel AI SDK

Q: How do I connect Ayrshare to my Vercel AI SDK project?

Install @ai-sdk/mcp and configure the client with your Vinkius endpoint. Pass the tools from createMCPClient directly into generateText or streamText to let your LLM call Ayrshare functions.

Q: Can I stream social media analytics using Ayrshare and Vercel AI SDK?

Yes, you can. When the agent calls getsocialanalytics, the JSON payload streams back to the client, allowing you to render live UI components as the data arrives.

Q: Does the Ayrshare MCP Server support multi-profile setups in Vercel AI SDK?

You can manage multiple profiles using listprofiles and createprofile. The agent switches context by passing the correct profile identifiers to the active tools.

Stream social media posts and live analytics directly into your Next.js UI using the Vercel AI SDK.

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Connect Ayrshare MCP to Vercel AI SDK

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

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Build real-time social dashboards with Vercel AI SDK

The `get_social_analytics` tool lets you fetch profile-level engagement metrics and render them instantly. Because Vercel AI SDK streams responses, your users watch the charts populate live instead of staring at a blank loading screen. This MCP Server handles the raw API data and pipes it straight to your React components. You can also trigger `get_post_analytics` to inspect individual post performance on the fly. Your UI updates on every chunk, giving users immediate feedback on how their content performs across networks.

Instant post publishing without page reloads

The `create_post` tool publishes your content to multiple social networks immediately. By pairing this with Vercel AI SDK's streaming text generation, you let users watch their social copy write itself and go live in one smooth action. If they want to plan ahead, the `schedule_post` tool handles future queueing. This SDK handles the asynchronous state, so your app remains fast and responsive while the server schedules the queue.

Interactive queue management in your UI

The `list_auto_schedules` tool fetches current automated posting times for any connected profile. Your AI client reads this schedule and suggests optimizations based on past engagement history. Users can modify these slots instantly using `set_auto_schedule` or wipe them out with `delete_auto_schedule`. As a result, Vercel AI SDK keeps the local UI state perfectly synced with the backend database.

Setup guide

Set up Ayrshare 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 Ayrshare 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 Ayrshare 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 Ayrshare. 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

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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%

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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 Ayrshare MCP in Vercel AI SDK

Install `@ai-sdk/mcp` and configure the client with your Vinkius endpoint. Pass the tools from `createMCPClient` directly into `generateText` or `streamText` to let your LLM call Ayrshare functions.

Yes, you can. When the agent calls `get_social_analytics`, the JSON payload streams back to the client, allowing you to render live UI components as the data arrives.

You can manage multiple profiles using `list_profiles` and `create_profile`. The agent switches context by passing the correct profile identifiers to the active tools.

No, Vinkius handles the underlying Ayrshare API authentication. Your local frontend code only needs the single Vinkius endpoint token to authorize all requests.

Your social posts, profile credentials, and analytics data run inside an isolated V8 sandbox. Vinkius uses zero-trust architecture, meaning your API tokens are never exposed to the LLM or stored in plain text.

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