How to Use the AirMatch Pro MCP in Vercel AI SDK

Q: Can I stream AirMatch Pro proposal drafts in real-time using Vercel AI SDK?

Yes, by passing createproposal to the Vercel AI SDK streaming helper, the text-generation model outputs the AirMatch Pro proposal details as they generate. Your UI renders the draft markdown live on the page.

Build live-updating recruitment dashboards using Vercel AI SDK and this MCP Server to stream AirMatch Pro talent pipelines straight to your users.

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Connect AirMatch Pro MCP to Vercel AI SDK

Create your Vinkius account to connect AirMatch Pro 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 AirMatch Pro with Vercel AI SDK

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Stream AirMatch Pro leads directly to React components

The `list_leads` tool pulls active recruitment targets directly into your Vercel AI SDK stream so users see incoming talent profiles render in real-time. Instead of staring at a blank screen, hiring managers watch candidate data populate row-by-row as your Next.js Edge Functions process the AirMatch Pro feed. By combining this with `get_lead`, your Vercel AI SDK interface displays deep-dive candidate histories instantly. You don't have to manage complex loading states because the React UI updates dynamically as each chunk of data arrives from the AirMatch Pro API.

Real-time estimate generation via MCP Server tools

The `list_estimates` tool lets your Vercel AI SDK application fetch and display billing options instantly inside Next.js or Svelte frontends. When a recruiter requests pricing options, the Vercel AI SDK handles the tool call behind the scenes, feeding live AirMatch Pro cost breakdowns directly to the client screen. If a client wants to lock in a price, your React app calls `create_proposal` over the active Vercel AI SDK stream. The user gets immediate visual confirmation of the new AirMatch Pro contract draft without waiting for a full page refresh.

Live status checking for AirMatch Pro pipelines

The `check_airmatch_status` tool verifies your connection health so the Vercel AI SDK frontend can display an active indicator before running complex queries. If a network blip occurs, the Vercel AI SDK catches it early, keeping your AirMatch Pro users informed instead of leaving them with a broken UI. Pairing this with `get_profile` lets you render personalized AirMatch Pro recruiter dashboards on the fly using Next.js. Your application retrieves user preferences and system health in a single, fast Vercel AI SDK streaming cycle.

Setup guide

Set up AirMatch Pro 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 AirMatch Pro 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 AirMatch Pro 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 AirMatch Pro. 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 AirMatch Pro MCP in Vercel AI SDK

Use the Vercel AI SDK's built-in fetch options to throttle requests before calling AirMatch Pro's `list_leads` tool. This keeps your Edge Functions running smoothly without hitting API ceilings.

Yes, by passing `create_proposal` to the Vercel AI SDK streaming helper, the text-generation model outputs the AirMatch Pro proposal details as they generate. Your UI renders the draft markdown live on the page.

Configure your Vinkius endpoint token inside your Next.js environment variables to grant Vercel AI SDK access. The SDK passes this single token to access all ten AirMatch Pro recruitment and sales tools over MCP.

The AirMatch Pro server runs in a secure sandbox, allowing your Vercel AI SDK edge routes to make lightweight HTTP calls to the endpoint. It avoids bulky SDK dependencies, keeping your Edge Function cold starts near zero.

Your AirMatch Pro proposals and lead details are processed in an ephemeral sandbox that never stores your business data. Vinkius routes the Vercel AI SDK requests directly through isolated V8 runtimes, keeping your hiring pipelines confidential.

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