How to Use the Clientify MCP in Vercel AI SDK

Q: How do I get started with Clientify and the Vercel AI SDK?

Install @ai-sdk/mcp, create the MCP client with your Vinkius endpoint, and pass the tools to generateText or streamText. You'll have Clientify data streaming into your React components in minutes.

Q: Can I filter contacts when using Clientify with the Vercel AI SDK?

The listclientifycontacts tool gets all contacts. You'll need to handle any filtering on the client side within your application's logic after the data streams in.

Q: What's the best way to show deal progress with Clientify and the Vercel AI SDK?

Use listsalespipelines to get the stages, then call listsalesdeals to get the deals themselves. You can then map the deals to their respective stages in your UI for a clear visual pipeline.

Stream Clientify CRM data directly into your Vercel AI SDK app's UI. No more loading spinners.

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Connect Clientify MCP to Vercel AI SDK

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

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Get Live CRM Data in Your UI

Pull Clientify contacts, companies, and deals right into your front end. The Vercel AI SDK streams tool results as they arrive, so your users see data populating in real time. Use `list_clientify_contacts` or `get_deal_details` and watch the UI build itself. This isn't just for lists. You can build interactive components that fetch detailed records on the fly. A user clicks a deal, and `get_deal_details` instantly streams the specifics into a side panel. It feels fast because it is fast.

Audit Sales Activity with this MCP Server

Give your users a window into their sales pipeline. The `list_sales_pipelines` and `list_crm_activities` tools let you build dashboards that show what's happening in Clientify right now. Track calls, emails, and meetings without making users switch tabs. You can also check on your own agent's identity within the CRM. The `get_my_clientify_profile` tool confirms which user account your app is authenticated with. It's a simple way to build trust and show users who's making the changes.

Build Custom Sales Views

Don't just show a generic list of deals. Let users build their own views. Combine `list_sales_deals` with your own UI filters to create custom dashboards inside your Next.js or Svelte app. Because you're working in the front end, you can mix Clientify data with other sources. Pull deals with this MCP server, match them against an internal database, and display a merged view. The AI SDK makes handling the data streams straightforward.

Setup guide

Set up Clientify 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 Clientify 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 Clientify 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 Clientify. 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 Clientify MCP in Vercel AI SDK

Install `@ai-sdk/mcp`, create the MCP client with your Vinkius endpoint, and pass the tools to `generateText` or `streamText`. You'll have Clientify data streaming into your React components in minutes.

The `list_clientify_contacts` tool gets all contacts. You'll need to handle any filtering on the client side within your application's logic after the data streams in.

Use `list_sales_pipelines` to get the stages, then call `list_sales_deals` to get the deals themselves. You can then map the deals to their respective stages in your UI for a clear visual pipeline.

Yes, the Vercel AI SDK and the MCP client are compatible with Vercel Edge Functions. You can run your AI logic close to your users for lower latency.

The server accesses your Clientify contacts, companies, deals, and activity logs. Your connection is secured through Vinkius's ephemeral, zero-trust sandbox, and your unique endpoint token handles all authentication. The data only exists for the duration of the call.

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