How to Use the Berg System CRM MCP in Vercel AI SDK

Q: Can I use Vercel AI SDK to bypass duplicate records in Berg System CRM?

Yes. When calling createnewcustomer, your AI client can pass the forceAdd parameter to bypass duplicate verification. This allows the Vercel AI SDK to force the record creation during live interactive chat sessions.

Q: How do I fetch custom sales fields with this toolset?

Use the getsalescustomfields tool inside your model call. The model inspects the fields returned by the endpoint and maps them to your application's UI state.

Feed real-time financial advisor data directly into your React views with the Vercel AI SDK and Berg System CRM.

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Connect Berg System CRM MCP to Vercel AI SDK

Create your Vinkius account to connect Berg System CRM 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 Berg System CRM with Vercel AI SDK

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Feed live Berg System CRM client profiles to Vercel AI SDK

`get_customer_details` pulls full financial advisor client profiles directly into your edge-rendered UI components. Your application doesn't make the advisor stare at a blank loading spinner while waiting for heavy financial records. Instead, the server fetches the JSON payload and feeds it into the text stream, letting your interface render policy numbers and contact details piece by piece. You can also use `list_crm_customers` to populate dynamic lists during live chat sessions. This MCP Server handles the raw data transport, so your frontend code stays clean while the AI client fills out advisor tables on the fly.

Run edge-compatible insurance policy lookups

`list_insurance_policies` queries active coverage data directly from the edge without hitting cold-start penalties. Vercel AI SDK handles these queries within lightweight Edge Functions running an MCP Server, meaning your advisor dashboard loads in milliseconds. Advisors get immediate access to coverage limits, premium amounts, and policy statuses right when they ask. If the client wants to see physical files, `list_stored_documents` fetches the file names and storage paths in the same execution context. This setup avoids heavy backend roundtrips by letting the Vercel AI SDK present the advisor's document links directly in the conversational stream.

Instantly create corporate client records

`create_new_company` writes new business accounts directly to your sales pipeline during live client onboarding calls. You don't have to build complex form validation logic because the Vercel AI SDK parses the conversational input and structures the API payload. The Berg System CRM validates the parameters and posts them to the endpoint, updating your frontend state instantly. To keep the sales pipeline moving, `list_sales_opportunities` lets your React app display active deals alongside the newly created company profile. This MCP Server integration ensures that your Vercel AI SDK real-time UI always reflects the actual state of your Berg System CRM sales funnel.

Setup guide

Set up Berg System CRM 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 Berg System CRM 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 Berg System CRM 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 Berg System. 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 Berg System CRM MCP in Vercel AI SDK

Install @ai-sdk/mcp and instantiate the client using the Vinkius HTTP URL. Pass the tools from get_customer_details directly into the streamText function. Your React frontend will render the JSON fields as they stream from the server.

Yes. When calling create_new_customer, your AI client can pass the forceAdd parameter to bypass duplicate verification. This allows the Vercel AI SDK to force the record creation during live interactive chat sessions.

Absolutely. The server connects via standard HTTP transport, which runs perfectly inside Vercel's edge runtime. You don't have to worry about heavy Node.js dependencies slowing down your edge middleware.

Use the get_sales_custom_fields tool inside your model call. The model inspects the fields returned by the endpoint and maps them to your application's UI state.

Vinkius runs the server inside an isolated V8 sandbox, preventing any direct access to your underlying environment. Your API tokens for Berg System CRM never touch the frontend, as they are securely injected at the proxy layer.

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