How to Use the Fieldly MCP in Vercel AI SDK

Stream real-time Fieldly construction data directly into your Vercel AI SDK interface without the wait.

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Connect Fieldly MCP to Vercel AI SDK

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

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Perplexity

Live construction data in your UI

Your AI client fetches work items and booking details, pushing results to your frontend as they happen. You don't wait for spinners; the data populates your components the moment `list_work_items` returns the array. This creates a responsive experience where field workers see their schedule update live. Your agent handles the heavy lifting of parsing `get_booking` payloads while your React components render the state updates.

Control Fieldly operations from Edge Functions

Run your operations on the edge by connecting this MCP Server to your Vercel deployment. Trigger `create_work_item` calls directly from your serverless functions to ensure construction tasks start the second an agent confirms the requirement. Your code manages the lifecycle through the Vercel AI SDK, keeping your integration lightweight. You maintain full control over the connection, ensuring that every `get_me` request stays within your defined execution context.

Inventory and billing visibility

Surface article lists and invoice summaries for your users by plugging into the Vercel AI SDK. Your agent pulls data from `list_articles` and `get_invoice` to provide instant answers about project costs and material availability. Everything stays in sync because your UI consumes the stream directly from the tools. You avoid manual data entry, letting the agent bridge the gap between your inventory database and the final invoice report.

Setup guide

Set up Fieldly 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 Fieldly 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 Fieldly transactions",
});

console.log(text);
await mcpClient.close();

Get your connection token →

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Common questions about Fieldly MCP in Vercel AI SDK

Install the MCP client package and point it to your server endpoint. You then pass the tools into your generation function to let the model decide when to call Fieldly methods.

Yes, you manage your own retry logic within your application code. The server provides the tools, and your SDK implementation handles the flow control for high-frequency calls.

Your data remains private to your session. We use ephemeral connections for every request, and your authentication token never leaves the secure environment of your edge function.

Yes, the tool results flow through the same stream as your text responses. The UI updates as soon as the tool returns the data.

You need an endpoint to host the server connection. Once connected, your client-side code interacts with the tools just like any other API call.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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