How to Use the Timeero MCP in Vercel AI SDK

Stream Timeero GPS timesheets and job status directly into your React or Next.js app using the Vercel AI SDK.

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Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers — Included with Plan

Connect Timeero MCP to Vercel AI SDK

Create your Vinkius account to connect Timeero to Vercel AI SDK — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

GDPR Included with Plan

Setup Timeero with Vercel AI SDK

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Claude

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Stream Live Field Timesheets to UI with Vercel AI SDK

Stop making users wait for heavy background syncs when loading Timeero logs. Hook your front-end up to this MCP Server to pull live records directly into your Vercel AI SDK stream. Your AI client can trigger `list_timeero_timesheets` and immediately render the raw hours on screen as they stream in, bypassing slow loading spinners entirely. If a supervisor asks who is currently on the clock, the agent calls `get_timeero_user` to fetch the specific employee profile. The Vercel AI SDK streams this data chunk by chunk, letting you build real-time monitoring dashboards that update instantly with Timeero metrics.

Instant Job and Task Dispatch

Dispatching field crews requires immediate validation inside your Vercel AI SDK interface. Your agent uses this MCP Server to see what projects are active by querying `list_timeero_jobs`. To drill down into specific requirements, the agent invokes `list_timeero_tasks` or gets a specific record via `get_timeero_job` to confirm assignment details, while pulling `get_timeero_task` for individual step instructions. It renders these details inline, giving dispatchers a live feed of operational data without page refreshes. This keeps your Vercel AI SDK application lightweight while keeping field assignments completely accurate.

Verify Schedule and API Health

Before pushing updates, your Vercel AI SDK application needs to verify connection integrity. Your agent runs `check_timeero_status` to ensure the API is responsive before querying `list_timeero_users` to see who is available. It then calls `list_timeero_schedules` to check shifts, getting the exact constraints with `get_timeero_schedule`. If there is a dispute, it pulls the specific log via `get_timeero_timesheet`. This lets managers verify timesheets live in the chat window without leaving their active Vercel AI SDK session.

Setup guide

Set up Timeero 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 Timeero 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 Timeero 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 Timeero. 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.

Connect Timeero now

Real-time monitoring

Live

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%

lower AI costs

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 Timeero MCP in Vercel AI SDK

It streams the JSON array directly from the server. By querying timesheets, the agent pushes data packets to your Next.js frontend as they arrive, rendering them instantly in UI components instead of waiting for the full payload.

Yes. The server runs on Vinkius, and you connect via standard HTTP transports. Your Edge Functions call the endpoint, fetch the tools, and process things like GPS coordinates without hitting timeout limits.

Vinkius manages the API keys securely. You only pass a single bearer token in your configuration, and the platform handles the headers for every request to the Timeero endpoint.

The agent can read schedules to help dispatchers make decisions. It uses scheduling tools to find current shifts, letting your team see who is working without leaving the chat interface.

All location data and timesheets are processed in secure, ephemeral V8 sandboxes via the MCP endpoint. Your API credentials and employee tracking details are never stored on Vinkius, maintaining strict data privacy compliance.

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