Workload MCP Server for Vercel AI SDKGive Vercel AI SDK instant access to 13 tools to Check Workload Status, Create Workflow, Disable Workflow, and more
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Workload through Vinkius and every tool is available as a typed function. ready for React Server Components, API routes, or any Node.js backend.
Ask AI about this App Connector for Vercel AI SDK
The Workload app connector for Vercel AI SDK is a standout in the Productivity category — giving your AI agent 13 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
import { createMCPClient } from "@ai-sdk/mcp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";
async function main() {
const mcpClient = await createMCPClient({
transport: {
type: "http",
// Your Vinkius token. get it at cloud.vinkius.com
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
});
try {
const tools = await mcpClient.tools();
const { text } = await generateText({
model: openai("gpt-4o"),
tools,
prompt: "Using Workload, list all available capabilities.",
});
console.log(text);
} finally {
await mcpClient.close();
}
}
main();
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Workload MCP Server
Connect your Workload account to any AI agent and take full control of your business process automation and automated workflow orchestration through natural conversation.
The Vercel AI SDK gives every Workload tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 13 tools through Vinkius and stream results progressively to React, Svelte, or Vue components. works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
What you can do
- Automation Portfolio Orchestration — List and manage your entire high-fidelity database of workflows programmatically, retrieving detailed trigger and action metadata
- Execution Intelligence Architecture — Programmatically query and monitor workflow execution history and success rates to maintain a perfectly coordinated audit trail
- Task & Resource Monitoring — Access real-time status updates for active automations and track task volume directly through your agent for instant reporting
- Metadata Management — Programmatically retrieve high-fidelity workflow IDs and connection statuses to coordinate your organizational productivity ecosystem
- Operational Monitoring — Verify account-level API connectivity and monitor orchestration volume directly through your agent for perfectly coordinated service scaling
The Workload MCP Server exposes 13 tools through the Vinkius. Connect it to Vercel AI SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 13 Workload tools available for Vercel AI SDK
When Vercel AI SDK connects to Workload through Vinkius, your AI agent gets direct access to every tool listed below — spanning workflow-automation, process-orchestration, business-process, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Verify connectivity
Create a workflow
Disable a workflow
Enable a workflow
Get connection details
Get execution details
Get workflow details
List connections
List executions
List executions by workflow
List workflow logs
List workflows
Retry an execution
Connect Workload to Vercel AI SDK via MCP
Follow these steps to wire Workload into Vercel AI SDK. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
npm install @ai-sdk/mcp ai @ai-sdk/openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the script
agent.ts and run with npx tsx agent.tsExplore tools
Why Use Vercel AI SDK with the Workload MCP Server
Vercel AI SDK provides unique advantages when paired with Workload through the Model Context Protocol.
TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box
Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same Workload integration everywhere
Built-in streaming UI primitives let you display Workload tool results progressively in React, Svelte, or Vue components
Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency
Workload + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Workload MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Workload in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Workload tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Workload capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Workload through natural language queries
Example Prompts for Workload in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Workload immediately.
"List all active workflows in my Workload account."
"Show the execution history for the 'Invoice Flow' (ID: wf_123)."
"Check my Workload orchestration metrics for this month."
Troubleshooting Workload MCP Server with Vercel AI SDK
Common issues when connecting Workload to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpWorkload + Vercel AI SDK FAQ
Common questions about integrating Workload MCP Server with Vercel AI SDK.
How does the Vercel AI SDK connect to MCP servers?
createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.Can I use MCP tools in Edge Functions?
Does it support streaming tool results?
useChat and streamText that handle tool calls and display results progressively in the UI.