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Orkes Conductor MCP Server for Vercel AI SDK 6 tools — connect in under 2 minutes

Built by Vinkius GDPR 6 Tools SDK

The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Orkes Conductor through Vinkius and every tool is available as a typed function. ready for React Server Components, API routes, or any Node.js backend.

Vinkius supports streamable HTTP and SSE.

typescript
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 Orkes Conductor, list all available capabilities.",
    });
    console.log(text);
  } finally {
    await mcpClient.close();
  }
}

main();
Orkes Conductor
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IAMAccess control
EU AI ActCompliant
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V8 IsolateSandboxed
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<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Orkes Conductor MCP Server

Connect your Orkes Conductor cluster to any AI agent and get full visibility into your workflow orchestration layer — definitions, running instances, task states, and execution history.

The Vercel AI SDK gives every Orkes Conductor tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 6 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

  • Workflow Definitions — List all registered workflow definitions with versions and descriptions, or inspect a specific workflow's graph schema with tasks, operators, and branching logic
  • Task Definitions — List all registered task definitions available for orchestration within your workflows
  • Running Instances — List actively running workflow instances filtered by workflow name to monitor what's currently executing
  • Execution Details — Get deep state details for any workflow execution including input/output mappings, task-by-task trace histories, and exceptions
  • Workflow Search — Search across all workflow executions using Elasticsearch queries, filtering by status, correlation ID, or workflow type

The Orkes Conductor MCP Server exposes 6 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.

How to Connect Orkes Conductor to Vercel AI SDK via MCP

Follow these steps to integrate the Orkes Conductor MCP Server with Vercel AI SDK.

01

Install dependencies

Run npm install @ai-sdk/mcp ai @ai-sdk/openai

02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

03

Run the script

Save to agent.ts and run with npx tsx agent.ts

04

Explore tools

The SDK discovers 6 tools from Orkes Conductor and passes them to the LLM

Why Use Vercel AI SDK with the Orkes Conductor MCP Server

Vercel AI SDK provides unique advantages when paired with Orkes Conductor through the Model Context Protocol.

01

TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box

02

Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same Orkes Conductor integration everywhere

03

Built-in streaming UI primitives let you display Orkes Conductor tool results progressively in React, Svelte, or Vue components

04

Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency

Orkes Conductor + Vercel AI SDK Use Cases

Practical scenarios where Vercel AI SDK combined with the Orkes Conductor MCP Server delivers measurable value.

01

AI-powered web apps: build dashboards that query Orkes Conductor in real-time and stream results to the UI with zero loading states

02

API backends: create serverless endpoints that orchestrate Orkes Conductor tools and return structured JSON responses to any frontend

03

Chatbots with tool use: embed Orkes Conductor capabilities into conversational interfaces with streaming responses and tool call visibility

04

Internal tools: build admin panels where team members interact with Orkes Conductor through natural language queries

Orkes Conductor MCP Tools for Vercel AI SDK (6)

These 6 tools become available when you connect Orkes Conductor to Vercel AI SDK via MCP:

01

get_execution

Get deep state details of a specific Workflow Execution

02

get_workflow_def

Get a specific Workflow Definition explicitly by name

03

list_running

List active, running workflow instances by explicit workflow name

04

list_task_defs

List all explicitly registered Task Definitions via Conductor API

05

list_workflow_defs

List all registered overarching Workflow Definitions via Orkes API

06

search_workflows

Perform an elastic Search across all Workflow executions

Example Prompts for Orkes Conductor in Vercel AI SDK

Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Orkes Conductor immediately.

01

"Show me all registered workflow definitions."

02

"Are there any failed workflows in the last 24 hours?"

03

"How many instances of the order-processing workflow are currently running?"

Troubleshooting Orkes Conductor MCP Server with Vercel AI SDK

Common issues when connecting Orkes Conductor to Vercel AI SDK through the Vinkius, and how to resolve them.

01

createMCPClient is not a function

Install: npm install @ai-sdk/mcp

Orkes Conductor + Vercel AI SDK FAQ

Common questions about integrating Orkes Conductor MCP Server with Vercel AI SDK.

01

How does the Vercel AI SDK connect to MCP servers?

Import createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.
02

Can I use MCP tools in Edge Functions?

Yes. The AI SDK is fully edge-compatible. MCP connections work on Vercel Edge Functions, Cloudflare Workers, and similar runtimes.
03

Does it support streaming tool results?

Yes. The SDK provides streaming primitives like useChat and streamText that handle tool calls and display results progressively in the UI.

Connect Orkes Conductor to Vercel AI SDK

Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.