How to Use the Kissflow MCP in Vercel AI SDK

Q: How do I connect the Kissflow MCP Server to Vercel AI SDK?

Install ai and @ai-sdk/mcp. Use createMCPClient with an HTTP transport URL pointing to your Vinkius endpoint. Then pass mcpClient.tools() to your generateText or streamText function.

Q: Can Vercel AI SDK stream Kissflow process items in real-time?

Yes. When the agent calls listprocessitems, the SDK streams the tool execution results directly to your React or Next.js frontend. Users see the workflow data appear immediately.

Connect Kissflow to your Vercel AI SDK frontend and stream live workflow data straight into your React components.

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Connect Kissflow MCP to Vercel AI SDK

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

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Stream Kissflow MCP Server Data

`list_processes` and `list_process_items` let your Vercel AI SDK frontend pull active workflow states instantly. You don't have to wait for a heavy REST payload to resolve before showing the user what is happening. The user asks for their pending approvals, and your Next.js app streams the results directly to the screen. They see the exact status of their requests render line by line.

Render Master Data Tables Live

`list_datasets` and `list_dataset_items` feed central master data straight to your Vue or Svelte interfaces. Your agent queries these reference tables the moment the user types a prompt. Instead of building custom API routes to handle dataform lookups, the MCP connection handles it. The AI client grabs the required records and pushes them to the UI components without missing a beat.

Query User Groups On Demand

`list_users` and `list_groups` pull directory information exactly when your application needs it. You can build internal dashboards where managers ask natural language questions about team structures. The AI fetches the requested profiles using `get_user_details` and streams the contact info back. No loading spinners. Just immediate answers rendering in your frontend.

Setup guide

Set up Kissflow 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 Kissflow 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 Kissflow 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 Kissflow. 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.

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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 Kissflow MCP in Vercel AI SDK

Install `ai` and `@ai-sdk/mcp`. Use `createMCPClient` with an HTTP transport URL pointing to your Vinkius endpoint. Then pass `mcpClient.tools()` to your `generateText` or `streamText` function.

Yes. When the agent calls `list_process_items`, the SDK streams the tool execution results directly to your React or Next.js frontend. Users see the workflow data appear immediately.

It absolutely works on the edge. You can deploy your application globally and still maintain a fast connection to your dataforms. Just remember to call `mcpClient.close()` when the execution finishes.

Vinkius handles the heavy lifting for auth. You just need your single endpoint token. Pass it into the HTTP transport configuration when setting up your MCP client.

Your data never trains external models. When your agent accesses user IDs via `get_user_details` or pulls form entries from `list_dataform_items`, the V8 Isolate Sandbox destroys the environment right after the request. The connection is entirely ephemeral.

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