QingFlow MCP Server for Vercel AI SDK 10 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect QingFlow through Vinkius and every tool is available as a typed function. ready for React Server Components, API routes, or any Node.js backend.
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Vinkius supports streamable HTTP and SSE.
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 QingFlow, 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 QingFlow MCP Server
Empower your AI agent to orchestrate your business processes with QingFlow, the premier no-code BPM platform for digital transformation. By connecting QingFlow to your agent, you transform complex application management and data orchestration into a natural conversation. Your agent can instantly list your applications, retrieve form schemas, manage records (create, update, delete), and even monitor workflow approval statuses without you ever needing to navigate the technical dashboard. Whether you are managing procurement, HR approvals, or project tracking, your agent acts as a real-time process manager, ensuring your business logic is always executed and optimized.
The Vercel AI SDK gives every QingFlow tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 10 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
- Application Orchestration — List all accessible applications and browse their internal structures.
- Data Management — Manage application records with full support for creating, listing, and granular updates.
- Workflow Monitoring — Check the current status of automated workflows and approval processes for any record.
- Schema Auditing — Retrieve application schemas to understand field structures and widget IDs.
- User Coordination — Access workspace user lists to manage assignments and participation effectively.
The QingFlow MCP Server exposes 10 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 QingFlow to Vercel AI SDK via MCP
Follow these steps to integrate the QingFlow MCP Server with Vercel AI SDK.
Install dependencies
Run npm install @ai-sdk/mcp ai @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the script
Save to agent.ts and run with npx tsx agent.ts
Explore tools
The SDK discovers 10 tools from QingFlow and passes them to the LLM
Why Use Vercel AI SDK with the QingFlow MCP Server
Vercel AI SDK provides unique advantages when paired with QingFlow 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 QingFlow integration everywhere
Built-in streaming UI primitives let you display QingFlow 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
QingFlow + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the QingFlow MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query QingFlow in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate QingFlow tools and return structured JSON responses to any frontend
Chatbots with tool use: embed QingFlow capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with QingFlow through natural language queries
QingFlow MCP Tools for Vercel AI SDK (10)
These 10 tools become available when you connect QingFlow to Vercel AI SDK via MCP:
create_record
Create a new application record
delete_record
Delete an application record
get_app_schema
Get application field schema
get_record_details
Get record detailed data
get_workflow_status
Get record workflow status
list_apps
List all QingFlow applications
list_data
List records in an application
list_users
List workspace users
list_workflows
List application workflows
update_record
Update an existing record
Example Prompts for QingFlow in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with QingFlow immediately.
"List all applications in my QingFlow workspace."
"Show me the records for the 'Asset Management' application."
"What is the approval status for record 'req-9920' in 'Leave Request'?"
Troubleshooting QingFlow MCP Server with Vercel AI SDK
Common issues when connecting QingFlow to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpQingFlow + Vercel AI SDK FAQ
Common questions about integrating QingFlow 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.Connect QingFlow with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect QingFlow to Vercel AI SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.