FlowiseAI MCP Server for Vercel AI SDKGive Vercel AI SDK instant access to 12 tools to Execute Chatflow Prediction, Get Chatflow Details, Get Server Version, and more
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect FlowiseAI 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 FlowiseAI app connector for Vercel AI SDK is a standout in the Friends Mcp category — giving your AI agent 12 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 FlowiseAI, 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 FlowiseAI MCP Server
Connect your FlowiseAI (self-hosted) instance to any AI agent and take full control of your LLM orchestration and RAG workflows through natural conversation.
The Vercel AI SDK gives every FlowiseAI tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 12 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
- Prediction Orchestration — Trigger specific chatflows and retrieve LLM-generated responses programmatically using natural language inputs
- Chatflow Management — List all orchestration flows and retrieve detailed technical structures and metadata to monitor your AI agents
- Vector Intelligence — Programmatically upsert documents or raw data into the vector stores linked to your chatflows to ensure high-fidelity context
- Component Oversight — Access server-wide credentials, custom tools, and global variables to manage your complete Flowise ecosystem
- Operational Visibility — Monitor user feedback, leads, and assistant profiles directly through your agent for instant reporting
The FlowiseAI MCP Server exposes 12 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 12 FlowiseAI tools available for Vercel AI SDK
When Vercel AI SDK connects to FlowiseAI through Vinkius, your AI agent gets direct access to every tool listed below — spanning llm-workflows, rag-pipelines, chatbot-development, 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.
Trigger an LLM flow prediction
Get details for a specific chatflow
Get Flowise server version
List OpenAI-style assistants
List user feedback for a chatflow
List all LLM orchestration flows
List custom tools
List captured leads
List global variables
List configured credentials
List chatflow templates
Push data into a vector store
Connect FlowiseAI to Vercel AI SDK via MCP
Follow these steps to wire FlowiseAI 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 FlowiseAI MCP Server
Vercel AI SDK provides unique advantages when paired with FlowiseAI 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 FlowiseAI integration everywhere
Built-in streaming UI primitives let you display FlowiseAI 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
FlowiseAI + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the FlowiseAI MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query FlowiseAI in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate FlowiseAI tools and return structured JSON responses to any frontend
Chatbots with tool use: embed FlowiseAI capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with FlowiseAI through natural language queries
Example Prompts for FlowiseAI in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with FlowiseAI immediately.
"List all my chatflows in Flowise."
"Execute chatflow 'cf_1' with question: 'How do I reset my password?'"
"Upsert this data into vector store for chatflow 'cf_2': [data]"
Troubleshooting FlowiseAI MCP Server with Vercel AI SDK
Common issues when connecting FlowiseAI to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpFlowiseAI + Vercel AI SDK FAQ
Common questions about integrating FlowiseAI 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.