Flow XO MCP Server for Vercel AI SDK 12 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Flow XO through the 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 Flow XO, 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 Flow XO MCP Server
Connect your Flow XO account to any AI agent and automate your chatbot interactions and messaging workflows through the Model Context Protocol (MCP). Flow XO is a versatile platform for building and managing chatbots across various channels like Slack, Telegram, and the web. Now, you can manage your automation flows, oversee chatbot users, and trigger webhook-based workflows directly through natural conversation.
The Vercel AI SDK gives every Flow XO tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 12 tools through the 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 Management — List all your chatbot flows and toggle their active status (enable/disable) instantly.
- User Oversight — Access your end-user database, fetch detailed profiles, and create or update user records.
- Direct Messaging — Send push messages directly to users via their unique response paths from your chat interface.
- Webhook Triggers — Push data payloads to Flow XO webhook trigger URLs to start automated sequences remotely.
- Interaction History — Retrieve the message history for specific users to understand past bot engagements.
- Platform Connectivity — List all connected bot accounts and platforms (Slack, Messenger, etc.) for better integration context.
- Automation Analytics — Fetch high-level usage summaries and performance metrics for your chatbot environment.
The Flow XO 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.
How to Connect Flow XO to Vercel AI SDK via MCP
Follow these steps to integrate the Flow XO 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 12 tools from Flow XO and passes them to the LLM
Why Use Vercel AI SDK with the Flow XO MCP Server
Vercel AI SDK provides unique advantages when paired with Flow XO 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 Flow XO integration everywhere
Built-in streaming UI primitives let you display Flow XO 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
Flow XO + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Flow XO MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Flow XO in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Flow XO tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Flow XO capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Flow XO through natural language queries
Flow XO MCP Tools for Vercel AI SDK (12)
These 12 tools become available when you connect Flow XO to Vercel AI SDK via MCP:
create_user
Register a new user
get_automation_analytics
Get usage summary
get_user_details
Get user profile
list_bot_accounts
). List platform accounts
list_broadcasts
List sent broadcasts
list_chatbot_users
List all end users
list_user_history
List user messages
list_workflows
List automation flows
send_push_message
Send a push message
toggle_workflow
Enable/Disable a flow
trigger_webhook
Trigger flow via webhook
update_user
Update user metadata
Example Prompts for Flow XO in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Flow XO immediately.
"List all my Flow XO chatbot users."
"Disable the workflow 'Old Customer Survey'."
"Send a push message to path 'abc/123': 'Your order has been shipped!'."
Troubleshooting Flow XO MCP Server with Vercel AI SDK
Common issues when connecting Flow XO to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpFlow XO + Vercel AI SDK FAQ
Common questions about integrating Flow XO 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 Flow XO 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 Flow XO to Vercel AI SDK
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.