ChatFly MCP Server for Vercel AI SDKGive Vercel AI SDK instant access to 7 tools to Chat, Create Bot, Get Bot, and more
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect ChatFly 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 ChatFly app connector for Vercel AI SDK is a standout in the Customer Support category — giving your AI agent 7 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 ChatFly, 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 ChatFly MCP Server
Connect your ChatFly account to any AI agent and take full control of your custom chatbot orchestration and automated knowledge ingestion workflows through natural conversation.
The Vercel AI SDK gives every ChatFly tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 7 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
- Bot Orchestration — Create and manage multiple high-fidelity AI chatbot instances programmatically, including configuring welcome messages and internal metadata
- Knowledge Ingestion — Programmatically train your bots by uploading website URLs and documents to coordinate an accurate, data-driven knowledge base
- Real-Time Interaction — Send messages and retrieve AI responses from specific bots to test performance or integrate chat into custom business applications
- Source Management — Access and monitor your complete directory of data sources (URLs, docs) to oversee the information feeding your digital assistants
- Operational Monitoring — Track chatbot performance, session histories, and account-level status directly through your agent for instant reporting
The ChatFly MCP Server exposes 7 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 7 ChatFly tools available for Vercel AI SDK
When Vercel AI SDK connects to ChatFly through Vinkius, your AI agent gets direct access to every tool listed below — spanning chatbot-builder, conversational-ai, lead-qualification, 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.
Interact with a chatbot
Provide name and welcome message. Create a new chatbot
Get details of a specific bot
List all chatbots
List data sources for a bot
Update an existing bot
Add a knowledge source to a bot
Connect ChatFly to Vercel AI SDK via MCP
Follow these steps to wire ChatFly 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 ChatFly MCP Server
Vercel AI SDK provides unique advantages when paired with ChatFly 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 ChatFly integration everywhere
Built-in streaming UI primitives let you display ChatFly 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
ChatFly + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the ChatFly MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query ChatFly in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate ChatFly tools and return structured JSON responses to any frontend
Chatbots with tool use: embed ChatFly capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with ChatFly through natural language queries
Example Prompts for ChatFly in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with ChatFly immediately.
"List all my available chatbots in ChatFly."
"Train 'bot_1' by ingesting 'https://vinkius.com/faq'."
"Ask 'bot_1': 'What are your support hours?'."
Troubleshooting ChatFly MCP Server with Vercel AI SDK
Common issues when connecting ChatFly to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpChatFly + Vercel AI SDK FAQ
Common questions about integrating ChatFly 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.