ByteNite 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 ByteNite 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 ByteNite, 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 ByteNite MCP Server
Connect your ByteNite account to any AI agent and orchestrate your video encoding workflows, distributed computing tasks, and media processing through natural conversation.
The Vercel AI SDK gives every ByteNite 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
- Encoding Oversight — List all video encoding jobs and retrieve detailed metadata, progress, and output URLs.
- Job Automation — Trigger new encoding tasks using pre-defined templates directly from your workspace.
- Template Management — List all available encoding templates to ensure consistent video quality across your projects.
- App Ecosystem — Access and list available apps within the ByteNite ecosystem for specialized processing tasks.
- System Monitoring — Retrieve real-time system information and health status of the ByteNite infrastructure.
- Account Statistics — Access your profile statistics and storage bucket configurations straight from your workspace.
The ByteNite 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 ByteNite to Vercel AI SDK via MCP
Follow these steps to integrate the ByteNite 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 ByteNite and passes them to the LLM
Why Use Vercel AI SDK with the ByteNite MCP Server
Vercel AI SDK provides unique advantages when paired with ByteNite 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 ByteNite integration everywhere
Built-in streaming UI primitives let you display ByteNite 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
ByteNite + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the ByteNite MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query ByteNite in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate ByteNite tools and return structured JSON responses to any frontend
Chatbots with tool use: embed ByteNite capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with ByteNite through natural language queries
ByteNite MCP Tools for Vercel AI SDK (10)
These 10 tools become available when you connect ByteNite to Vercel AI SDK via MCP:
create_encoding_job
Start a new video encoding job
get_account_info
Retrieve core account/profile statistics
get_app
Get details of a specific app
get_encoding_job
Get details and progress of a specific encoding job
get_system_info
Retrieve core system information and health
get_template
Get details of a specific encoding template
list_apps
List all available apps in the ByteNite ecosystem
list_encoding_jobs
List all video encoding jobs
list_storage_buckets
List all configured storage buckets
list_templates
List all encoding templates
Example Prompts for ByteNite in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with ByteNite immediately.
"List all my current video encoding jobs in ByteNite."
"Show the available encoding templates."
"Encode video https://example.com/source.mp4 using template temp_123."
Troubleshooting ByteNite MCP Server with Vercel AI SDK
Common issues when connecting ByteNite to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpByteNite + Vercel AI SDK FAQ
Common questions about integrating ByteNite 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 ByteNite 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 ByteNite to Vercel AI SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.