SproutVideo MCP Server for Vercel AI SDKGive Vercel AI SDK instant access to 11 tools to Create Playlist, Delete Video, Get Account, and more
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect SproutVideo 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 SproutVideo app connector for Vercel AI SDK is a standout in the Productivity category — giving your AI agent 11 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 SproutVideo, 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 SproutVideo MCP Server
Connect your SproutVideo account to any AI agent and simplify your video hosting and content management through natural conversation.
The Vercel AI SDK gives every SproutVideo tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 11 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
- Video Management — List all hosted videos, retrieve detailed metadata, and monitor playback stats and plays
- Playlist Control — Query and manage video playlists to organize your content delivery
- Metadata Automation — Update video titles, descriptions, and tags programmatically directly from your agent
- Cleanup & Maintenance — Delete old or redundant videos and manage your storage usage
- Operational Insights — Query video tags to understand your library structure and content distribution
The SproutVideo MCP Server exposes 11 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 11 SproutVideo tools available for Vercel AI SDK
When Vercel AI SDK connects to SproutVideo through Vinkius, your AI agent gets direct access to every tool listed below — spanning video-hosting, video-cms, streaming, 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.
Create a new video playlist
Delete a video
Get account information and usage
Get details for a specific playlist
Get analytics for a specific video
Get details for a specific video
List all video folders
List video playlists
List video tags
List SproutVideo videos
Update video details
Connect SproutVideo to Vercel AI SDK via MCP
Follow these steps to wire SproutVideo 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 SproutVideo MCP Server
Vercel AI SDK provides unique advantages when paired with SproutVideo 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 SproutVideo integration everywhere
Built-in streaming UI primitives let you display SproutVideo 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
SproutVideo + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the SproutVideo MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query SproutVideo in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate SproutVideo tools and return structured JSON responses to any frontend
Chatbots with tool use: embed SproutVideo capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with SproutVideo through natural language queries
Example Prompts for SproutVideo in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with SproutVideo immediately.
"List all videos in SproutVideo."
"Show me the video engagement analytics for all published videos with viewer retention data."
"Create a new playlist called Product Tutorials and add the top 5 most viewed tutorial videos."
Troubleshooting SproutVideo MCP Server with Vercel AI SDK
Common issues when connecting SproutVideo to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpSproutVideo + Vercel AI SDK FAQ
Common questions about integrating SproutVideo 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.