Cloudinary MCP Server for Vercel AI SDK 8 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Cloudinary 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 Cloudinary, 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 Cloudinary MCP Server
Connect your Cloudinary account to any AI agent and take full control of your media library through natural conversation. Streamline how you manage, optimize, and distribute images and videos natively.
The Vercel AI SDK gives every Cloudinary tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 8 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
- Resource Oversight — List and retrieve details for all media resources including public IDs, formats, and secure URLs natively
- Usage Intelligence — Access core usage and quota reports for storage, bandwidth, and transformations flawlessly
- Asset Logistics — Monitor tags, folders, and transformations used across your media library securely
- Search Management — Perform advanced searches using complex expressions to find specific assets instantly flawlessly
- Automation Logistics — List configured upload presets to ensure consistent asset ingestion flawlessly
- Content Control — Permanently delete unwanted media resources directly from your chat interface flawlessly
The Cloudinary MCP Server exposes 8 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 Cloudinary to Vercel AI SDK via MCP
Follow these steps to integrate the Cloudinary 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 8 tools from Cloudinary and passes them to the LLM
Why Use Vercel AI SDK with the Cloudinary MCP Server
Vercel AI SDK provides unique advantages when paired with Cloudinary 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 Cloudinary integration everywhere
Built-in streaming UI primitives let you display Cloudinary 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
Cloudinary + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Cloudinary MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Cloudinary in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Cloudinary tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Cloudinary capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Cloudinary through natural language queries
Cloudinary MCP Tools for Vercel AI SDK (8)
These 8 tools become available when you connect Cloudinary to Vercel AI SDK via MCP:
delete_media_resource
Permanently delete a media resource from the cloud
get_cloudinary_usage_report
Retrieve core usage and quota information (Storage, Bandwidth, Transformations)
get_media_resource_details
Get detailed information for a specific media resource
list_media_resources
List all media resources (images, videos) in the cloud
list_media_tags
List all tags used in the media library
list_media_transformations
List all named and dynamic transformations
list_upload_presets
List all configured upload presets
search_media_library
Search for resources using a search expression
Example Prompts for Cloudinary in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Cloudinary immediately.
"List all images in my Cloudinary library."
"What is my current Cloudinary storage usage?"
"Search for all MP4 videos uploaded in the last 24 hours."
Troubleshooting Cloudinary MCP Server with Vercel AI SDK
Common issues when connecting Cloudinary to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpCloudinary + Vercel AI SDK FAQ
Common questions about integrating Cloudinary 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 Cloudinary 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 Cloudinary to Vercel AI SDK
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.