Cloudinary with Vercel AI SDK

How to integrate Cloudinary MCP with Vercel AI SDK v6

Trusted by

GET STARTED FOR FREE GET A DEMO

30 min · no commitment · see it on your stack

Introduction Also integrate Cloudinary with TL;DR What is Vercel AI SDK What is the Cloudinary MCP server Supported Tools & Triggers Creating MCP Server - Stand-alone vs Composio SDK Step-by-step Guide Complete Code Conclusion How to build Cloudinary MCP Agent with another framework Explore Other Toolkits FAQ

Connect Cloudinary without Auth hassles

We manage OAuth, API Key, token refresh, and scopes, you just build.

Try for Free

Introduction

This guide walks you through connecting Cloudinary to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Cloudinary agent that can create a new folder for event photos, delete derived assets with ids [123,456], set up upload preset with watermarking through natural language commands.

This guide will help you understand how to give your Vercel AI SDK agent real control over a Cloudinary account through Composio's Cloudinary MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Cloudinary with

OpenAI Agents SDK Claude Agent SDK Claude Code Claude Cowork Codex OpenClaw Hermes CLI Google ADK LangChain Mastra AI LlamaIndex CrewAI

TL;DR

Here's what you'll learn:

How to set up and configure a Vercel AI SDK agent with Cloudinary integration
Using Composio's Tool Router to dynamically load and access Cloudinary tools
Creating an MCP client connection using HTTP transport
Building an interactive CLI chat interface with conversation history management
Handling tool calls and results within the Vercel AI SDK framework

What is Vercel AI SDK?

The Vercel AI SDK is a TypeScript library for building AI-powered applications. It provides tools for creating agents that can use external services and maintain conversation state.

Key features include:

streamText: Core function for streaming responses with real-time tool support
MCP Client: Built-in support for Model Context Protocol via @ai-sdk/mcp
Step Counting: Control multi-step tool execution with stopWhen: stepCountIs()
OpenAI Provider: Native integration with OpenAI models

What is the Cloudinary MCP server, and what's possible with it?

The Cloudinary MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Cloudinary account. It provides structured and secure access to your digital asset management system, so your agent can perform actions like organizing folders, creating metadata fields, managing upload presets, and handling asset deletion on your behalf.

Automated folder and asset organization: Easily instruct your agent to create new asset folders or remove empty ones, keeping your Cloudinary library tidy and structured.
Metadata management: Let your agent create custom metadata fields or delete obsolete ones, extending and refining your asset tagging and search capabilities.
Preset and upload mapping creation: Have your agent set up upload presets with specific options or define dynamic folder mappings, automating consistent upload processes across your assets.
Resource and derived asset cleanup: Direct your agent to permanently delete assets by ID or remove unnecessary derived resources, ensuring your storage stays efficient and clutter-free.
Datasource entry management: Ask your agent to inactivate or delete specific datasource entries from metadata fields, keeping your metadata schema accurate and up to date.

Supported Tools & Triggers

Tools

Activate Live StreamTool to manually activate a Cloudinary live stream.

Create Asset Relations by Asset IDTool to add related assets by asset ID.

Create Asset Relations by Public IDTool to create relations between assets by public ID.

Create FolderTool to create a new asset folder.

Create Image from TextTool to create an image from text using Cloudinary's text generation API.

Create Live StreamTool to create a new live stream in Cloudinary.

Create Live Stream OutputTool to create a new live stream output configuration.

Create Metadata FieldTool to create a new metadata field definition.

Create Metadata RuleTool to create a new conditional metadata rule.

Create Multi-Resource AnimationTool to create an animated image, video, or PDF from a set of images.

Create SlideshowTool to create an auto-generated video slideshow from existing Cloudinary assets.

Create Streaming ProfileTool to create a new adaptive streaming profile in your Cloudinary account.

Create TransformationTool to create a new named transformation by assigning a custom name to a set of transformation parameters.

Create TriggerTool to create a new webhook trigger for a specified event type.

Create Upload MappingTool to create a new upload mapping folder and URL template.

Create Upload PresetTool to create a new upload preset.

Delete Asset Relations by Asset IDTool to delete asset relations by asset ID.

Delete Asset Relations by Public IDTool to delete asset relations by public ID.

Delete Derived ResourcesTool to delete derived assets.

Delete Metadata Field Datasource EntriesTool to delete datasource entries for a specified metadata field.

Delete FolderTool to delete an empty asset folder.

Delete Live StreamTool to delete a live stream from Cloudinary.

Delete Live Stream OutputTool to delete a live stream output from Cloudinary.

Delete Metadata FieldTool to delete a metadata field by external ID.

Delete Metadata RuleTool to delete a conditional metadata rule by its ID.

Delete Resources by Asset IDTool to delete resources by asset IDs.

Delete Resources by Public IDTool to delete Cloudinary resources by public ID, prefix, or all resources.

Delete Resources by TagsTool to delete Cloudinary assets by tag.

Delete Streaming ProfileTool to delete a custom streaming profile or revert a built-in profile to original settings.

Delete Transformation (v2)Tool to delete a named transformation from your Cloudinary account.

Delete TriggerTool to delete a trigger (webhook notification).

Delete Upload MappingTool to delete a folder upload mapping.

Delete Upload PresetTool to delete an upload preset from the account.

Destroy AssetTool to permanently destroy a Cloudinary asset/resource by public ID.

Destroy Asset by IDTool to delete an asset by its immutable asset ID.

Explicit Resource UpdateTool to update an existing asset and/or eagerly generate derived transformations using Cloudinary's Explicit API.

Explode Multi-Page ResourceTool to create derived images from multi-page files (PDF, PSD, TIFF, animated GIF) by exploding them into separate images.

Generate ArchiveTool to create an archive (ZIP or TGZ file) containing a set of assets from your Cloudinary environment.

Get Adaptive Streaming ProfilesTool to list adaptive streaming profiles.

Get Analysis Task StatusTool to get the status of an analysis task.

Get product environment config detailsTool to get product environment config details.

Get Live StreamTool to get details of a single live stream by ID.

Get Live Stream OutputTool to get details of a single live stream output.

Get Live Stream OutputsTool to get a list of live stream outputs.

Get Live StreamsTool to get a list of live streams from Cloudinary.

Get Metadata Field By IDTool to get a single metadata field definition by external ID.

Get Resource by Asset IDGet Resource by Asset ID

Get Resource by Public IDTool to get details of a single resource by public ID.

Get Resources by Asset FolderTool to list assets stored directly in a specified folder.

Get Resources by ContextTool to retrieve assets with a specified contextual metadata key/value.

Get Resources in ModerationTool to retrieve assets in a moderation queue by status.

Get Root FoldersTool to list all root folders in the product environment.

Get Streaming Profile DetailsTool to get details of a single streaming profile by name.

Get Resource TagsTool to list all tags used for a specified resource type.

Get TransformationTool to retrieve details of a specific transformation.

Get TransformationsTool to list all transformations (named and unnamed).

List Webhook TriggersTool to list all webhook triggers for event types in your environment.

Get Upload Mapping DetailsTool to retrieve details of a single upload mapping by folder.

Get Upload MappingsTool to list all upload mappings.

Get Upload PresetTool to retrieve details of a single upload preset by name.

Get UsageTool to get product environment usage details.

Get Video ViewsTool to get video analytics views from Cloudinary.

Idle Live StreamTool to manually idle a Cloudinary live stream.

List ImagesTool to list image assets from Cloudinary.

List Metadata FieldsTool to list all structured metadata fields defined in your Cloudinary product environment.

List Metadata RulesTool to retrieve all conditional metadata rules defined in your Cloudinary account.

List Raw FilesTool to list raw assets from Cloudinary.

List Resources by Asset IDsTool to retrieve multiple resources by their asset IDs.

List Resources by External IDsTool to retrieve resources by their external IDs.

List Resources by TagTool to list resources (assets) with a specified tag.

List Resources by TypeTool to retrieve resources (assets) by resource type and storage type.

List Resource TypesTool to list all available resource types in your Cloudinary product environment.

List Upload PresetsTool to list all upload presets configured in the account.

List Video AssetsTool to list video assets from Cloudinary.

Manage Context MetadataTool to add or remove contextual metadata on Cloudinary assets.

Order Metadata Field DatasourceTool to update ordering of a metadata field datasource.

Ping Cloudinary ServersTool to ping Cloudinary servers.

Publish ResourcesTool to publish Cloudinary assets by public IDs, prefix, or tag.

Rename or Move Resource Public IDTool to rename an asset's public ID using Cloudinary's rename endpoint.

Reorder Metadata FieldTool to change the position of a specific metadata field.

Reorder Metadata FieldsTool to reorder all metadata fields in the product environment.

Restore Metadata Field Datasource EntriesTool to restore previously deleted datasource entries for a metadata field.

Restore Deleted ResourcesTool to restore deleted Cloudinary resources by public IDs.

Restore Resources by Asset IDsTool to restore backed up assets by asset IDs.

Search AssetsTool to search and filter assets using powerful query expressions.

Search Datasource in Metadata FieldTool to search datasource values in a metadata field.

Search FoldersTool to search asset folders with filtering, sorting, and pagination.

Search All Metadata Field DatasourcesTool to search across all metadata field datasources.

Visual Search AssetsTool to find images in your asset library based on visual similarity or content.

Show FolderTool to list sub-folders within a specified folder.

Update Asset MetadataTool to populate or update metadata field values on one or more Cloudinary assets.

Update FolderTool to rename or move an existing asset folder.

Update Live StreamTool to update a live stream's configuration in Cloudinary.

Update Live Stream OutputTool to modify an existing live stream output configuration.

Update Metadata FieldTool to update a metadata field definition by external ID.

Update Metadata Field DatasourceTool to update the datasource (allowed values) for a metadata field.

Update Metadata RuleTool to update an existing conditional metadata rule.

Update Resource by Asset IDTool to update asset properties by asset ID in Cloudinary.

Update Resource by Public IDTool to update asset properties by public ID in Cloudinary.

Update Resource TagsTool to add, remove, replace, or remove all tags for one or more Cloudinary assets.

Update Streaming ProfileTool to modify an existing adaptive streaming profile's configuration.

Update Transformation (v2)Tool to update the definition of an existing named transformation.

Update TriggerTool to update the callback URL of an existing webhook trigger.

Update Upload MappingTool to update an existing upload mapping by changing its remote URL template.

Update Upload PresetTool to update an existing upload preset's configuration settings.

Upload AssetTool to upload media assets (images, videos, raw files) to Cloudinary.

Upload File ChunkTool to upload a single chunk of a large file to Cloudinary.

Upload File (Auto Detect)Tool to upload files with automatic resource type detection.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Prerequisites

Before you begin, make sure you have:

Node.js and npm installed
A Composio account with API key
An OpenAI API key

Getting API Keys for OpenAI and Composio

OpenAI API Key

Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
Keep the API key safe.

Composio API Key

Log in to the Composio dashboard.
Navigate to your API settings and generate a new API key.
Store this key securely as you'll need it for authentication.

Install required dependencies

bash

npm install @ai-sdk/openai @ai-sdk/mcp @composio/core ai dotenv

First, install the necessary packages for your project.

What you're installing:

@ai-sdk/openai: Vercel AI SDK's OpenAI provider
@ai-sdk/mcp: MCP client for Vercel AI SDK
@composio/core: Composio SDK for tool integration
ai: Core Vercel AI SDK
dotenv: Environment variable management

Set up environment variables

bash

OPENAI_API_KEY=your_openai_api_key_here
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_user_id_here

Create a .env file in your project root.

What's needed:

OPENAI_API_KEY: Your OpenAI API key for GPT model access
COMPOSIO_API_KEY: Your Composio API key for tool access
COMPOSIO_USER_ID: A unique identifier for the user session

Import required modules and validate environment

typescript

import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Composio } from "@composio/core";
import * as readline from "readline";
import { streamText, type ModelMessage, stepCountIs } from "ai";
import { createMCPClient } from "@ai-sdk/mcp";

const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey,
});

What's happening:

We're importing all necessary libraries including Vercel AI SDK's OpenAI provider and Composio
The dotenv/config import automatically loads environment variables
The MCP client import enables connection to Composio's tool server

Create Tool Router session and initialize MCP client

typescript

async function main() {
  // Create a tool router session for the user
  const session = await composio.create(composioUserID!, {
    toolkits: ["cloudinary"],
  });

  const mcpUrl = session.mcp.url;

What's happening:

We're creating a Tool Router session that gives your agent access to Cloudinary tools
The create method takes the user ID and specifies which toolkits should be available
The returned mcp object contains the URL and authentication headers needed to connect to the MCP server
This session provides access to all Cloudinary-related tools through the MCP protocol

Connect to MCP server and retrieve tools

typescript

const mcpClient = await createMCPClient({
  transport: {
    type: "http",
    url: mcpUrl,
    headers: session.mcp.headers, // Authentication headers for the Composio MCP server
  },
});

const tools = await mcpClient.tools();

What's happening:

We're creating an MCP client that connects to our Composio Tool Router session via HTTP
The mcp.url provides the endpoint, and mcp.headers contains authentication credentials
The type: "http" is important - Composio requires HTTP transport
tools() retrieves all available Cloudinary tools that the agent can use

Initialize conversation and CLI interface

typescript

let messages: ModelMessage[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log(
  "Ask any questions related to cloudinary, like summarize my last 5 emails, send an email, etc... :)))\n",
);

const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: "> ",
});

rl.prompt();

What's happening:

We initialize an empty messages array to maintain conversation history
A readline interface is created to accept user input from the command line
Instructions are displayed to guide the user on how to interact with the agent

Handle user input and stream responses with real-time tool feedback

typescript

rl.on("line", async (userInput: string) => {
  const trimmedInput = userInput.trim();

  if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) {
    console.log("\nGoodbye!");
    rl.close();
    process.exit(0);
  }

  if (!trimmedInput) {
    rl.prompt();
    return;
  }

  messages.push({ role: "user", content: trimmedInput });
  console.log("\nAgent is thinking...\n");

  try {
    const stream = streamText({
      model: openai("gpt-5"),
      messages,
      tools,
      toolChoice: "auto",
      stopWhen: stepCountIs(10),
      onStepFinish: (step) => {
        for (const toolCall of step.toolCalls) {
          console.log(`[Using tool: ${toolCall.toolName}]`);
          }
          if (step.toolCalls.length > 0) {
            console.log(""); // Add space after tool calls
          }
        },
      });

      for await (const chunk of stream.textStream) {
        process.stdout.write(chunk);
      }

      console.log("\n\n---\n");

      // Get final result for message history
      const response = await stream.response;
      if (response?.messages?.length) {
        messages.push(...response.messages);
      }
    } catch (error) {
      console.error("\nAn error occurred while talking to the agent:");
      console.error(error);
      console.log(
        "\nYou can try again or restart the app if it keeps happening.\n",
      );
    } finally {
      rl.prompt();
    }
  });

  rl.on("close", async () => {
    await mcpClient.close();
    console.log("\n👋 Session ended.");
    process.exit(0);
  });
}

main().catch((err) => {
  console.error("Fatal error:", err);
  process.exit(1);
});

What's happening:

We use streamText instead of generateText to stream responses in real-time
toolChoice: "auto" allows the model to decide when to use Cloudinary tools
stopWhen: stepCountIs(10) allows up to 10 steps for complex multi-tool operations
onStepFinish callback displays which tools are being used in real-time
We iterate through the text stream to create a typewriter effect as the agent responds
The complete response is added to conversation history to maintain context
Errors are caught and displayed with helpful retry suggestions

Complete Code

Here's the complete code to get you started with Cloudinary and Vercel AI SDK:

typescript

import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Composio } from "@composio/core";
import * as readline from "readline";
import { streamText, type ModelMessage, stepCountIs } from "ai";
import { createMCPClient } from "@ai-sdk/mcp";

const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey,
});

async function main() {
  // Create a tool router session for the user
  const session = await composio.create(composioUserID!, {
    toolkits: ["cloudinary"],
  });

  const mcpUrl = session.mcp.url;

  const mcpClient = await createMCPClient({
    transport: {
      type: "http",
      url: mcpUrl,
      headers: session.mcp.headers, // Authentication headers for the Composio MCP server
    },
  });

  const tools = await mcpClient.tools();

  let messages: ModelMessage[] = [];

  console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
  console.log(
    "Ask any questions related to cloudinary, like summarize my last 5 emails, send an email, etc... :)))\n",
  );

  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: "> ",
  });

  rl.prompt();

  rl.on("line", async (userInput: string) => {
    const trimmedInput = userInput.trim();

    if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) {
      console.log("\nGoodbye!");
      rl.close();
      process.exit(0);
    }

    if (!trimmedInput) {
      rl.prompt();
      return;
    }

    messages.push({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    try {
      const stream = streamText({
        model: openai("gpt-5"),
        messages,
        tools,
        toolChoice: "auto",
        stopWhen: stepCountIs(10),
        onStepFinish: (step) => {
          for (const toolCall of step.toolCalls) {
            console.log(`[Using tool: ${toolCall.toolName}]`);
          }
          if (step.toolCalls.length > 0) {
            console.log(""); // Add space after tool calls
          }
        },
      });

      for await (const chunk of stream.textStream) {
        process.stdout.write(chunk);
      }

      console.log("\n\n---\n");

      // Get final result for message history
      const response = await stream.response;
      if (response?.messages?.length) {
        messages.push(...response.messages);
      }
    } catch (error) {
      console.error("\nAn error occurred while talking to the agent:");
      console.error(error);
      console.log(
        "\nYou can try again or restart the app if it keeps happening.\n",
      );
    } finally {
      rl.prompt();
    }
  });

  rl.on("close", async () => {
    await mcpClient.close();
    console.log("\n👋 Session ended.");
    process.exit(0);
  });
}

main().catch((err) => {
  console.error("Fatal error:", err);
  process.exit(1);
});

Conclusion

You've successfully built a Cloudinary agent using the Vercel AI SDK with streaming capabilities! This implementation provides a powerful foundation for building AI applications with natural language interfaces and real-time feedback.

Key features of this implementation:

Real-time streaming responses for a better user experience with typewriter effect
Live tool execution feedback showing which tools are being used as the agent works
Dynamic tool loading through Composio's Tool Router with secure authentication
Multi-step tool execution with configurable step limits (up to 10 steps)
Comprehensive error handling for robust agent execution
Conversation history maintenance for context-aware responses

You can extend this further by adding custom error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.

How to build Cloudinary MCP Agent with another framework

OpenAI Agents SDK

Use Cloudinary MCP with OpenAI Agents SDK

Claude Agent SDK

Use Cloudinary MCP with Claude Agent SDK

Claude Code

Use Cloudinary MCP with Claude Code

Claude Cowork

Use Cloudinary MCP with Claude Cowork

Codex

Use Cloudinary MCP with Codex

OpenClaw

Use Cloudinary MCP with OpenClaw

Hermes

Use Cloudinary MCP with Hermes

CLI

Use Cloudinary MCP with CLI

Google ADK

Use Cloudinary MCP with Google ADK

LangChain

Use Cloudinary MCP with LangChain

Mastra AI

Use Cloudinary MCP with Mastra AI

LlamaIndex

Use Cloudinary MCP with LlamaIndex

CrewAI

Use Cloudinary MCP with CrewAI

Explore Other Toolkits

Figma

Oauth2Api Key

Figma is a collaborative interface design tool for teams and individuals. It streamlines design workflows with real-time collaboration and easy sharing.

Abyssale

Api Key

Abyssale is a creative automation platform for generating images, videos, GIFs, PDFs, and HTML5 content programmatically. It streamlines and scales visual content production for marketing, design, and operations teams.

Alttext ai

Api Key

AltText.ai is a service that generates alt text for images automatically. It helps boost accessibility and SEO for your visual content.

TOOLKIT MARKETPLACE

FAQ

What are the differences in Tool Router MCP and Cloudinary MCP?

With a standalone Cloudinary MCP server, the agents and LLMs can only access a fixed set of Cloudinary tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Cloudinary and many other apps based on the task at hand, all through a single MCP endpoint.

Can I use Tool Router MCP with Vercel AI SDK v6?

Yes, you can. Vercel AI SDK v6 fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Cloudinary tools.

Can I manage the permissions and scopes for Cloudinary while using Tool Router?

Yes, absolutely. You can configure which Cloudinary scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Cloudinary data and credentials are handled as safely as possible.

Used by agents from

Never worry about agent reliability

We handle tool reliability, observability, and security so you never have to second-guess an agent action.

Get started for free Get a demo↗

Harsha GaddipatiCo-founder, Slashy

Karan skipped his own birthday party to fix our critical issue. It was 10 pm and he diverted his Waymo to help us instead. This really sets the bar, shows you the commitment you need to have when users rely on your software.

Abhi AryaCo-founder, Opennote

A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it has immensely helped in keeping new users on the platform.

Nirman DaveCEO, Zams

We chose Composio over Pipedream because it delivered depth where it mattered. It supported niche tools and tricky edge cases that other platforms simply ignored. Giving us confidence to scale without compromising.

Ryan YuFounder, Extra Thursday

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down in the complexities of managing agent auth would have been a death sentence for Extra Thursday.

Tomisin JenrolaFounder & CEO, SwarmZero

Before partnering with Composio, adding tool integrations was a slow, resource-intensive process. Each integration could take weeks or months of engineering time, and maintaining them meant constantly keeping up with API changes.

Jerome LeclancheCo-Founder, Ingram Technologies

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

Harsha GaddipatiCo-founder, Slashy

Abhi AryaCo-founder, Opennote

Nirman DaveCEO, Zams

Ryan YuFounder, Extra Thursday

Tomisin JenrolaFounder & CEO, SwarmZero

Jerome LeclancheCo-Founder, Ingram Technologies

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

Harsha GaddipatiCo-founder, Slashy

Abhi AryaCo-founder, Opennote

Nirman DaveCEO, Zams

Ryan YuFounder, Extra Thursday

Tomisin JenrolaFounder & CEO, SwarmZero

Jerome LeclancheCo-Founder, Ingram Technologies

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

How to integrate Cloudinary MCP with Vercel AI SDK v6

Table of Contents

Connect Cloudinary without Auth hassles

Introduction

Also integrate Cloudinary with

TL;DR

What is Vercel AI SDK?

What is the Cloudinary MCP server, and what's possible with it?

Supported Tools & Triggers

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

How the Composio SDK works

Step-by-step Guide

Prerequisites

Getting API Keys for OpenAI and Composio

Install required dependencies

Set up environment variables

Import required modules and validate environment

Create Tool Router session and initialize MCP client

Connect to MCP server and retrieve tools

Initialize conversation and CLI interface

Handle user input and stream responses with real-time tool feedback

Complete Code

Conclusion

How to build Cloudinary MCP Agent with another framework

OpenAI Agents SDK

Claude Agent SDK

Claude Code

Claude Cowork

Codex

OpenClaw

Hermes

CLI

Google ADK

LangChain

Mastra AI

LlamaIndex

CrewAI

Explore Other Toolkits

Figma

Abyssale

Alttext ai

FAQ

What are the differences in Tool Router MCP and Cloudinary MCP?

Can I use Tool Router MCP with Vercel AI SDK v6?

Can I manage the permissions and scopes for Cloudinary while using Tool Router?

How safe is my data with Composio Tool Router?

Used by agents from

Never worry about agent reliability