How to integrate Cloudinary MCP with Pydantic AI

This guide walks you through connecting Cloudinary to Pydantic AI 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 Pydantic AI 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.

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Cloudinary is a cloud-based platform for managing, uploading, and transforming images and videos. It streamlines media workflows and delivers optimized assets globally.

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Introduction

This guide walks you through connecting Cloudinary to Pydantic AI 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 Pydantic AI 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

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TL;DR

Here's what you'll learn:
  • How to set up your Composio API key and User ID
  • How to create a Composio Tool Router session for Cloudinary
  • How to attach an MCP Server to a Pydantic AI agent
  • How to stream responses and maintain chat history
  • How to build a simple REPL-style chat interface to test your Cloudinary workflows

What is Pydantic AI?

Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications.

Key features include:

  • Type Safety: Built on Pydantic for automatic data validation
  • MCP Support: Native support for Model Context Protocol servers
  • Streaming: Built-in support for streaming responses
  • Async First: Designed for async/await patterns

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.

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:

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

Step-by-step Guide

Step by step09 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account with an active API key
  • Basic familiarity with Python and async programming
2

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.
3

Install dependencies

bash
pip install composio pydantic-ai python-dotenv

Install the required libraries.

What's happening:

  • composio connects your agent to external SaaS tools like Cloudinary
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your agent to Composio's API
  • USER_ID associates your session with your account for secure tool access
  • OPENAI_API_KEY to access OpenAI LLMs
5

Import dependencies

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()
What's happening:
  • We load environment variables and import required modules
  • Composio manages connections to Cloudinary
  • MCPServerStreamableHTTP connects to the Cloudinary MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant
6

Create a Tool Router Session

python
async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Cloudinary
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["cloudinary"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an 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 session.mcp.url is the MCP server URL that your agent will use
7

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
cloudinary_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[cloudinary_mcp],
    instructions=(
        "You are a Cloudinary assistant. Use Cloudinary tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Cloudinary endpoint
  • The agent uses GPT-5 to interpret user commands and perform Cloudinary operations
  • The instructions field defines the agent's role and behavior
8

Build the chat interface

python
# Simple REPL with message history
history = []
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to help you with Cloudinary.\n")

while True:
    user_input = input("You: ").strip()
    if user_input.lower() in {"exit", "quit", "bye"}:
        print("\nGoodbye!")
        break
    if not user_input:
        continue

    print("\nAgent is thinking...\n", flush=True)

    async with agent.run_stream(user_input, message_history=history) as stream_result:
        collected_text = ""
        async for chunk in stream_result.stream_output():
            text_piece = None
            if isinstance(chunk, str):
                text_piece = chunk
            elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                text_piece = chunk.delta
            elif hasattr(chunk, "text"):
                text_piece = chunk.text
            if text_piece:
                collected_text += text_piece
        result = stream_result

    print(f"Agent: {collected_text}\n")
    history = result.all_messages()
What's happening:
  • The agent reads input from the terminal and streams its response
  • Cloudinary API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns
9

Run the application

python
if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • The asyncio loop launches the agent and keeps it running until you exit

Complete Code

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

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()

async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Cloudinary
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["cloudinary"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")

    # Attach the MCP server to a Pydantic AI Agent
    cloudinary_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[cloudinary_mcp],
        instructions=(
            "You are a Cloudinary assistant. Use Cloudinary tools to help users "
            "with their requests. Ask clarifying questions when needed."
        ),
    )

    # Simple REPL with message history
    history = []
    print("Chat started! Type 'exit' or 'quit' to end.\n")
    print("Try asking the agent to help you with Cloudinary.\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "bye"}:
            print("\nGoodbye!")
            break
        if not user_input:
            continue

        print("\nAgent is thinking...\n", flush=True)

        async with agent.run_stream(user_input, message_history=history) as stream_result:
            collected_text = ""
            async for chunk in stream_result.stream_output():
                text_piece = None
                if isinstance(chunk, str):
                    text_piece = chunk
                elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                    text_piece = chunk.delta
                elif hasattr(chunk, "text"):
                    text_piece = chunk.text
                if text_piece:
                    collected_text += text_piece
            result = stream_result

        print(f"Agent: {collected_text}\n")
        history = result.all_messages()

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You've built a Pydantic AI agent that can interact with Cloudinary through Composio's Tool Router. With this setup, your agent can perform real Cloudinary actions through natural language. You can extend this further by:
  • Adding other toolkits like Gmail, HubSpot, or Salesforce
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + Cloudinary for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.
TOOLS

Supported Tools

Every Cloudinary action and event your agent gets out of the box.

Activate Live Stream

Tool to manually activate a Cloudinary live stream.

Create Asset Relations by Asset ID

Tool to add related assets by asset ID.

Create Asset Relations by Public ID

Tool to create relations between assets by public ID.

Create Folder

Tool to create a new asset folder.

Create Image from Text

Tool to create an image from text using Cloudinary's text generation API.

Create Live Stream

Tool to create a new live stream in Cloudinary.

Create Live Stream Output

Tool to create a new live stream output configuration.

Create Metadata Field

Tool to create a new metadata field definition.

Create Metadata Rule

Tool to create a new conditional metadata rule.

Create Multi-Resource Animation

Tool to create an animated image, video, or PDF from a set of images.

Create Slideshow

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

Create Streaming Profile

Tool to create a new adaptive streaming profile in your Cloudinary account.

Create Transformation

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

Create Trigger

Tool to create a new webhook trigger for a specified event type.

Create Upload Mapping

Tool to create a new upload mapping folder and URL template.

Create Upload Preset

Tool to create a new upload preset.

Delete Asset Relations by Asset ID

Tool to delete asset relations by asset ID.

Delete Asset Relations by Public ID

Tool to delete asset relations by public ID.

Delete Derived Resources

Tool to delete derived assets.

Delete Metadata Field Datasource Entries

Tool to delete datasource entries for a specified metadata field.

Delete Folder

Tool to delete an empty asset folder.

Delete Live Stream

Tool to delete a live stream from Cloudinary.

Delete Live Stream Output

Tool to delete a live stream output from Cloudinary.

Delete Metadata Field

Tool to delete a metadata field by external ID.

Delete Metadata Rule

Tool to delete a conditional metadata rule by its ID.

Delete Resources by Asset ID

Tool to delete resources by asset IDs.

Delete Resources by Public ID

Tool to delete Cloudinary resources by public ID, prefix, or all resources.

Delete Resources by Tags

Tool to delete Cloudinary assets by tag.

Delete Streaming Profile

Tool 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 Trigger

Tool to delete a trigger (webhook notification).

Delete Upload Mapping

Tool to delete a folder upload mapping.

Delete Upload Preset

Tool to delete an upload preset from the account.

Destroy Asset

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

Destroy Asset by ID

Tool to delete an asset by its immutable asset ID.

Explicit Resource Update

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

Explode Multi-Page Resource

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

Generate Archive

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

Get Adaptive Streaming Profiles

Tool to list adaptive streaming profiles.

Get Analysis Task Status

Tool to get the status of an analysis task.

Get product environment config details

Tool to get product environment config details.

Get Live Stream

Tool to get details of a single live stream by ID.

Get Live Stream Output

Tool to get details of a single live stream output.

Get Live Stream Outputs

Tool to get a list of live stream outputs.

Get Live Streams

Tool to get a list of live streams from Cloudinary.

Get Metadata Field By ID

Tool to get a single metadata field definition by external ID.

Get Resource by Asset ID

Get Resource by Asset ID

Get Resource by Public ID

Tool to get details of a single resource by public ID.

Get Resources by Asset Folder

Tool to list assets stored directly in a specified folder.

Get Resources by Context

Tool to retrieve assets with a specified contextual metadata key/value.

Get Resources in Moderation

Tool to retrieve assets in a moderation queue by status.

Get Root Folders

Tool to list all root folders in the product environment.

Get Streaming Profile Details

Tool to get details of a single streaming profile by name.

Get Resource Tags

Tool to list all tags used for a specified resource type.

Get Transformation

Tool to retrieve details of a specific transformation.

Get Transformations

Tool to list all transformations (named and unnamed).

List Webhook Triggers

Tool to list all webhook triggers for event types in your environment.

Get Upload Mapping Details

Tool to retrieve details of a single upload mapping by folder.

Get Upload Mappings

Tool to list all upload mappings.

Get Upload Preset

Tool to retrieve details of a single upload preset by name.

Get Usage

Tool to get product environment usage details.

Get Video Views

Tool to get video analytics views from Cloudinary.

Idle Live Stream

Tool to manually idle a Cloudinary live stream.

List Images

Tool to list image assets from Cloudinary.

List Metadata Fields

Tool to list all structured metadata fields defined in your Cloudinary product environment.

List Metadata Rules

Tool to retrieve all conditional metadata rules defined in your Cloudinary account.

List Raw Files

Tool to list raw assets from Cloudinary.

List Resources by Asset IDs

Tool to retrieve multiple resources by their asset IDs.

List Resources by External IDs

Tool to retrieve resources by their external IDs.

List Resources by Tag

Tool to list resources (assets) with a specified tag.

List Resources by Type

Tool to retrieve resources (assets) by resource type and storage type.

List Resource Types

Tool to list all available resource types in your Cloudinary product environment.

List Upload Presets

Tool to list all upload presets configured in the account.

List Video Assets

Tool to list video assets from Cloudinary.

Manage Context Metadata

Tool to add or remove contextual metadata on Cloudinary assets.

Order Metadata Field Datasource

Tool to update ordering of a metadata field datasource.

Ping Cloudinary Servers

Tool to ping Cloudinary servers.

Publish Resources

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

Rename or Move Resource Public ID

Tool to rename an asset's public ID using Cloudinary's rename endpoint.

Reorder Metadata Field

Tool to change the position of a specific metadata field.

Reorder Metadata Fields

Tool to reorder all metadata fields in the product environment.

Restore Metadata Field Datasource Entries

Tool to restore previously deleted datasource entries for a metadata field.

Restore Deleted Resources

Tool to restore deleted Cloudinary resources by public IDs.

Restore Resources by Asset IDs

Tool to restore backed up assets by asset IDs.

Search Assets

Tool to search and filter assets using powerful query expressions.

Search Datasource in Metadata Field

Tool to search datasource values in a metadata field.

Search Folders

Tool to search asset folders with filtering, sorting, and pagination.

Search All Metadata Field Datasources

Tool to search across all metadata field datasources.

Visual Search Assets

Tool to find images in your asset library based on visual similarity or content.

Show Folder

Tool to list sub-folders within a specified folder.

Update Asset Metadata

Tool to populate or update metadata field values on one or more Cloudinary assets.

Update Folder

Tool to rename or move an existing asset folder.

Update Live Stream

Tool to update a live stream's configuration in Cloudinary.

Update Live Stream Output

Tool to modify an existing live stream output configuration.

Update Metadata Field

Tool to update a metadata field definition by external ID.

Update Metadata Field Datasource

Tool to update the datasource (allowed values) for a metadata field.

Update Metadata Rule

Tool to update an existing conditional metadata rule.

Update Resource by Asset ID

Tool to update asset properties by asset ID in Cloudinary.

Update Resource by Public ID

Tool to update asset properties by public ID in Cloudinary.

Update Resource Tags

Tool to add, remove, replace, or remove all tags for one or more Cloudinary assets.

Update Streaming Profile

Tool to modify an existing adaptive streaming profile's configuration.

Update Transformation (v2)

Tool to update the definition of an existing named transformation.

Update Trigger

Tool to update the callback URL of an existing webhook trigger.

Update Upload Mapping

Tool to update an existing upload mapping by changing its remote URL template.

Update Upload Preset

Tool to update an existing upload preset's configuration settings.

Upload Asset

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

Upload File Chunk

Tool to upload a single chunk of a large file to Cloudinary.

Upload File (Auto Detect)

Tool to upload files with automatic resource type detection.

FRAMEWORKS

How to build Cloudinary MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Cloudinary MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Cloudinary MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Cloudinary MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Cloudinary MCP with Claude Cowork

Codex logo

Codex

Use Cloudinary MCP with Codex

OpenClaw logo

OpenClaw

Use Cloudinary MCP with OpenClaw

Hermes logo

Hermes

Use Cloudinary MCP with Hermes

CLI logo

CLI

Use Cloudinary MCP with CLI

Google ADK logo

Google ADK

Use Cloudinary MCP with Google ADK

LangChain logo

LangChain

Use Cloudinary MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Cloudinary MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Cloudinary MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Cloudinary MCP with LlamaIndex

CrewAI logo

CrewAI

Use Cloudinary MCP with CrewAI

FAQ

Frequently asked questions

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.

Yes, you can. Pydantic AI 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.

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.

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.

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

Harsha Gaddipati
Harsha Gaddipati
Co-founder, Slashy

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's immensely helped keep new users on the platform.

Abhi Arya
Abhi Arya
Co-founder, Opennote

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

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Nirman Dave
CEO, Zams

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

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Ryan Yu
Founder, Extra Thursday

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

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Founder & CEO, SwarmZero

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.

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Co-Founder, Ingram Technologies