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Cloudinary MCP Server: MCP Integration & AI-Driven Media Optimization

Cloudinary MCP Server: Seamlessly integrate Model Context Protocol with Cloudinary API, optimizing media workflows and boosting AI-driven performance for developers and enterprises." (138字符)

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About Cloudinary MCP Server

What is Cloudinary MCP Server: MCP Integration & AI-Driven Media Optimization?

Cloudinary MCP Server acts as a bridge between AI assistants and your Cloudinary account. It leverages the Model Context Protocol (MCP) to expose Cloudinary's Upload and Admin APIs as actionable tools, enabling automated media management workflows. This server empowers AI systems to programmatically upload, organize, and optimize digital assets while maintaining seamless integration with existing infrastructure.

How to use Cloudinary MCP Server: MCP Integration & AI-Driven Media Optimization?

Install the server component and configure API credentials
Set up MCP compatibility with your AI platform (e.g., Claude Desktop)
Implement API calls for core operations: media uploads, metadata updates, and asset transformations
Trigger automated workflows via AI-driven decisions (e.g., content categorization, image optimization)

Cloudinary MCP Server Features

Key Features of Cloudinary MCP Server: MCP Integration & AI-Driven Media Optimization?

API Abstraction Layer

Translates complex media operations into simple API endpoints for AI systems

Automated Asset Management

Enables programmatic uploads, deletions, and metadata tagging without manual intervention

Intelligent Media Optimization

Applies AI-driven optimizations like format conversion, compression, and responsive resizing

Seamless MCP Integration

Standardized protocol support for smooth communication with AI platforms

Use cases of Cloudinary MCP Server: MCP Integration & AI-Driven Media Optimization?

Automated content moderation using AI-powered classification
Dynamic image generation followed by immediate cloud storage
Smart asset retrieval for personalized user experiences
Real-time media transformations based on user preferences
AI-driven analytics for optimizing storage and delivery costs

Cloudinary MCP Server FAQ

FAQ from Cloudinary MCP Server: MCP Integration & AI-Driven Media Optimization?

How do I get started?

Install the server package, configure your Cloudinary API credentials, and set up MCP endpoints in your AI platform.

Can I customize workflows?

Yes - create custom API endpoints for unique media processing requirements using server-side logic.

What happens if credentials expire?

Implement automatic credential rotation via Cloudinary's API key management features.

How do I report issues?

Open tickets through GitHub Issues for troubleshooting and feature requests.

Content

Cloudinary MCP Server

A Model Context Protocol server that exposes Cloudinary Upload & Admin API methods as tools by AI assistants. This integration allows AI systems to trigger and interact with your Cloudinary cloud.

How It Works

The MCP server:

Makes calls on your behalf to the Cloudinary API
Enables uploading of assets to Cloudinary
Enables management of assets in your Cloudinary cloud

It relies on the Cloudinary API to perform these actions. Not all methods and parameters are supported. More will be added over time.

Open an issue with a request for specific method if you need it.

Benefits

Turn your Cloudinary cloud actions into callable tools for AI assistants
Turn your Cloudinary assets into data for AI assistants

Usage with Claude Desktop

Prerequisites

NodeJS
MCP Client (like Claude Desktop App)
Create & Copy Cloudinary API Key/Secret at: API KEYS

Installation

To use this server with the Claude Desktop app, add the following configuration to the "mcpServers" section of your claude_desktop_config.json:

{
    "mcpServers": {
        "cloudinary-mcp-server": {
            "command": "npx",
            "args": ["-y", "cloudinary-mcp-server"],
            "env": {
                "CLOUDINARY_CLOUD_NAME": "<cloud name>",
                "CLOUDINARY_API_KEY": "<api-key>",
                "CLOUDINARY_API_SECRET": "<api-secret>"
            }
        }
    }
}

CLOUDINARY_CLOUD_NAME - your cloud name
CLOUDINARY_API_KEY - The API Key for your cloud
CLOUDINARY_API_SECRET - The API Secret for your cloud

Tools

The following tools are available:

upload

* Description: Upload an asset to Cloudinary
* Parameters: 
  * `source`: URL, file path, base64 content, or binary data to upload
  * `folder`: Optional folder path in Cloudinary
  * `publicId`: Optional public ID for the uploaded asset
  * `resourceType`: Type of resource to upload (image, video, raw, auto)
  * `tags`: Comma-separated list of tags to assign to the asset

delete-asset

* Description: Delete an asset from Cloudinary
* Parameters: 
  * `publicId`: The public ID of the asset to delete
  * `assetId`: The asset ID of the asset to delete

get-asset

* Description: Get details about a specific asset
* Parameters: 
  * `assetId`: The Cloudinary asset ID
  * `publicId`: The public ID of the asset
  * `resourceType`: Type of asset (image, raw, video)
  * `type`: Delivery type (upload, private, authenticated, etc.)
  * `tags`: Whether to include the list of tag names
  * `context`: Whether to include contextual metadata
  * `metadata`: Whether to include structured metadata

find-assets

* Description: Search for assets in Cloudinary
* Parameters: 
  * `expression`: Search expression (e.g. 'tags=cat' or 'public_id:folder/*')
  * `resourceType`: Resource type (image, video, raw)
  * `maxResults`: Maximum number of results (1-500)
  * `nextCursor`: Next cursor for pagination
  * `tags`: Include tags in the response
  * `context`: Include context in the response

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