Cloudinary MCP Servers
by
Provides a suite of Model Context Protocol servers enabling natural‑language control over Cloudinary’s media management, asset handling, environment configuration, structured metadata, AI analysis, and workflow automation.
Cloudinary MCP Servers Overview
What is Cloudinary MCP Servers about?
Cloudinary MCP Servers expose Cloudinary’s full media management capabilities through Model Context Protocol endpoints, allowing large language models and conversational AI to upload, transform, analyze, organize, and automate media assets using natural language commands.
How to use Cloudinary MCP Servers?
- Choose remote or local deployment – remote servers are ready‑to‑use via HTTPS URLs; local servers run on your machine with
npxand the corresponding npm packages. - Configure authentication – set
CLOUDINARY_URLor individualCLOUDINARY_CLOUD_NAME,CLOUDINARY_API_KEY, andCLOUDINARY_API_SECRETenvironment variables. - Add server definitions to your LLM tool configuration (JSON examples are provided for both remote URLs and local
npxcommands). - Invoke the servers from an LLM‑enabled application (e.g., Cursor, Claude) by issuing natural‑language requests such as “upload this image”, “list assets tagged ‘summer’”, or “run a moderation analysis on the video”.
Key features of Cloudinary MCP Servers
- Asset Management – upload, transform, search, tag, organize, and download media assets.
- Environment Config – manage upload presets, transformation settings, streaming profiles, and webhooks.
- Structured Metadata – create custom metadata schemas, validation rules, and searchable fields.
- Analysis – AI‑powered tagging, moderation, captioning, object detection, quality checks, and more.
- MediaFlows – low‑code workflow automation for media pipelines, conditional logic, and notification handling.
- Remote and Local Options – instantly use hosted servers or run them locally for full control.
- Standardized MCP Interface – consistent request/response format across all servers.
Use cases of Cloudinary MCP Servers
- Content creators automate bulk uploads, apply consistent transformations, and generate SEO‑friendly metadata via chat.
- E‑commerce platforms use AI analysis to auto‑tag product images, detect prohibited content, and enrich catalog metadata.
- Marketing teams orchestrate media pipelines (e.g., resize, watermark, publish) with natural‑language workflow definitions.
- Developers integrate media management into custom LLM assistants without writing API calls.
- Moderation services perform real‑time content safety checks and auto‑moderation through conversational prompts.
FAQ from the Cloudinary MCP Servers
Q: Do I need to install anything to use the remote servers? A: No. Remote servers are hosted by Cloudinary; simply configure the URL and authentication.
Q: Can I run multiple servers simultaneously?
A: Yes. Each server runs independently and can be accessed via its own URL or local npx command.
Q: Which authentication method is recommended?
A: Setting the CLOUDINARY_URL environment variable is the most convenient for both remote and local deployments.
Q: Are there any paid features? A: Advanced AI analysis, high‑volume usage, custom metadata fields, and certain transformation capabilities may require a paid Cloudinary plan.
Q: How do I troubleshoot interrupted LLM responses? A: Limit the scope of asset listings, break large requests into smaller steps, and use filtering parameters to keep responses concise.
Cloudinary MCP Servers's README
Cloudinary MCP Servers
Model Context Protocol (MCP) is a new, standardized protocol for managing context between large language models (LLMs) and external systems. This repository provides comprehensive MCP servers for Cloudinary's media management platform, enabling you to use natural language to upload, transform, analyze, and organize your media assets directly from AI applications like Cursor and Claude.
With these MCP servers, you can seamlessly manage your entire media workflow through conversational AI - from uploading and transforming images and videos, to configuring automated processing pipelines, analyzing content with AI-powered tools, and organizing assets with structured metadata. Whether you're building media-rich applications, managing large asset libraries, or automating content workflows, these servers provide direct access to Cloudinary's full suite of media optimization and management capabilities.
The following MCP servers are available for Cloudinary:
| Server Name | Description | GitHub Repository | Remote MCP Server |
|---|---|---|---|
| Asset Management | Upload, manage, and transform your media assets with advanced search and organization capabilities | @cloudinary/asset-management | asset-management SSE |
| Environment Config | Configure and manage your Cloudinary environment settings, upload presets, and transformations | @cloudinary/environment-config | environment-config SSE |
| Structured Metadata | Create, manage, and query structured metadata fields for enhanced asset organization and searchability | @cloudinary/structured-metadata | structured-metadata SSE |
| Analysis | Leverage AI-powered content analysis, moderation, and auto-tagging capabilities for your media assets | @cloudinary/analysis | analysis SSE |
| MediaFlows | Build and manage low-code workflow automations for images and videos with AI-powered assistance | MediaFlows MCP | mediaflows MCP |
Table of Contents
- Documentation
- Installation
- Configuration Examples
- Authentication
- Features by Server
- Need access to more Cloudinary tools?
- Troubleshooting
- Paid Features
- License
Documentation
For detailed guides, tutorials, and comprehensive documentation on using Cloudinary's MCP servers:
- Cloudinary MCP and LLM Tool Documentation - Complete guide to integrating Cloudinary with AI/LLM applications
- MediaFlows MCP Documentation - Setup instructions and guidelines for using the MediaFlows (MCP) server
Installation
Remote MCP Servers (Recommended)
Remote MCP servers are hosted by Cloudinary and ready to use immediately. No local installation required.
Local MCP Servers
Local MCP servers run on your machine using npm packages. Choose this option if you need more control or customization.
Note: You'll need to configure your environment variables (CLOUDINARY_CLOUD_NAME, CLOUDINARY_API_KEY, CLOUDINARY_API_SECRET) with your actual credentials after installation.
Configuration Examples
Remote MCP Servers Configuration
Remote servers are hosted by Cloudinary and accessed via URL:
{
"mcpServers": {
"cloudinary-asset-mgmt-remote": {
"url": "https://asset-management.mcp.cloudinary.com/sse"
},
"cloudinary-env-config-remote": {
"url": "https://environment-config.mcp.cloudinary.com/sse"
},
"cloudinary-smd-remote": {
"url": "https://structured-metadata.mcp.cloudinary.com/sse"
},
"cloudinary-analysis-remote": {
"url": "https://analysis.mcp.cloudinary.com/sse"
},
"mediaflows": {
"url": "https://mediaflows.mcp.cloudinary.com/v2/mcp"
}
}
}
Local MCP Servers Configuration
Local servers run on your machine using npm packages:
Option 1: Using CLOUDINARY_URL environment variable (Recommended)
{
"mcpServers": {
"cloudinary-asset-mgmt": {
"command": "npx",
"args": ["-y", "--package", "@cloudinary/asset-management", "--", "mcp", "start"],
"env": {
"CLOUDINARY_URL": "cloudinary://api_key:api_secret@cloud_name"
}
},
"cloudinary-env-config": {
"command": "npx",
"args": ["-y", "--package", "@cloudinary/environment-config", "--", "mcp", "start"],
"env": {
"CLOUDINARY_URL": "cloudinary://api_key:api_secret@cloud_name"
}
},
"cloudinary-smd": {
"command": "npx",
"args": ["-y", "--package", "@cloudinary/structured-metadata", "--", "mcp", "start"],
"env": {
"CLOUDINARY_URL": "cloudinary://api_key:api_secret@cloud_name"
}
},
"cloudinary-analysis": {
"command": "npx",
"args": ["-y", "--package", "@cloudinary/analysis", "--", "mcp", "start"],
"env": {
"CLOUDINARY_URL": "cloudinary://api_key:api_secret@cloud_name"
}
}
}
}
Option 2: Using individual environment variables
{
"mcpServers": {
"cloudinary-asset-mgmt": {
"command": "npx",
"args": ["-y", "--package", "@cloudinary/asset-management", "--", "mcp", "start"],
"env": {
"CLOUDINARY_CLOUD_NAME": "cloud_name",
"CLOUDINARY_API_KEY": "api_key",
"CLOUDINARY_API_SECRET": "api_secret"
}
}
}
}
Option 3: Using command line arguments
{
"mcpServers": {
"cloudinary-asset-mgmt": {
"command": "npx",
"args": [
"-y", "--package", "@cloudinary/asset-management",
"--",
"mcp", "start",
"--cloud-name", "cloud_name",
"--api-key", "api_key",
"--api-secret", "api_secret"
]
}
}
}
MediaFlows MCP Server Configuration
For MediaFlows, use the following configuration:
{
"mcpServers": {
"mediaflows": {
"url": "https://mediaflows.mcp.cloudinary.com/v2/mcp",
"headers": {
"cld-cloud-name": "cloud_name",
"cld-api-key": "api_key",
"cld-secret": "api_secret"
}
}
}
}
Authentication
When running MCP servers locally, authentication can be configured in several ways:
Option 1: Individual environment variables (Recommended)
export CLOUDINARY_CLOUD_NAME="cloud_name"
export CLOUDINARY_API_KEY="api_key"
export CLOUDINARY_API_SECRET="api_secret"
Option 2: CLOUDINARY_URL environment variable
export CLOUDINARY_URL="cloudinary://api_key:api_secret@cloud_name"
Option 3: Command line arguments
Pass credentials directly as arguments (see configuration examples above)
You can find your Cloudinary credentials in your Cloudinary Console Dashboard under Settings > Security.
Features by Server
Asset Management Server
- Upload and manage media assets (images, videos, raw files)
- Search and organize assets with advanced filtering capabilities
- Handle asset operations and transformations
- Manage folders, tags, and asset relationships
- Generate archives and download links
Environment Config Server
- Configure upload presets and transformation settings
- Manage streaming profiles and webhook notifications
- Set up upload mappings
Structured Metadata Server
- Create and manage structured metadata fields
- Configure conditional metadata rules and validation
- Organize and search metadata configurations
- Handle metadata field relationships and ordering
Analysis Server
- AI-powered content analysis including tagging, moderation, and captioning
- Object detection and recognition with multiple AI models
- Image quality analysis and watermark detection
- Content moderation and safety analysis
- Fashion, text, and anatomy detection capabilities
MediaFlows Server
- Build and manage workflow automations using natural language
- Query existing PowerFlow automations in your environment
- Create conditional logic based on metadata, tags, and asset properties
- Automate asset moderation, approval, and notification workflows
- Debug and understand existing automation configurations
Need access to more Cloudinary tools?
We're continuing to add more functionality to these MCP servers. If you'd like to leave feedback, file a bug or provide a feature request, please open an issue on this repository.
Troubleshooting
"Claude's response was interrupted..."
If you see this message, Claude likely hit its context-length limit and stopped mid-reply. This happens most often on servers that trigger many chained tool calls such as the asset management server with large asset listings.
To reduce the chance of running into this issue:
- Try to be specific, keep your queries concise.
- If a single request calls multiple tools, try to break it into several smaller tool calls to keep the responses short.
- Use filtering parameters to limit the scope of asset searches and listings.
Authentication Issues
Ensure your Cloudinary credentials are correctly configured and have the necessary permissions for the operations you're trying to perform.
Paid Features
Some features may require a paid Cloudinary plan. Ensure your Cloudinary account has the necessary subscription level for the features you intend to use, such as:
- Advanced AI analysis features
- High-volume API usage
- Custom metadata fields
- Advanced transformation capabilities
License
Licensed under the MIT License. See LICENSE file for details.
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Cloudinary MCP Servers's Information
- Author
- cloudinary
- Category
- Cloud Platforms
- License
- MIT License
- Stars
- 3
- Updated
- about 2 months ago
Configuration
{
"mcpServers": {
"cloudinary-asset-mgmt": {
"command": "npx",
"args": [
"-y",
"--package",
"@cloudinary/asset-management",
"--",
"mcp",
"start"
],
"env": {
"CLOUDINARY_URL": "<YOUR_CLOUDINARY_URL>"
}
},
"cloudinary-env-config": {
"command": "npx",
"args": [
"-y",
"--package",
"@cloudinary/environment-config",
"--",
"mcp",
"start"
],
"env": {
"CLOUDINARY_URL": "<YOUR_CLOUDINARY_URL>"
}
},
"cloudinary-structured-metadata": {
"command": "npx",
"args": [
"-y",
"--package",
"@cloudinary/structured-metadata",
"--",
"mcp",
"start"
],
"env": {
"CLOUDINARY_URL": "<YOUR_CLOUDINARY_URL>"
}
},
"cloudinary-analysis": {
"command": "npx",
"args": [
"-y",
"--package",
"@cloudinary/analysis",
"--",
"mcp",
"start"
],
"env": {
"CLOUDINARY_URL": "<YOUR_CLOUDINARY_URL>"
}
}
}
}Configure Clients
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