# Cloudinary Asset Management MCP Server

> Cloudinary Asset Management MCP Server — cloudinary-asset-management-mcp. Use this tool when you need to efficiently manage media assets in Cloudinary, as it enables uploading, searching, transforming, and organizing images and videos through natural language inputs, solving media management and optimization problems. It takes natural language commands as input and outputs managed media assets, streamlining content workflows. Ideal for use cases requiring automated media asset management, such as content creation, e-commerce, and digital marketing.

Canonical page: https://skillsregistry.net/skills/cloudinary-asset-management-mcp  
JSON: https://api.skillsregistry.net/v1/skills/cloudinary-asset-management-mcp

## Description

Enables AI assistants to manage Cloudinary media assets, including uploading, searching, transforming, and organizing images and videos through natural language.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-08-30

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** media
- **Updated:** 2026-08-30

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/ai4reyr9o1)
- **Repository:** <https://github.com/cloudinary/asset-management-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "cloudinary-asset-management-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/cloudinary-asset-management-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/cloudinary-asset-management-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt