cloud-infrastructureproductivity

Cloudinary

by yoavniran

Access Cloudinary's Upload and Admin APIs to upload, manage, and search your digital assets with powerful media asset ma

Provides direct access to Cloudinary's Upload and Admin APIs for uploading, retrieving, searching, and managing digital media assets in your Cloudinary cloud.

github stars

1

Direct API access to CloudinaryRequires API key setup

best for

  • / Content creators managing media libraries
  • / Developers building media-rich applications
  • / Teams automating asset workflows

capabilities

  • / Upload media files to Cloudinary
  • / Search and retrieve existing assets
  • / Manage digital media metadata
  • / Access Cloudinary Admin API functions

what it does

Connects AI assistants to Cloudinary's cloud storage for uploading and managing images, videos, and other digital media assets.

about

Cloudinary is a community-built MCP server published by yoavniran that provides AI assistants with tools and capabilities via the Model Context Protocol. Access Cloudinary's Upload and Admin APIs to upload, manage, and search your digital assets with powerful media asset ma It is categorized under cloud infrastructure, productivity.

how to install

You can install Cloudinary in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

Cloudinary is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

# Cloudinary MCP Server cloudinary-mcp-server MCP server

npm version

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](https://cloudinary.com/documentation/admin_api) to perform these actions. Not all methods and parameters are supported. More will be added over time. Open an [issue](https://github.com/yoavniran/cloudinary-mcp-server/issues) 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](https://console.cloudinary.com/settings/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`: ```json { "mcpServers": { "cloudinary-mcp-server": { "command": "npx", "args": ["-y", "cloudinary-mcp-server"], "env": { "CLOUDINARY_CLOUD_NAME": "", "CLOUDINARY_API_KEY": "", "CLOUDINARY_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: 1. **upload** - Description: Upload a file (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 2. **delete-asset** - Description: Delete a file (asset) from Cloudinary - Parameters: - `publicId`: The public ID of the asset to delete - `assetId`: The asset ID of the asset to delete 3. **get-asset** - Description: Get the details of a specific file (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 4. **find-assets** - Description: Search for existing files (assets) in Cloudinary with a query expression - 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 5. **get-usage** - Description: Get a report on the status of your product environment usage, including storage, credits, bandwidth, requests, number of resources, and add-on usage - Parameters: - `date`: Optional. The date for the usage report in the format: yyyy-mm-dd. Must be within the last 3 months. Default: the current date

FAQ

What is the Cloudinary MCP server?
Cloudinary is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Cloudinary?
This profile displays 10 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
MCP server reviews

Ratings

4.510 reviews
  • Shikha Mishra· Oct 10, 2024

    Cloudinary is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Piyush G· Sep 9, 2024

    We evaluated Cloudinary against two servers with overlapping tools; this profile had the clearer scope statement.

  • Chaitanya Patil· Aug 8, 2024

    Useful MCP listing: Cloudinary is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Sakshi Patil· Jul 7, 2024

    Cloudinary reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Ganesh Mohane· Jun 6, 2024

    I recommend Cloudinary for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Oshnikdeep· May 5, 2024

    Strong directory entry: Cloudinary surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Dhruvi Jain· Apr 4, 2024

    Cloudinary has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Rahul Santra· Mar 3, 2024

    According to our notes, Cloudinary benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Pratham Ware· Feb 2, 2024

    We wired Cloudinary into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Yash Thakker· Jan 1, 2024

    Cloudinary is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.