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.
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
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.
Ratings
4.5★★★★★10 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.