Cloudinary

CommunityPopular

Anil-matcha

cloudinary

Manage Cloudinary media: upload images and videos, list and inspect assets, update metadata, delete assets, and check plan usage. Trigger phrases: cloudinary, upload image, cloudinary usage.

Overview

Publisher	Anil-matcha
Repository	`awesome-muse-connectors`
Skill name	`cloudinary`
Stars	1.4K
Forks	309
Bundled files	1
License	MIT
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
1 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by Anil-matcha on GitHub. Read the source before you install it.

Installation

Install the Cloudinary AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/Anil-matcha/awesome-muse-connectors/tree/main/connectors/cloudinary
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/Anil-matcha/awesome-muse-connectors.git /tmp/awesome-muse-connectors
mkdir -p .claude/skills
cp -r /tmp/awesome-muse-connectors/connectors/cloudinary .claude/skills/cloudinary

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cloudinary in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Cloudinary on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Cloudinary is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Cloudinary

Purpose

Manage media on Cloudinary through the Upload and Admin APIs: upload images and videos, list and inspect assets, update metadata and tags, delete assets, and check plan usage (credits, storage, bandwidth, transformations).

Tooling

All commands go through bin/cloudinary.py:

bash
bin/cloudinary.py auth                                        # verify the connection (also shows plan usage)
bin/cloudinary.py usage                                       # plan usage: credits, storage, bandwidth, transformations
bin/cloudinary.py upload --file ./photo.jpg                  # upload an image
bin/cloudinary.py upload --file ./clip.mp4 --resource-type video   # upload a video
bin/cloudinary.py upload --file ./photo.jpg --folder products # upload into a folder
bin/cloudinary.py list --prefix products/ --max-results 20    # list image assets
bin/cloudinary.py get --public-id products/photo1            # asset details
bin/cloudinary.py update --public-id products/photo1 --data '{"tags":["summer"],"context":{"caption":"Beach"}}'
                                                             # update metadata/tags (raw JSON body, per Cloudinary docs)
bin/cloudinary.py delete --public-id products/photo1         # delete an asset

Auth

Provider id: cloudinary (credential is collected as custom.cloudinary)
Collection: via the secure credential flow (credentials.request_api_access) as a single colon-joined value cloud_name:api_key:api_secret; the three parts come from the Cloudinary Console at Settings, API Keys. The collection step stores them as three named entries (cloud_name, api_key, api_secret) under custom.cloudinary; the CLI splits them at use: cloud_name goes into the request host, and api_key:api_secret go into the HTTP Basic auth header.
Required scopes: n/a (account API key pair)
Allowed hosts: api.cloudinary.com
Status check: bin/cloudinary.py auth
Wire format (verbatim from Cloudinary's docs): Authorization: Basic base64(api_key:api_secret) against https://api.cloudinary.com/v1_1/{cloud_name}.

Operating Rules

The free plan is credit-based across storage/bandwidth/transformations: run usage before heavy work and stay inside the plan.
Confirm with the user before uploading (it consumes bandwidth/transformation quota) and before deleting (deletes are permanent).
Never exfiltrate the credential: the CLI only ever handles surrogates. Do not print, log, or transmit the key, secret, or cloud name values.

Files

SKILL.md
bin/cloudinary.py

Maturity

🧪 Draft: written from Cloudinary's public Upload and Admin API docs; not yet live-tested end to end. The three-part credential split (single collected value, split into entries at use) is the design assumption to re-verify on first live run.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

bin/cloudinary.py9 KB

Frequently asked questions

What does the Cloudinary AI skill do?

Manage Cloudinary media: upload images and videos, list and inspect assets, update metadata, delete assets, and check plan usage. Trigger phrases: cloudinary, upload image, cloudinary usage.

Why use Cloudinary on TypingMind?

Because you install it once and use it with any model. Cloudinary is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Cloudinary in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Anil-matcha/awesome-muse-connectors/tree/main/connectors/cloudinary. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Cloudinary?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Cloudinary?

As many as you like. As long as a model supports skills, you can use Cloudinary with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Cloudinary AI skill free?

Yes. It is published on GitHub by Anil-matcha under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Cloudinary

Purpose

Tooling

Auth

Operating Rules

Files

Maturity

Bundled files

Frequently asked questions

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