Integration
Connect Cloudinary to Google Vertex AI
When New Tagged Resource fires in Cloudinary, your agent runs Analyze Document in Google Vertex AI. Describe the whole flow and it is built, tested on every scenario and kept running.
What the catalog holds today. Ask for anything missing and your agent reads the API documentation and adds it.
Build solutions, not workarounds.
What do you want Cloudinary and Google Vertex AI to do together?
Ask the assistant
Connect your AI client
Give your AI client this address.
https://mcp.apiant.aiAny client that takes a remote MCP server. Nothing to install. Create your free account, then sign in once in your browser.
Set it up in your client
Claude Code
Run this in the directory you want to work in.
claude mcp add --transport http -s project apiant-ai https://mcp.apiant.aiStart Claude Code there, approve the server, and sign in in the browser page it opens.
Claude Code guide (opens in a new tab)Claude, web and desktop
Open Customize, then Connectors, then Add custom connector, and paste the address. On Team and Enterprise an owner adds it first.
Setup guide (opens in a new tab)Cursor
Add the address to your MCP configuration as a server URL. Cursor signs you in in your browser.
Setup guide (opens in a new tab)Zed
Open Settings, then AI, then MCP Servers, then Add Server, then Add Remote Server.
Setup guide (opens in a new tab)Codex and the ChatGPT desktop app
Open Settings, then MCP servers, then Add server, and choose Streamable HTTP. From the terminal, Codex takes the address with its own add command and then signs you in.
Setup guide (opens in a new tab)Any other MCP client
Paste the address where the client asks for a remote MCP server URL, and name the server apiant-ai where it lets you. APIANT's skills reach the client over the same connection.
Setup guide (opens in a new tab)Example flows
What Cloudinary can start in Google Vertex AI
then Analyze Document in Google Vertex AI
Starting points drawn from the triggers and actions in the catalog today. Describe the flow you need, at any depth, and your agent builds it and tests every scenario before it ships.
Everything your agent can do with Cloudinary and Google Vertex AI
Triggers and actions 2 triggers · 16 actions
- New Tagged Resource
Triggers when a new resource is uploaded and is tagged with a given tag.
- New Uploaded Resource
Triggers when a new resource is uploaded.
- Get Usage Report
Creates a report on the status of your Cloudinary account usage details, including storage, bandwidth, requests, number of resources, and add-on usage.
- Transform Resource
Creates a Cloudinary URL that can be used to transform, manipulate, and share the resource.
- Upload Resource
Uploads a new resource to your Cloudinary account.
- Upload Resource (Advanced)
Uploads a new resource to your Cloudinary account. This advanced action includes additional upload parameters.
- Analyze Document
Analyzes a document (PDF, image, or text file) using Gemini Vision to extract insights, summaries, or structured data.
- Analyze Text Sentiment
Analyzes text for positive or negative sentiment.
- Classify Text
Classify some text from amongst a list of categories.
- Conversation
Sends a chat message, optionally storing messages as you go.
- Count Tokens
Returns how many tokens a prompt uses for a Gemini model on Vertex AI.
- Generate Code
Generates, explains, refactors, debugs, or converts code using AI. Supports multiple programming languages.
- Generate Embeddings
Generates vector embeddings for text. Useful for semantic search, RAG, and similarity comparisons.
- Generate Image
Generates an image from a prompt.
- Send Prompt
Sends a prompt and generates a completion.
- Summarize Text
Summarizes text.
- Translate Text
Translates text between languages using AI with support for different tones and styles.
- Write an Email
Writes the content of an email based on your provided prompt for use in a subsequent step.
No trigger or action matches that. Ask your agent to add it: it reads the API documentation and builds what you describe.
Each app on its own
Reviews
What our customers say
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Questions
Cloudinary and Google Vertex AI, answered
What can start an automation from Cloudinary?
Any of Cloudinary's 2 triggers in the catalog, including New Tagged Resource and New Uploaded Resource. Describe the moment in plain language and your agent picks the right one.
What can your agent do in Google Vertex AI when something happens in Cloudinary?
Any of Google Vertex AI's 12 actions, including Send Prompt, Analyze Document, Analyze Text Sentiment and Classify Text. Your agent maps the data both ways and tests every scenario before it ships.
Can it also run from Google Vertex AI to Cloudinary?
Google Vertex AI has no triggers in the catalog today, so automations start in Cloudinary. If you need the other direction, ask: your agent reads Google Vertex AI's API documentation and adds it.
Do I have to build a connector for Cloudinary or Google Vertex AI?
No. Both are in the catalog with their triggers and actions. You describe the automation; your agent builds it, tests every scenario and keeps it running.
What happens when something fails?
Your agent works that out for you. It plans the failure paths along with the happy path, then tests every scenario before it ships.
Is there a free plan?
Yes. Every plan includes the agent, including free, and building from your own AI client spends no assistant credits.