Integration
Connect Pcloud to Google Vertex AI
When New file fires in Pcloud, 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 Pcloud and Google Vertex AI to do together?
Ask the assistant
Connect your AI client
Give your AI client this address.
https://mcp.apiant.aiOne connection does both: ask your client to act in an app once, or have it build an automation that keeps running. Any 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 Pcloud can start in Google Vertex AI
When New file in Pcloud
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 Pcloud and Google Vertex AI
Triggers and actions 1 trigger · 25 actions
- New file
Triggers when a new file appears in the chosen pCloud folder.
- Add folder
Creates a new folder in pCloud, inside a parent folder or at a given path.
- Add public link for file
Creates a public link to a file in pCloud and returns the link and its code.
- Copy file
Copies a file to another folder or path in your pCloud drive and returns the new file's details.
- Delete file
Deletes a file from pCloud, identified by its file id or path.
- Delete folder
Deletes an empty folder in pCloud by its id or path and returns the deleted folder's details.
- Get file
Returns the details of a file in pCloud, such as its name, path, size and content type.
- Get file download link
Returns a temporary download link for a pCloud file, along with when the link expires.
- Get user info
Returns the connected pCloud user's account details: email, verification and premium status, language, and storage quota usage.
- List folder contents
Returns the files and subfolders inside a pCloud folder, optionally the whole tree.
- List public links
Returns all of the current user's public links to files and folders, with download and traffic counts.
- Update file
Renames a file and/or moves it to another folder in pCloud. Returns the updated file's details.
- Update folder
Renames and/or moves a folder in pCloud and returns the updated folder's details.
- Upload file
Uploads a file from a URL into a pCloud folder and returns the new file's details.
- 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
Pcloud and Google Vertex AI, answered
What can start an automation from Pcloud?
Any of Pcloud's 1 trigger in the catalog, including New file. 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 Pcloud?
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 Pcloud?
Google Vertex AI has no triggers in the catalog today, so automations start in Pcloud. 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 Pcloud 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.
Can my AI client use Pcloud and Google Vertex AI without building an automation?
Yes. With your AI client connected to APIANT, ask it to do something in either app once and it runs that action on the spot. Ask for an automation and your agent builds it, tests every scenario and keeps it running. One connection covers both.
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.