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Vinkius

Google Cloud Storage Bucket Connector for AI agents.

4 live capabilities

Securely manage cloud files and data in your Google Cloud environment

Live agent request Google Cloud Storage Bucket / Connector

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AI Agent

Why people use Google Cloud Storage Bucket

Google Cloud Storage Bucket File Management for Cloud Storage

With this Connector, that manual cycle disappears. Your AI agent can interact with your bucket directly. It sees the storage as a native file system it can browse, read from, and write to. You just give the command, and the agent handles the upload or retrieval in the background.

  • Claude
  • ChatGPT
  • Gemini
  • Cursor
  • Visual Studio Code
  • Windsurf

What Vinkius changes

You get a secure, isolated cloud storage space for your AI agent to use as its own persistent file system.

Use it from Claude, ChatGPT, Cursor or another AI client you already have.

One account · 5,900+ Connectors

  1. Real-world use case 01

    Automated Log Management

    An AI agent processes daily logs and uses put_object to save a summary while using delete_object to clear the raw data.

  2. Real-world use case 02

    Asset Generation Storage

    A creative agent generates images and saves them to a specific bucket so they can be accessed later by other capabilities.

  3. Real-world use case 03

    Document Analysis Pipeline

    A legal agent uses list_objects to find all contracts in a folder and get_object to read them one by one.

Complete set · 4capabilities

The complete Google Cloud Storage Bucket capability set.

These are the exact actions your AI can choose when you ask it to work with Google Cloud Storage Bucket.

Capability set01 / 01

01—04

4 capabilities in this set.

Part of 4 available through Google Cloud Storage Bucket.

  1. 01 Capability

    Delete object

    Remove a specific file from your bucket. This helps keep your storage clean by letting the agent delete temporary files.

  2. 02 Capability

    Get object

    Read the data inside a file. Use this when your agent needs to analyze a document or fetch a specific configuration.

  3. 03 Capability

    List objects

    See everything inside the bucket. This allows your agent to navigate folders and find the files it needs to work on.

  4. 04 Capability

    Put object

    Upload or overwrite a file in the bucket. This is how your agent saves its memories, generated images, or processed reports.

Set up in minutes

One URL. Then ask Google Cloud Storage Bucket to work.

Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Google Cloud Storage Bucket from the conversation.

Choose your client

Live preview
Advanced clients IDE · CLI

Claude · Web + desktop

Official guide ↗

Connector URL · ready to paste

Streamable HTTP
https://edge.vinkius.com/vk_preview_QhAG95VshubCLwHLxWzs4UBAKrUBhFO0KBJe1tOf/mcp
  1. Step 01

    Open Connectors

    In Claude Web or Claude Desktop, open Settings and choose Connectors.

  2. Step 02

    Add the URL

    Choose Add custom connector, name it Google Cloud Storage Bucket, and paste the URL above.

  3. Step 03

    Turn it on in chat

    Select +, open Connectors, and enable Google Cloud Storage Bucket for the conversation.

Where the request belongs

Work Google Cloud Storage Bucket can move forward.

Built around the request

This is for cloud engineers and AI researchers who need to give an agent access to data without opening up their entire cloud account. It solves the problem of balancing AI productivity with strict security requirements.

01

Cloud Engineer

They use this to give an AI agent access to a specific data bucket for processing without granting broad IAM permissions.

02

AI Researcher

They use this to create a persistent memory bank for their agent to store long-term logs and training data.

03

Backend Developer

They use this to offload file management tasks to an agent while keeping the files in a managed cloud environment.

Build the capability set

Add more capabilities.

Each Connector adds new actions and data without changing how you work.

Browse Connectors
Google Cloud Storage logo
01 12 capabilities

Google Cloud Storage

Manage your GCS buckets and objects. list files, upload data, and audit permissions via AI.

View Connector
Amazon S3 Bucket logo
02 7 capabilities

Amazon S3 Bucket

Single-bucket object storage for AI agents. scoped access to one S3 bucket for secure, focused data operations.

View Connector
Backblaze B2 logo
03 10 capabilities

Backblaze B2

Manage Backblaze B2 Cloud Storage via AI. control buckets, file versions, objects, and access rules autonomously.

View Connector
Amazon S3 logo
04 10 capabilities

Amazon S3

Cloud object storage orchestration. manage buckets, objects, and metadata via AI.

View Connector
Aliyun OSS / 阿里云对象存储 logo
05 10 capabilities

Aliyun OSS / 阿里云对象存储

China's leading object storage service. manage files, buckets, and metadata via AI.

View Connector
Qiniu Cloud logo
06 11 capabilities

Qiniu Cloud

Orchestrate Qiniu Cloud storage. manage buckets, handle file uploads, and monitor CDN performance directly from any AI agent.

View Connector

Bring your own AI

Change the model, client or framework. Keep Google Cloud Storage Bucket connected.

  • Claude
  • ChatGPT
  • Gemini
  • Cursor
  • VS Code
  • Windsurf
  • ZCode
  • Cline
  • Zed
  • Continue
  • Kiro
  • Roo Code
  • Zencoder
  • Goose
  • Void
  • Augment Code
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  • Qodo
  • Tabnine
  • Pieces
  • Sourcegraph Cody
  • JetBrains
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  • Jan
  • LM Studio
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  • Cherry Studio
  • LibreChat
  • TypingMind
  • Chorus
  • 5ire
  • n8n
  • LangChain
  • LlamaIndex
  • CrewAI
  • Vercel AI SDK

Before you connect

Questions about Google Cloud Storage Bucket.

The practical details behind the request, access and result.

Can the Google Cloud Storage Bucket MCP access my whole project?

No, it's designed for scoped access. It only connects to one specific bucket you choose, which keeps the rest of your cloud infrastructure safe.

How do I make sure my agent doesn't delete my production data?

By using this Connector, you limit the agent's permissions to a single bucket. It won't have the ability to see or touch your other buckets or production backups.

Can my agent save its own memories using this?

Yes, your agent can use the bucket as a persistent memory bank by saving and retrieving files between different sessions.

Is this fast enough for large files?

Yes, it uses native Google Cloud integration, so it handles high-performance tasks like uploading and retrieving large objects efficiently.

Do I need to be a cloud expert to use this?

Not at all. Once you've set up the bucket and service account, the AI agent handles all the complex interactions for you.

Can I use this to store images?

Absolutely. It works for any type of file, including images, JSON configs, logs, and large documents.

What happens if the bucket is full?

The Connector will report the error back to your agent, which can then notify you or attempt to clear out old files to make room.

Why limit the agent to a single GCS Bucket?

To enforce zero-trust security. An autonomous AI agent should never have carte blanche to read or delete objects across your entire Google Cloud project.

How does the Service Account authentication work?

The Connector uses the Project ID, Client Email, and Private Key from your GCP Service Account JSON to sign JWT tokens and seamlessly access the GCS REST API.

Can it read binary files?

Currently, the capability returns the raw text content. If you download a binary image, it will be represented as a raw string. It is best used for JSON, Markdown, CSVs, or logs.

One connection away

Give your agent a direct line to Google Cloud Storage Bucket.

Connect Google Cloud Storage Bucket once. Keep it beside 5,900+ managed Connectors when the next task needs more.

Explore every Connector No credit card required · Free tier available