Can I upload large files directly through this server?

The `upload_object` tool is designed for small to medium text-based content. For very large binary files or production datasets, it is recommended to use the gsutil CLI or the Google Cloud Console to ensure optimal transfer speeds and integrity.

How do I check if a bucket is publicly accessible?

You can use the `list_bucket_acl` or `get_bucket_iam` tools. The AI agent will retrieve the permissions and can identify if roles like 'allUsers' or 'allAuthenticatedUsers' have been granted access.

Can I move files between different buckets?

Yes! Use the `copy_object` tool to copy an object from a source bucket to a destination bucket. To 'move' it, you would typically copy the object first and then use `delete_object` on the source.

Google Cloud Storage MCP Server for OpenAI Agents SDK 12 tools — connect in under 2 minutes

Name: Google Cloud Storage
Availability: InStock
Author: Vinkius

openai.github.io/openai-agents-python/mcp

Built by Vinkius GDPR 12 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Google Cloud Storage through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="Google Cloud Storage Assistant",
            instructions=(
                "You help users interact with Google Cloud Storage. "
                "You have access to 12 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from Google Cloud Storage"
        )
        print(result.final_output)

asyncio.run(main())

Fully ManagedVinkius Servers

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High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Google Cloud Storage MCP Server

Connect your Google Cloud Storage project to your AI agent and streamline your cloud data management. Use natural language to browse buckets, inspect file metadata, manage object lifecycles, and audit security permissions across your global storage infrastructure.

The OpenAI Agents SDK auto-discovers all 12 tools from Google Cloud Storage through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Google Cloud Storage, another analyzes results, and a third generates reports, all orchestrated through Vinkius.

What you can do

Bucket Exploration — List all buckets in your project and retrieve detailed metadata including location and storage class
Object Management — Browse files within buckets using prefixes (folders), view sizes, and delete or copy objects effortlessly
Data Operations — Upload text-based content directly or initiate object copies between buckets via simple commands
Security Auditing — Check Access Control Lists (ACLs) and IAM policies for both buckets and individual objects to ensure compliance
Project Insights — Retrieve service account details and manage HMAC keys for legacy or cross-cloud integrations

The Google Cloud Storage MCP Server exposes 12 tools through the Vinkius. Connect it to OpenAI Agents SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Google Cloud Storage to OpenAI Agents SDK via MCP

Follow these steps to integrate the Google Cloud Storage MCP Server with OpenAI Agents SDK.

Install the SDK

Run pip install openai-agents in your Python environment

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Run the script

Save the code above and run it: python agent.py

Explore tools

The agent will automatically discover 12 tools from Google Cloud Storage

Why Use OpenAI Agents SDK with the Google Cloud Storage MCP Server

OpenAI Agents SDK provides unique advantages when paired with Google Cloud Storage through the Model Context Protocol.

Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

Google Cloud Storage + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the Google Cloud Storage MCP Server delivers measurable value.

Automated workflows: build agents that query Google Cloud Storage, process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents. one queries Google Cloud Storage, another analyzes results, a third generates reports

Data enrichment pipelines: stream data through Google Cloud Storage tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query Google Cloud Storage to resolve tickets, look up records, and update statuses without human intervention

Google Cloud Storage MCP Tools for OpenAI Agents SDK (12)

These 12 tools become available when you connect Google Cloud Storage to OpenAI Agents SDK via MCP:

copy_object

Copy an object within or between buckets

delete_object

Remove an object from a bucket

get_bucket_iam

Get IAM policy for a bucket

get_bucket_metadata

Get metadata for a specific bucket

get_object_metadata

Get metadata for a specific object (file)

get_project_service_account

Check the storage service account for the project

list_bucket_acl

Check bucket permissions

list_buckets

List all buckets in the project

list_hmac_keys

List HMAC keys for a service account

list_object_acl

Check permissions for a specific object

list_objects

List objects within a bucket

upload_object

Upload a new file to a bucket

Example Prompts for Google Cloud Storage in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Google Cloud Storage immediately.

"List all buckets in my Google Cloud project."

"Find all files in bucket 'prod-assets' that start with 'images/2024/'."

"Check who has access to the 'user-uploads-data' bucket."

Troubleshooting Google Cloud Storage MCP Server with OpenAI Agents SDK

Common issues when connecting Google Cloud Storage to OpenAI Agents SDK through the Vinkius, and how to resolve them.

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

Google Cloud Storage + OpenAI Agents SDK FAQ

Common questions about integrating Google Cloud Storage MCP Server with OpenAI Agents SDK.

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.