Google Cloud Storage MCP. Manage files, audit permissions, delete data via conversation.
Google Cloud Storage MCP lets you manage your entire cloud storage infrastructure through natural language conversation. Use your AI agent to list buckets, inspect file metadata, audit security permissions (IAM/ACLs), and move data—all without navigating the GCP Console. It's full control over GCS objects and buckets, handled by simple commands.
Give Claude and any AI agent real-world access
See a complete list of all buckets in your project, along with their specific location and storage class details.
Browse for objects inside a bucket using prefixes (like folders) to filter down thousands of stored files quickly.
Transfer text-based content or artifacts directly into any specified bucket in the cloud.
Copy files from one bucket to another, or permanently delete specific objects that are no longer needed.
Audit the Access Control Lists (ACLs) and Identity and Access Management (IAM) policies for both entire buckets and individual files.
Get detailed information about the project's service accounts or list keys used for cross-cloud integrations.
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What AI agents can do with Google Cloud Storage MCP with 12 Tools
Use these tools to perform deep cloud operations, including listing buckets, managing object lifecycles, checking access controls, and transferring files through natural language prompts.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Google Cloud Storage MCPCopy Object
Copies a file from one location to another, either within the same bucket or across different buckets.
Delete Object
Permanently removes a specified object (file) from its current bucket.
Get Bucket Iam
Retrieves the full IAM policy that controls who has access to an entire bucket.
Get Bucket Metadata
Gets key information, like creation date and location, for a specific bucket.
Get Object Metadata
Retrieves detailed metadata (size, type, dates) for a single file inside a bucket.
Get Project Service Account
Checks the assigned service account details used by the project's storage resources.
List Bucket Acl
Lists all current permissions and access rules applied to an entire bucket.
List Buckets
Retrieves a list of every single storage bucket available in your project.
List Hmac Keys
Lists the unique HMAC keys associated with a service account for integration...
List Object Acl
Checks and lists all permissions applied only to one specific object (file).
List Objects
Finds and lists all files within a bucket that match a given prefix or folder path.
Upload Object
Transfers a new file from your local environment into an empty or existing cloud bucket.
Security and governance baked right in.
Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on each call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Google Cloud Storage, then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,200+ others, all in one place
- Add new capabilities to your AI anytime you want
- Connections are secured and governed automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog weekly
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Google Cloud Storage. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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The Pain of Manual Console Navigation
Today, managing a major cloud storage project means opening the GCP console. You click into the 'Storage' tab, then navigate to your specific bucket name. To check permissions, you have to find the IAM section, and if that isn't enough, you drill down further into ACLs—it’s a dozen clicks just to answer one simple question: 'Is this public?'
With this MCP, you talk to your agent. You ask, 'What are the access rules for all assets in the staging bucket?' and it returns the full policy immediately. It's like having an expert cloud architect sitting next to you, instantly giving answers instead of sending you through a maze of menus.
Managing Objects with Google Cloud Storage MCP
The manual steps that vanish include opening the console, clicking 'Objects', filtering by prefix, and then checking each file's metadata one by one. You never have to click through folders again just to see what data exists.
You now simply ask your agent to list all objects matching a pattern, and it provides the full list with sizes and dates in plain text. It changes cloud operations from tedious clicking into simple conversation.
What Google Cloud Storage MCP does for your AI
Managing large cloud storage projects usually means spending hours in complex consoles, clicking through nested menus just to check a file size or verify who has access. This MCP changes that. You connect your Google Cloud Storage project, and your AI agent becomes your dedicated administrator. Instead of running API calls manually, you simply ask natural language questions: 'Show me the status of all development buckets' or 'Who can read the user logs in this bucket?' The agent handles the underlying complexity, reading the metadata, checking security policies, and executing operations like uploading new content or copying objects between locations.
It means your AI client doesn't just talk to storage; it acts like a knowledgeable cloud ops specialist. This is how Vinkius makes powerful infrastructure tools accessible directly through conversation.
019d75a8-405b-7147-9eeb-1afd99e2ae94 How to set up Google Cloud Storage MCP
The bottom line is, you get full control over complex cloud storage operations without ever opening a web console.
First, subscribe to this MCP and provide your Google Cloud Project ID along with your OAuth credentials.
Next, complete the required secure authorization flow to grant access to your cloud data within the system.
Finally, start asking your AI agent questions in Claude, Cursor, or any compatible client. It executes commands like listing buckets or checking permissions on demand.
Who uses Google Cloud Storage MCP
This connector is essential for Cloud Engineers who spend too much time manually checking build artifacts. It's perfect for Data Scientists needing to verify file sizes or modification dates across large datasets, and Security Teams that need instant audits of bucket permissions.
Checks if a specific log file or build artifact exists in a staging bucket without logging into the GCP console.
Browses large datasets to verify file sizes and check modification dates using conversational queries.
Audits bucket permissions and public access settings instantly by asking the agent to check ACLs or IAM policies.
Benefits of connecting Google Cloud Storage MCP
Audit compliance instantly: Instead of navigating complex IAM and ACL settings, simply ask the agent to check who has read or write access to a specific bucket using list_bucket_acl. You get an immediate pass/fail report.
Stop manual file checking: Need to know if 'build-v3.zip' exists? Ask your AI client to use list_object_acl and get_object_metadata, getting the status instantly without opening the console.
Efficient data movement: Use copy_object or upload_object to move datasets between staging and production buckets in a single conversational turn. No more multi-step GUI transfers.
Deep security oversight: The agent lets you check project service accounts using get_project_service_account, ensuring that cross-cloud integrations are running with the correct permissions.
Massive time savings for ops teams: Combining list_buckets and list_objects allows your AI client to map out complex data architectures—from finding all assets in 'prod' to locating a specific log file deep within 'logs/2024/'.
Full lifecycle management: Easily control the full object life cycle, whether you need to delete_object obsolete files or copy_object them for archival purposes.
Google Cloud Storage MCP use cases
Verifying compliance before launch
A security team needs to ensure that no sensitive user data is publicly exposed. They ask the agent to check 'user-uploads-data' bucket permissions using list_bucket_acl and get_bucket_iam, confirming public access ('allUsers') is blocked across all objects.
Archiving old datasets
A data scientist needs to move a year's worth of raw logs from 'logs/2023/' to the cold storage archive. They instruct the agent to list_objects for that prefix and then execute copy_object, keeping the original file intact.
Troubleshooting missing assets
A cloud engineer can't find a specific build artifact. Instead of opening the console, they ask the agent to list_objects using a known prefix ('assets/images/') and get_object_metadata to verify the exact file name and size.
Setting up new pipelines
A developer needs to test data flow. They use upload_object to push a dummy configuration file into the staging bucket, then ask list_buckets to confirm the asset is visible and available for downstream processes.
Google Cloud Storage MCP tradeoffs
What to watch out for, and the recommended way to handle each one.
Using generic search terms
A user just searches 'find my data' in the chat. The AI client gets confused because it doesn't know which bucket, prefix, or date range to check.
Always be specific. Use list_objects and provide a clear path: 'list objects in prod-assets-9302 that start with images/2024/' to get precise results.
Assuming permissions are correct
A team member assumes the marketing assets folder is private, but accidentally publishes sensitive content because they never verified access controls.
Before any major upload_object or copy_object action, run list_bucket_acl and get_bucket_iam to confirm that only authorized service accounts have write permissions.
Doing manual object checks
A user has 50 files to check for size or modification date. They open the console, click into every folder, and manually copy-paste data points.
Use get_object_metadata on a list of objects identified by list_objects. The agent pulls all the required metrics in one query.
When to use Google Cloud Storage MCP
You should use this MCP if your workflow involves complex, multi-step data governance: checking who can access what, moving files between different environments (dev to staging), or auditing a large number of assets. You need it when the answer isn't 'yes/no', but requires reading metadata and security policies across multiple buckets.
You don't use this if you just need simple file transfers without checking permissions; for that, a basic sync tool might suffice. Also, if your only task is to write code based on local files—and never touch the cloud environment—you shouldn't use it. This MCP is specifically for controlling and observing data in Google Cloud Storage.
Frequently asked questions about Google Cloud Storage MCP
How do I check permissions on a specific file using Google Cloud Storage MCP? +
Use list_object_acl to check the access rules for any single file. This is much faster than checking the entire bucket's policy if you only care about one item.
Can I list all my buckets using Google Cloud Storage MCP? +
Yes, use list_buckets to retrieve a complete roster of every single bucket in your project. This is the starting point for any large-scale audit or inventory task.
What tool do I use to move files from one storage location to another? +
Use copy_object. This function lets you transfer data between buckets, which is safer than deleting and re-uploading the file manually.
Does Google Cloud Storage MCP handle metadata retrieval for multiple files? +
Yes, you can request get_object_metadata or list_objects to gather size and modification dates for many files at once through a single query.
If I need to delete old logs, which tool should I use with Google Cloud Storage MCP? +
Use delete_object. Remember that this action is permanent, so always confirm the file name and bucket before confirming deletion via your agent.