Amazon S3 Bucket MCP. Scoped storage access for your AI agent.
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Amazon S3 Bucket MCP Server provides scoped access to a single S3 storage bucket. Your AI agent can read, write, and manage objects—listing files, getting metadata, uploading JSON, and deleting objects—all without needing full cloud credentials.
It enforces the principle of least privilege, confining all operations to one defined bucket for maximum security.
What your AI agents can do
Delete object
Removes a specific object from the bucket.
Get bucket acl
Retrieves the Access Control List (ACL) for the bucket.
Get bucket policy
Retrieves the full policy document governing the bucket's access.
List all objects within the designated bucket, optionally narrowing the search using prefixes and delimiters.
Retrieve either the full content of an object or just its metadata (size, type, headers) without downloading the entire file.
Create and upload new objects containing raw strings or JSON data into the bucket.
Delete specific objects by key to maintain storage hygiene and remove stale data.
Retrieve the bucket's Access Control List (ACL) or the full bucket policy to check for compliance settings.
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Supported MCP Clients
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Amazon S3 Bucket MCP Server: 7 Tools for Data Operations
Use these seven tools to list, read, write, delete, and audit objects within a single, secure S3 bucket.
019e3863delete object
Removes a specific object from the bucket.
019e3863get bucket acl
Retrieves the Access Control List (ACL) for the bucket.
019e3863get bucket policy
Retrieves the full policy document governing the bucket's access.
019e3863get object data
Fetches the actual content stored inside an object.
019e3863get object metadata
Gets details about an object, such as its size, content type, and last modified date.
019e3863list objects
Lists all objects in the bucket, allowing filtering by prefixes and delimiters.
019e3863put object
Uploads a new object with provided content to the bucket.
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 every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Amazon S3 Bucket, then connect any of our 4,700+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,700+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
What you can do with this MCP connector
This MCP server gives your AI agent scoped access to a single Amazon S3 bucket. It lets your agent read, write, and manage objects—listing files, getting metadata, uploading JSON, and deleting objects—all without needing full cloud credentials. It keeps everything confined to one defined bucket for maximum security.
List Files: You can use list_objects to see every object in the bucket, and you've got the option to filter that list using specific prefixes or delimiters.
Get Object Details and Content: You can grab the full content of an object using get_object_data, or you can just check the object's details—like its size, content type, and when it was last modified—by calling get_object_metadata.
Upload New Data: Need to drop new stuff in the bucket? You use put_object to upload new objects, whether that content is a raw string or structured JSON data.
Clean Up Storage: You can run delete_object to remove specific objects by their key, which keeps your storage clean and cuts out stale data.
Review Security Policies: You can check the bucket's security settings by retrieving the Access Control List (ACL) using get_bucket_acl, or you can pull the entire policy document that governs the bucket's access with get_bucket_policy.
How Amazon S3 Bucket MCP Works
- 1 Subscribe to the Amazon S3 Bucket MCP Server and provide your AWS credentials, region, and the target bucket name.
- 2 Your AI client sends a command (e.g., 'List all files under reports/').
- 3 The server executes the tool using the scoped credentials, and the agent receives the list or data.
The bottom line is, your agent works inside a digital sandbox, limited only to the single bucket you specify.
Who Is Amazon S3 Bucket MCP For?
Data teams and security engineers need this. It solves the problem of giving AI agents enough access to work, but not too much. If you're tired of worrying that an agent could accidentally delete production data or read private logs from an unrelated bucket, this is for you. It keeps the AI focused.
Uses the agent to process data by listing files, fetching metadata, and writing results to a specific data lake partition.
Runs the agent to check the bucket's ACL and policy, confirming that access controls match compliance requirements.
Assigns the server to different agents to enforce strict tenant isolation, ensuring one workflow can't touch another's data.
What Changes When You Connect
- Data Integrity: Use
delete_objectandput_objectto ensure data is written and cleaned up precisely where it needs to go, preventing orphaned files and stale logs. - Audit Readiness: Running
get_bucket_aclorget_bucket_policylets your agent quickly check the bucket's security posture. You get a compliance report without manual checks. - Focused Discovery:
list_objectslets the agent find exactly what it needs by using prefixes and delimiters, so it doesn't waste time sifting through thousands of unrelated files. - Efficiency: You don't need to download entire files just to check a date or size.
get_object_metadatagives you the object's details instantly, saving bandwidth and time. - Safety First: By using this single-bucket scope, you eliminate the risk of your agent accidentally touching other resources in your AWS account. It's contained.
- Content Retrieval: When the agent needs the raw data,
get_object_datafetches the full content. This is how it pulls data for processing or analysis.
Real-World Use Cases
Analyzing Quarterly Reports
A data engineer needs to process the latest quarter's sales data. They ask their agent to first run list_objects to find all files under the 'Q3/2024/' prefix. Then, the agent uses get_object_metadata on the resulting files to identify the largest CSV. Finally, it calls get_object_data to pull the content and pass it to a local analysis script.
Enforcing Data Governance
A security auditor must confirm that only specific roles can access PII data. They use the agent to call get_bucket_policy and get_bucket_acl. If the output doesn't show the required read restrictions, the agent flags it immediately, stopping the workflow before a compliance violation occurs.
Automating Log Archival
An operations team uses the agent to clean up old logs. It calls list_objects to find all files older than 90 days in the 'logs/archive/' folder. It then runs delete_object on each identified file, keeping the bucket clean and reducing storage costs.
Ingesting Configuration Files
A platform engineer needs to deploy a new application config. They provide the JSON payload and ask the agent to put_object it into the 'config/prod/app.json' key. The agent then runs get_object_metadata to confirm the file landed correctly.
The Tradeoffs
Using `get_object_data` for listing
A user thinks they need to download the content of every file just to check if it exists or what its type is. This wastes bandwidth and adds massive latency.
→
Don't use get_object_data. Instead, use list_objects to get the file keys and get_object_metadata to check the type and size. That's the right way.
Manual policy checks
A developer manually logs into the AWS console every time they need to verify access rights, which is slow and prone to human error.
→
Let the agent run get_bucket_policy or get_bucket_acl. It pulls the current policy straight into your chat, letting you verify access rights instantly.
Over-scoping access
Giving the agent full S3 access because 'it's easier,' which exposes every bucket and every piece of data in your account.
→ Limit the agent to this single-bucket MCP Server. It keeps the blast radius tiny and only grants access to the exact data you need.
When It Fits, When It Doesn't
Use this server if your priority is security and auditability. You need the AI agent to perform discrete data operations (read, write, delete) on a specific, limited set of files, and you must prove that the agent never touches anything outside that scope. Don't use this if your goal is to manage multiple, disparate data sources (like connecting to a database and S3). For that, you'd need a tool that handles multiple cloud services. If you only need to read file contents, you might just need a basic file reader tool, but if you also need to manage the files (like checking policies or listing prefixes), this is the right choice.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Amazon S3 Bucket. 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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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 7 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Managing cloud files shouldn't require AWS CLI commands.
Before this server, if you needed to check a file's status or list what's in the bucket, you had to open the AWS console, navigate to the bucket, and run a series of specific commands. It's slow, involves clicking through tabs, and you're always worried about running the wrong command.
Now, your agent handles it. You just tell it, 'List all reports from Q1.' It runs the `list_objects` tool, filters the results, and gives you a clean, actionable list right in the chat. No console clicks needed.
Amazon S3 Bucket MCP Server: Control Object Operations
You no longer have to manually check if a file is clean before uploading it, nor do you need to check the permissions every time you run a script. The agent uses `get_object_metadata` to check the file details, and then uses `put_object` to write the data, all in one conversational flow.
The difference is simple: you move from complex, multi-step console work to a single, natural conversation. It makes the whole process faster and, frankly, safer.
Common Questions About Amazon S3 Bucket MCP
How do I check the access policy using the Amazon S3 Bucket MCP Server? +
Use the get_bucket_policy tool. It retrieves the full policy document and shows you exactly what permissions are allowed or denied for the bucket.
What if I want to see the names of all files in the bucket? +
Run the list_objects tool. You can also tell it to filter the list by a specific prefix (like 'reports/') to narrow down the search.
Can I upload a JSON file to the bucket? +
Yes, use the put_object tool. You just pass the JSON content to the tool, and it uploads the object to the specified key in the bucket.
Is the Amazon S3 Bucket MCP Server safe for production data? +
Yes. The server is scoped to one single bucket, which is the industry standard for limiting the blast radius. It only allows operations on that specific data set.
How do I delete a file using the Amazon S3 Bucket MCP Server? +
Call the delete_object tool. You must provide the full object key for the file you want to remove.
How do I get the object content using the Amazon S3 Bucket MCP Server? +
Your agent retrieves the full object content using get_object_data. This method pulls the raw bytes of a file, allowing your agent to process the data immediately for analysis or transformation.
What is the scope of the Amazon S3 Bucket MCP Server, and how does it ensure security? +
The server enforces scoped access to one specific bucket. It only allows read, write, and management operations within that single bucket, preventing access to other data or account-level operations.
How do I upload different types of data using the Amazon S3 Bucket MCP Server? +
You use the put_object tool to upload data. You can upload string content or JSON content, making it versatile for configuration files, logs, or raw text data.
How is this different from the full Amazon S3 server? +
The full Amazon S3 server gives the agent access to all buckets in your AWS account — it can list, create, and delete buckets. This server scopes the agent to a single, pre-configured bucket. The agent can only read, write, and manage objects within that bucket. This follows the principle of least privilege, which is critical for secure agent deployments.
How do I get my AWS Access Key and Secret Key? +
Log in to the AWS Management Console, navigate to IAM (Identity and Access Management), and create a user with programmatic access. For this integration, we recommend a policy scoped to a single bucket (e.g., s3:GetObject, s3:PutObject, s3:DeleteObject, s3:ListBucket limited to your target bucket ARN).
Can I upload large files using this integration? +
The put_object tool handles standard REST uploads and is best suited for small to medium-sized files or JSON data. For very large files, standard AWS tools utilizing Multipart Uploads are recommended.
Can my agent access multiple buckets? +
Each instance of this server is scoped to exactly one bucket. If your agent needs access to multiple buckets, you can subscribe to this server multiple times — each with a different bucket configuration. This maintains strict isolation between data boundaries.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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