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s3-mcp

by KonMam

list_buckets

Retrieve all AWS S3 buckets in your account. This tool returns a JSON-formatted list of available storage containers for managing cloud data.

Instructions

Lists all buckets in the AWS account.

Returns: str: JSON formatted list of buckets.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The handler function for the 'list_buckets' tool. It is registered via the @mcp.tool() decorator, calls the core logic helper, and formats the response as JSON.
    @mcp.tool()
    def list_buckets() -> str:
        """Lists all buckets in the AWS account.
    
        Returns:
            str: JSON formatted list of buckets.
        """
        result = _list_buckets_logic()
  • Supporting helper function that executes the core S3 API call to list buckets using the boto3 client.
    def _list_buckets_logic() -> Dict[str, Any]:
        """Core logic to list S3 buckets.
    
        Returns:
            Dict[str, Any]: Raw boto3 response from list_buckets.
        """
        client = get_s3_client()
        return client.list_buckets()
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. While it states the return format ('JSON formatted list of buckets'), it lacks critical behavioral context such as authentication requirements, rate limits, pagination behavior, error conditions, or whether this operation is safe/read-only. The description doesn't contradict annotations (none exist), but provides minimal behavioral insight.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured in two sentences: first stating the core functionality, then specifying the return format. Every sentence adds value, with no redundant information. It could be slightly improved by front-loading the return format information more explicitly, but overall it's appropriately concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (no parameters, has output schema) and lack of annotations, the description provides basic but incomplete context. It covers what the tool does and the return format, but misses important operational details like authentication, error handling, and behavioral characteristics that would be crucial for an agent to use this AWS tool effectively. The existence of an output schema reduces the need to describe return values, but other gaps remain.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so there are no parameter semantics to explain. The description appropriately doesn't attempt to describe non-existent parameters. With 100% schema description coverage (empty schema) and no parameters, a baseline score of 4 is appropriate as there's nothing missing or misleading about parameter documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Lists') and resource ('all buckets in the AWS account'), making the purpose immediately understandable. It distinguishes this tool from siblings like list_objects_v2 (which lists objects within a bucket) by focusing on bucket-level enumeration rather than object-level operations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context by specifying 'AWS account' scope, but provides no explicit guidance on when to use this versus alternatives like list_objects_v2 or other bucket-related operations. There's no mention of prerequisites, permissions needed, or comparison with sibling tools beyond the inherent resource distinction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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