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AWS-Auth

AWS-Auth

by N0mansky
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

aws_list_eks_clusters

List EKS clusters in a specific AWS region and optionally update your local kubeconfig to connect kubectl to the found clusters.

Instructions

List EKS clusters in a specific AWS region and optionally configure local ~/.kube/config.

Args: region: AWS region (e.g. 'us-east-1', 'us-west-2') profile_name: AWS profile name to use (default: 'default') update_kubeconfig: If True, automatically configures kubeconfig for found clusters

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "aws_list_eks_clusters"
  }
}

Input Schema

NameRequiredDescriptionDefault
regionNous-east-1
profile_nameNodefault
update_kubeconfigNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It does disclose the key side effect that update_kubeconfig=True mutates the local ~/.kube/config, which is genuinely useful behavioral context. However, it says nothing about credential requirements, what happens when no clusters exist, or any side effects of the default path.

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?

Front-loads the purpose sentence and follows with a compact arg list. Slightly redundant for region/profile which repeat schema defaults, but overall efficient with no wasted prose.

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

Completeness4/5

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

An output schema exists, so return values need not be explained. Given the tool's moderate complexity, the description is essentially complete for calling it: all three params are covered and the kubeconfig side effect is stated. Only minor gaps remain around credential/error behavior.

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?

Schema description coverage is 0%, so the description must compensate, and it largely does: region gets concrete examples, profile_name states its default, and update_kubeconfig explains its behavioral effect. This adds real meaning beyond the bare schema types and defaults.

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

Purpose4/5

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

States a specific verb+resource ('List EKS clusters') plus a clear scope ('in a specific AWS region') and adds the secondary capability of writing kubeconfig. The purpose is unambiguous, though it never names or contrasts with its closest sibling (aws_update_kubeconfig), which also touches kubeconfig.

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

Usage Guidelines2/5

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

No when-to-use or when-not-to-use guidance is given, and the alternatives are not mentioned. It's implied you call this to enumerate clusters, but the overlap with aws_update_kubeconfig (which also configures kubeconfig) is never resolved, leaving the agent to guess which tool to pick.

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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