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AWS MCP Server

AWS MCP Server

by marcelobrake
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

aws_autoscaling_describe_launch_configurations

Retrieve AWS Auto Scaling launch configurations to manage scaling group settings and deployment parameters.

Instructions

List launch configurations used by Auto Scaling Groups.

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_autoscaling_describe_launch_configurations"
  }
}

Input Schema

NameRequiredDescriptionDefault
profileNoAWS profile name from ~/.aws/config (e.g., 'default', 'production')
regionNoAWS region override (e.g., 'us-east-1', 'sa-east-1')
launch_configuration_namesNoSpecific launch configuration names
max_recordsNoMaximum configurations to return

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'List' implies read-only behavior, the description does not explicitly confirm safety, explain pagination behavior, or describe the output format. It fails to mention that all parameters are optional or how the filtering works.

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 a single efficient sentence with no wasted words. It is appropriately front-loaded with the action verb. However, it may be overly terse given the lack of annotations and output schema.

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 100% schema coverage and a simple read-only operation, the description is minimally adequate but leaves gaps. It does not explain the relationship between launch configurations and auto scaling groups in depth, nor does it clarify the pagination model or authentication requirements typical of AWS tools.

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

Parameters3/5

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

Schema description coverage is 100%, establishing a baseline of 3. The description mentions 'launch configurations' generally but does not add semantic meaning to specific parameters (e.g., explaining that launch_configuration_names filters to specific configs, or that max_records controls pagination). It does not compensate beyond what the schema already provides.

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?

The description uses a specific verb ('List') and resource ('launch configurations'), and distinguishes itself from sibling tools like 'aws_autoscaling_describe_auto_scaling_groups' by clearly targeting launch configurations rather than the groups themselves. The phrase 'used by Auto Scaling Groups' adds useful relational context.

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?

The description provides no guidance on when to use this tool versus alternatives, no prerequisites (e.g., needing valid AWS credentials), and no information about what happens if called without filters (returns all vs requires specific names).

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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