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Amazon SageMaker Well-Architected MCP Server

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validate_sagemaker_resource

Validate SageMaker resources against all six Well-Architected pillars to uncover security, reliability, performance, cost, and sustainability issues with recommended actions.

Instructions

Validate a SageMaker resource against all Well-Architected Framework pillars.

    Checks security, reliability, performance efficiency, cost optimization,
    operational excellence, and sustainability best practices for the specified resource.

    ## Supported Resource Types
    - **endpoint**: SageMaker real-time inference endpoints
    - **training_job**: SageMaker training jobs
    - **notebook_instance**: SageMaker notebook instances
    - **model**: SageMaker models

    ## Checks Performed
    - **Security**: KMS encryption, VPC isolation, network isolation, inter-container encryption
    - **Reliability**: Multi-instance endpoints, training timeouts, checkpointing, retry strategies
    - **Performance**: Instance generation, data capture, data distribution, instance sizing
    - **Cost**: Cost tags, spot training, serverless inference, lifecycle configs
    - **Operational Excellence**: Operational tags, auto-scaling, experiment tracking
    - **Sustainability**: Graviton instances, spot utilization, right-sizing

    ## Fallback Options
    - If this tool fails, use AWS CLI: `aws sagemaker describe-endpoint --endpoint-name <name>`
    - Or use the AWS SageMaker Console to review resource configurations

    Args:
        ctx: MCP context
        resource_type: Type of SageMaker resource
        resource_name: Name of the resource to validate
        region_name: AWS region name (default: us-east-1)
        profile_name: AWS profile name (optional)

    Returns:
        ValidateResourceResponse with findings and summary

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
region_nameNoAWS region name. Default is us-east-1.us-east-1
profile_nameNoAWS profile name. If not provided, uses the default profile.
resource_nameYesName of the SageMaker resource to validate.
resource_typeYesType of SageMaker resource: endpoint, training_job, notebook_instance, or model.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYesResponse content
isErrorNoWhether this is an error response
summaryYesFindings summary by pillar
findingsYesList of findings
resourceYesName of the validated resource
resource_typeYesType of the resource

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden and mostly meets it: it enumerates all six pillar checks, concrete examples per pillar, and a fallback path. It does not explicitly state side-effect freedom or IAM requirements, but 'validate' and 'checks' strongly imply a read-only assessment.

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 longer than average but well-structured with headings for supported types, checks, fallback, arguments, and returns. The front-loaded summary is effective, and each section adds operational value rather than padding.

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?

For a moderately complex validation tool with no annotations and an output schema, the description covers supported inputs, the exact pillar checks, fallbacks, and the response shape. It omits permission requirements and error behavior, but the provided context is sufficient for selecting and invoking the tool correctly in most cases.

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%, so the schema already documents all four parameters. The description's Args section largely repeats those definitions and even mentions ctx, which is not part of the input schema; the only added value is the expanded resource-type list and example checks, which are not strictly parameter semantics.

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 opening sentence states a specific action and object: 'Validate a SageMaker resource against all Well-Architected Framework pillars.' The Supported Resource Types section and singular 'resource_name' make the single-resource scope clear, distinguishing it from siblings like validate_all_endpoints.

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 gives clear context by listing supported resource types and fallback CLI/console options, but it never explicitly says when to prefer this tool over the sibling validation tools. The singular-resource scope is implied rather than stated as an alternative, so an agent must infer the routing decision.

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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