Amazon SageMaker Well-Architected MCP Server

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list_sagemaker_resources

List SageMaker endpoints, training jobs, notebook instances, and models in a specified AWS region to enable Well-Architected validation.

Instructions

List SageMaker resources available for validation.

    Returns endpoints, training jobs, notebook instances, and models
    in the specified region.

    Args:
        ctx: MCP context
        region_name: AWS region name (default: us-east-1)
        profile_name: AWS profile name (optional)

    Returns:
        ListResourcesResponse with resource lists

Input Schema

TableJSON Schema

Name	Required	Description	Default
`region_name`	No	AWS region name. Default is us-east-1.	us-east-1
`profile_name`	No	AWS profile name. If not provided, uses the default profile.

Output Schema

TableJSON Schema

Name	Required	Description
`models`	No	List of models
`content`	Yes	Response content
`isError`	No	Whether this is an error response
`endpoints`	No	List of endpoints
`training_jobs`	No	List of training jobs
`notebook_instances`	No	List of notebook instances

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 6, 2026

TDQS

B3.2/5.0

Behavior3/5

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

No annotations are provided, so the description carries full behavioral burden. It discloses the read-only nature via 'List', the resource categories, and region scoping. However, it does not cover pagination, credential/auth requirements, resource status filtering, or error behavior.

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 summary sentence is front-loaded and clearly communicates purpose. The docstring-style Args/Returns sections are scannable and compact, though the Args section repeats schema information.

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?

For a simple optional-parameter list call with an output schema, the essential invocation information is present. But it omits when-to-use guidance and notes on auth/credential assumptions, making it adequate rather than complete.

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 both region_name and profile_name. The description adds no substantive semantics beyond re-stating defaults and optionality, so the baseline 3 is appropriate.

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 ('List'), resource ('SageMaker resources'), and scope ('available for validation', 'in the specified region'), and enumerates returned resource types. It clearly distinguishes from sibling 'validate_*' tools by its listing focus, though it doesn't name the alternatives explicitly.

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?

'available for validation' hints at a pre-validation enumeration step, but the description gives no explicit conditions for when to use this tool vs validate_sagemaker_resource, validate_all_endpoints, or validate_all_resources. There are no exclusions or alternatives mentioned.

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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