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Get any resource

get_resource
Read-onlyIdempotent

Retrieve any Kubernetes object by specifying API version, kind, and resource name, with optional namespace and kube-context for targeting the right cluster.

Instructions

Read an arbitrary Kubernetes object by apiVersion/kind/name (e.g. apiVersion=apps/v1, kind=Deployment).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindYese.g. Pod, Deployment, Ingress
nameYesResource name
contextNokube-config context to target (defaults to current-context)
namespaceNoNamespace (omit for cluster-scoped resources)
apiVersionYese.g. v1, apps/v1, networking.k8s.io/v1

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.2.1
    • removedInput schema / additionalProperties
      Removed value: -false
  2. First observedv0.1.0

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description's 'Read' adds no new safety information. It does add the targeting method (apiVersion/kind/name) but discloses no additional behavioral traits like return format or error handling. With annotations covering the safety profile, the description contributes only marginal context.

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

Conciseness5/5

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

The description is a single, front-loaded sentence with no fluff or redundancy. The action, target, and example are presented in order of importance, making it highly concise and well-structured.

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?

The tool has five parameters, all documented in the schema, and the annotations cover the safety profile. The description gives a clear example and sufficient targeting instructions. While it omits explicit return format details, the output schema is absent and 'read' implies returning the object, so the description is adequately complete for an agent to invoke it correctly.

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?

The input schema has 100% coverage with descriptions for all five parameters, so the baseline is 3. The description provides a concrete example (apiVersion=apps/v1, kind=Deployment) that clarifies parameter formatting, which is a small value-add beyond the schema, but not enough to raise the score above 3.

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 states a clear action ('Read'), a specific resource ('an arbitrary Kubernetes object'), and the identifying parameters (apiVersion/kind/name). It explicitly differentiates itself from siblings like get_pod and list_* tools by emphasizing 'arbitrary', making its purpose unambiguous.

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 word 'arbitrary' implies this tool is for resources not covered by sibling get_pod or list_* tools, but the description does not explicitly state when to use it over alternatives. It provides only implicit guidance and no direct comparison to siblings, leaving the decision to the agent's inference.

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