k8s-docs-mcp

check_api_version

Verify Kubernetes API versions for a Kind, detect deprecations/removals, and get the stable apiVersion plus migration advice.

Instructions

Verifies Kubernetes API version compatibility, deprecations, and removals deterministically via OpenAPI registry.

Args:
    kind: The Kubernetes resource Kind (e.g. 'Ingress', 'PodSecurityPolicy', 'CronJob', 'ValidatingAdmissionPolicy').
    api_version: Optional apiVersion to test (e.g. 'extensions/v1beta1', 'networking.k8s.io/v1').

Returns:
    Authoritative validation report with current stable apiVersion, deprecation notices, and migration advice.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "kind": "<kind>"
    },
    "name": "check_api_version"
  }
}

Input Schema

Name	Required	Description	Default
`kind`	Yes
`api_version`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 20, 2026

TDQS

B3.4/5.0

Behavior3/5

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

No annotations are provided, so the description carries the behavioral burden. It usefully discloses that results are deterministic and sourced from an authoritative OpenAPI registry, and summarizes the return payload, but it never states that the call is side-effect-free, nor any auth or rate-limit constraints.

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-loaded purpose sentence followed by tight Args/Returns sections; every line earns its place. Slightly formulaic but no filler or repetition.

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 two-parameter, read-only verification tool with an output schema present, the definition covers both inputs and indicates the shape of the report. Only the absence of usage guidance and annotation-level guarantees keeps it from being fully complete.

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 does: it explains kind as the resource Kind with four concrete examples and api_version as an optional version to test with real syntax examples ('extensions/v1beta1', 'networking.k8s.io/v1'). This adds genuine meaning beyond the bare schema titles.

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 (verifies) and resource (Kubernetes API version compatibility, deprecations, removals) plus the mechanism (OpenAPI registry). This implicitly distinguishes it from the docs-oriented siblings like search_k8s_docs, but it never names an alternative tool 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?

There is no when-to-use or when-not-to-use guidance, no prerequisites, and no routing to siblings such as list_supported_resources or get_canonical_manifest. The agent must infer the usage context purely from the purpose sentence.

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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