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sanjaypsachdev

OpenShift MCP Server

oc_apply

Apply YAML manifests to OpenShift clusters with comprehensive validation and error handling, supporting dry-run, force apply, pruning, and server-side application.

Instructions

Apply YAML manifests to OpenShift cluster with comprehensive error handling and validation for all scenarios

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoURL to YAML manifest to apply
waitNoWait for resources to be ready
forceNoForce apply, ignore conflicts
pruneNoPrune resources not in current configuration
dryRunNoValidate only, don't apply (client or server)
cascadeNoDeletion cascade strategy
contextNoOpenShift context to use (optional)
timeoutNoTimeout for wait operation (e.g., "60s", "5m")
filenameNoPath to YAML file to apply
manifestNoYAML manifest content to apply
selectorNoLabel selector for pruning
validateNoValidate resources before applying
kustomizeNoApply kustomization directory
namespaceNoOpenShift namespace/projectdefault
overwriteNoOverwrite existing resources
recursiveNoProcess directory recursively
gracePeriodNoGrace period for resource deletion (seconds)
fieldManagerNoField manager name for server-side apply
pruneWhitelistNoResource types to include in pruning
serverSideApplyNoUse server-side apply
Behavior2/5

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

With no annotations, the description must carry the burden of disclosing behavioral traits. It only offers a vague claim about 'comprehensive error handling and validation' without specifics on side effects, idempotency, cluster requirements, or handling of conflicts. This is insufficient for a mutating tool with 20 parameters.

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 sentence, making it very concise and front-loaded with the core action. However, the phrase 'for all scenarios' is vague and adds little value, slightly reducing the score from a perfect 5.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 20 parameters, no annotations, and no output schema, a one-sentence description is inadequate. It fails to mention the various input modes (URL, file, manifest, kustomize), prunability, server-side apply, or wait/force options, leaving major gaps in understanding the tool's full capabilities.

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 provides descriptions for all 20 parameters (100% coverage), so the description need not add parameter details. The description adds no parameter-specific meaning, but the schema is thorough, so the baseline score of 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?

The description clearly states the tool applies YAML manifests to an OpenShift cluster. The verb 'apply' is specific and implies create-or-update behavior, distinguishing it from siblings like oc_create or oc_delete, though it does not explicitly name alternatives.

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 such as oc_create, oc_patch, or oc_delete. No scenarios or exclusion criteria are mentioned, leaving the agent to infer usage from the tool name and schema.

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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