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Kubernetes MCP Server

Kubernetes MCP Server

by thekaranpargaie
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set-image

Update container images in Kubernetes deployments to deploy new versions or fix issues by specifying deployment, container, and new image parameters.

Instructions

Update the image of a deployment

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": {
      "deployment": "<deployment>",
      "container": "<container>",
      "image": "<image>"
    },
    "name": "set-image"
  }
}

Input Schema

NameRequiredDescriptionDefault
deploymentYesThe name of the deployment to update
containerYesThe name of the container to update
imageYesThe new image to use
namespaceNoThe namespace of the deployment (optional, defaults to current context namespace)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.0.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. While 'Update' implies mutation, it doesn't specify whether this requires special permissions, whether it triggers a rollout restart, what happens to existing pods, or potential side effects. For a mutation tool with zero annotation coverage, this is inadequate.

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, efficient sentence with zero wasted words. It's appropriately sized for the tool's complexity and gets straight to the point without unnecessary elaboration.

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 mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what happens after the update, whether changes are immediate, what validation occurs, or what the response contains. Given the complexity of updating deployment images in Kubernetes, more context is needed.

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 all parameters are documented in the schema. The description doesn't add any meaningful parameter semantics beyond what's already in the schema descriptions. The baseline score of 3 is appropriate when the schema does the heavy lifting.

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 action ('Update') and target ('image of a deployment'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'patch' or 'scale-deployment' that might also modify deployments, nor does it specify this is specifically for container images rather than other deployment aspects.

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 like 'patch' or 'scale-deployment'. There's no mention of prerequisites, when-not-to-use scenarios, or comparison with sibling tools that might perform similar functions.

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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