Skip to main content
Glama
jhmorimoto

Kubernetes Read-Only MCP

by jhmorimoto

list_rbac

Read-only

List Kubernetes Roles, RoleBindings, ClusterRoles, and ClusterRoleBindings as read-only metadata to diagnose RBAC configurations in a cluster or namespace without making changes.

Instructions

List Roles, RoleBindings, ClusterRoles and ClusterRoleBindings as metadata.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
clusterYes
namespaceNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, so the description does not need to re-state that this is a read operation. The phrase 'as metadata' adds a mild behavioral hint about return depth, but the description does not disclose namespace/cluster scoping behavior, pagination, or potential permission requirements. This is acceptable given the read-only annotation, but not especially rich.

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 dense sentence with no filler or redundancy. It front-loads the core action and resource types, and every word adds meaning. While terse, that terseness is not tautological; it is information-dense.

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?

The tool is simple by design and has an output schema, so return-value documentation is not strictly needed. However, with two parameters and zero schema descriptions, the missing parameter semantics and lack of usage guidance leave the agent without enough information to call the tool confidently. The description is too sparse to be complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

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 by explaining parameter semantics, but it never mentions 'cluster' or 'namespace'. An agent cannot tell what values are valid for cluster, how namespace filters results, or whether namespace is required for some resources. This is a significant gap.

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 names four specific resource types (Roles, RoleBindings, ClusterRoles, ClusterRoleBindings) and uses the verb 'List', making the tool's purpose explicit. It is clearly distinguishable from sibling list_* tools like list_pods, list_nodes, or list_crds because it targets RBAC metadata specifically.

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 description implies when to use the tool by naming RBAC resources, but it gives no explicit guidance about when to choose this over alternatives or when not to use it. Sibling tools like list_resources or get_resource could overlap, and no routing information is provided.

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

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/jhmorimoto/kubernetes-readonly-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server