Skip to main content
Glama
mmpyro

vcluster-mcp

by mmpyro

get_namespace_annotations

Fetch all annotations for a Kubernetes namespace by providing its name, with optional kubeconfig path for cluster access.

Instructions

Get annotations for a specific namespace.

This function retrieves all annotations associated with a Kubernetes namespace. Annotations are similar to labels but are typically used for storing non-identifying metadata.

Args: namespace: The name of the namespace to get annotations from. kubeconfig_path: Optional path to a kubeconfig file. If not provided, the default kubeconfig from the environment will be used.

Returns: Union[Dict[str, str], str]: Dictionary of annotations on success, or error object if failed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
namespaceYes
kubeconfig_pathNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description carries behavioral burden. It discloses return type ('Dictionary of annotations on success, or error object') and optional kubeconfig behavior, though it doesn't explicitly state that the operation is non-destructive or mention permission requirements.

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?

Structured docstring with a short first sentence, context paragraph, and Args/Returns sections. Each sentence adds value; no filler.

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

Completeness5/5

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

For a simple read operation, the description covers purpose, parameter semantics, and return behavior. It's complete given the low complexity and presence of a described output.

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

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the Args section fully describes both parameters: namespace as the required name, and kubeconfig_path as an optional path defaulting to the environment kubeconfig. This compensates for the lack of schema descriptions.

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?

Description opens with 'Get annotations for a specific namespace' and clarifies it retrieves all annotations, distinguishing it from sibling tools like get_namespace_labels and set_namespace_annotation. The verb and resource are specific.

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?

No explicit when/when-not guidance is provided; the description only implies usage by contrasting annotations with labels. It doesn't name alternatives like get_namespace_labels.

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

Install Server

Other Tools

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/mmpyro/vcluster-mcp'

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