Skip to main content
Glama
Hadar301

openshift-installer-checker

by Hadar301
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

scan_cluster

Scans a connected OpenShift or Kubernetes cluster to list available resources, including CPU, memory, GPUs, storage classes, operators, and CRDs. Provides a full inventory for capacity planning and capability checks.

Instructions

Scan the connected OpenShift/Kubernetes cluster for available resources.

This performs a FULL cluster scan, returning all available resources.

USE THIS TOOL WHEN:
- User asks "what resources are available in my cluster?"
- User asks "what does my cluster have?"
- User asks "scan my cluster"
- User wants to know their cluster's capabilities WITHOUT comparing to any app
    For Example, questions like:
        - "How many available GPUs are on the cluster?"
        - "How many available CPU cores are on the cluster?"
    And also question that might regard other cluster resources.

DO NOT USE when user asks about installing/deploying an app (use check_feasibility instead)
DO NOT USE when user asks about app requirements (use fetch_repo_content instead)

Returns comprehensive cluster information including:
- Node resources (CPU, memory, allocatable, available, usage)
- GPU availability, models, and memory (VRAM)
- Storage classes
- Installed operators (OpenShift only)
- Custom Resource Definitions (CRDs)

Fails with clear error if cluster is not accessible.

Returns:
    Dictionary containing:
    - success: Boolean indicating if the operation was successful
    - cluster_info: Node resources, GPU info, storage classes, operators, CRDs
    - error: Error message if cluster not accessible

Example:
    >>> scan_cluster()
    {
        "success": True,
        "cluster_info": {
            "nodes": {...},
            "gpu_resources": {
                "total_gpus": 4,
                "gpu_models": ["NVIDIA-A10G"],
                "gpu_memory_mb": 23028
            },
            "storage_classes": [...],
            "operators": [...],
            "crds": [...]
        }
    }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations provided, the description carries the full behavioral burden. It discloses that this is a full-cluster scan, lists the categories of information returned, and states that it fails with a clear error if the cluster is inaccessible. It could go further by noting side effects or resource cost, but for a no-parameter scan tool this is strong disclosure.

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 well-structured with clear sections and front-loaded purpose. It is somewhat longer than strictly necessary because the returned information and example partially duplicate the bullets, but the organization makes it easy to parse and the length is justified by the usage guidance.

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 zero-parameter tool with no output schema and no annotations, the description is complete: it states what the tool does, when to use it, what it returns, and how it behaves on failure. The inline return dictionary and example fill the gap left by the absent output schema.

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?

The input schema has zero parameters, so there is nothing for the description to explain about parameters. With a 100% schema coverage baseline and no params, a score of 4 is appropriate; the description adds no unnecessary parameter information.

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 states a specific verb and resource: 'Scan the connected OpenShift/Kubernetes cluster for available resources.' It clearly distinguishes itself from siblings by defining scope as a full cluster scan rather than app feasibility or repo content fetching.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides an explicit 'USE THIS TOOL WHEN' section with concrete user queries, and a 'DO NOT USE' section naming check_feasibility and fetch_repo_content as alternatives. This leaves no ambiguity about when to invoke this tool versus its siblings.

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

Deploy Server

Other Tools