mcp-vmware

by Hokonoken

Overview Schema Source Related Servers Discussions Admin

Python

Hybrid

vmware_get_cluster_config

Read-onlyIdempotent

Retrieve cluster HA and DRS configuration, including failover capacity and current failover level.

Instructions

Detailed HA (DAS) and DRS configuration of a cluster + failover capacity.

Returns a JSON {name, ha:{enabled, admission_control_enabled, failover_level, restart_priority, current_failover_level}, drs:{enabled, behavior, vmotion_rate}, rules_count}.

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": {
      "cluster": "<cluster>"
    },
    "name": "vmware_get_cluster_config"
  }
}

Input Schema

Name	Required	Description	Default
`cluster`	Yes	Cluster name (see vmware_list_clusters)

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jul 14, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds value by detailing exactly which configuration fields are returned (HA, DRS, rules_count, failover level), providing context beyond annotations.

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 very concise, using two short paragraphs. It front-loads the purpose and then lists the return JSON structure without any unnecessary words.

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?

Given the tool's moderate complexity (returns structured HA and DRS data) and presence of output schema and annotations, the description covers all essential aspects: input (cluster name), output format, and configuration details. No gaps remain.

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?

With 100% schema coverage and one parameter, the baseline is 3. The description adds minimal extra meaning—only referencing vmware_list_clusters for obtaining the cluster name. No further elaboration on parameter semantics.

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 clearly states the tool returns detailed HA (DAS) and DRS configuration and failover capacity of a cluster, and specifies the exact JSON structure. This distinguishes it from siblings like vmware_drs_recommendations and vmware_list_clusters.

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

Usage Guidelines4/5

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

The description implicitly guides usage by noting the cluster parameter comes from vmware_list_clusters and the output provides config details. It does not explicitly state when to use vs alternatives or when not to use, but the prerequisite is mentioned.

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