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proliant-mcp

proliant-mcp

by hjma29
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Get Server Summary

get_server_summary
Read-onlyIdempotent

Retrieves a ProLiant server's identity, power and POST state, health, UID status, BIOS/iLO versions, CPU and memory summary from iLO.

Instructions

Server identity and state: model, product ID, serial, power and POST state, health, UID light, BIOS and iLO versions, CPU count/model and total memory.

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": {
      "server": "<server>"
    },
    "name": "get_server_summary"
  }
}

Input Schema

NameRequiredDescriptionDefault
serverYesServer name from list_servers (or its iLO host/IP).

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior2/5

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

Annotations already declare readOnly, idempotent, non-destructive, and openWorld, and an output schema exists, so the enumerated field list largely restates return content the structured data already covers. The description adds no behavioral context beyond that — no mention of the network round-trip/latency implied by openWorldHint, no auth or reachability prerequisites for the iLO host.

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?

A single compact sentence, front-loaded with the resource and followed by a terse field list; no wasted wording. The colon-delimited list style is dense but readable.

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

Completeness4/5

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

For a one-parameter read-only tool with full schema coverage, rich annotations, and an output schema, the definition supplies enough to call it correctly. The only real hole is sibling differentiation, which the usage dimension already captures.

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?

The single parameter has 100% schema description coverage ('Server name from list_servers (or its iLO host/IP)'), and the description adds nothing further. Baseline 3 applies since the schema fully carries parameter meaning.

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 names the resource ('Server identity and state') and enumerates the exact contents returned (model, serial, power/POST state, health, BIOS/iLO versions, CPU, memory), so an agent knows precisely what it gets. It does not, however, distinguish itself from overlapping siblings such as get_health, get_ilo_info, or get_firmware_inventory, which return subsets of the same data.

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?

There is no when-to-use or when-not-to-use statement and no alternative is named, even though the field list overlaps heavily with get_health, get_ilo_info, get_firmware_inventory, get_processors, and get_memory. The only implicit guidance is that this is a consolidated snapshot, which the agent must infer.

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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