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openITCOCKPIT

openITCOCKPIT MCP Server

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Monitoring Engine Health

get_monitoring_engine_stats
Read-onlyIdempotent

Diagnose mass check failures by reviewing monitoring engine health: host/service counts, check throughput, and latency to distinguish stale results from real outages.

Instructions

Health of the monitoring engine itself: how many hosts and services it watches, and its check throughput and latency.

Relevant when many unrelated checks fail at once: high check latency or a collapsed check rate means the engine is behind and its results are stale, which looks identical to a real outage.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

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

A4.5/5.0
Behavior4/5

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

Annotations already cover read-only, idempotent, open-world, and non-destructive behavior. The description adds useful behavioral context by explaining that stale/lagging engine results can look like a real outage, which helps the agent interpret the numbers.

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?

Two tightly written sentences: the first states what the tool returns, and the second justifies when it matters. No filler, and the key information is front-loaded.

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 read-only, no-input tool with an output schema present, the description provides the necessary purpose and diagnostic context. Nothing essential is missing.

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 no parameters, so there is nothing for the description to clarify at the parameter level. The description compensates by stating what the zero-argument call reports.

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 a specific resource (the monitoring engine itself) and the exact data returned: watched hosts/services, check throughput, and latency. This clearly separates it from sibling tools focused on individual hosts, services, or logs.

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?

It gives an explicit trigger context: many unrelated checks failing at once, where the tool distinguishes engine lag from a real outage. It does not name alternative tools or state when not to use it, but the situational guidance is clear.

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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