openITCOCKPIT MCP Server

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by openITCOCKPIT

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Python

Remote

Find Services

find_services

Read-onlyIdempotent

Query services by host, name, state, container, host group, or flapping, and get per-state counts to identify critical services, host workloads, or disk warnings.

Instructions

Find services by host, name, state, container, host group or flapping, and count them per state. Use it for "which services are critical", "what runs on host web01" or "which disk checks warn". For how one known service is doing, use get_service_health.

Input Schema

TableJSON Schema

Name	Required	Description
`host`	No	Part of the host name. Empty: any host.
`name`	No	Part of the service name. Empty: any service.
`limit`	No	How many services to list. The counts always cover every match.
`state`	No	Only services in these states, e.g. ["warning", "critical"].
`flapping`	No	true: only services whose state is flapping, counted among up to 100 matches.
`container`	No	Only services in this container: its exact name or path, e.g. tenant-a.
`hostgroup`	No	Only services on hosts of this host group: its exact name.
`in_downtime`	No	true: only services in a downtime. false: only services outside one.
`acknowledged`	No	true: only acknowledged problems. false: only unacknowledged.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.5.0Sep 18, 2026

TDQS

A4.7/5.0

Behavior4/5

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

The annotations already declare readOnlyHint, idempotentHint, openWorldHint, and non-destructive behavior. The description adds that the result is a filtered listing with per-state counts, which is useful behavioral context beyond the annotations. It leaves output-shape details to the output schema, which is acceptable.

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 compact sentences do all the work: the first gives scope and filter/aggregation behavior, the second gives usage examples and the alternative tool. There is no filler or repetition of schema content.

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 an all-optional, read-only, schema-rich tool, the description covers selection, typical queries, and routing to the correct sibling. Return values are handled by the output schema, so 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?

Schema coverage is 100%, so the schema carries most parameter meaning; the baseline is 3. The description adds value by mapping natural-language use cases to filter dimensions and by stating the aggregate per-state counting behavior, which is not visible in the request schema.

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 action and resource ('Find services') and immediately lists the filter dimensions, plus the per-state count. It distinguishes this list/search tool from the sibling get_service_health, so an agent can tell which call answers a multi-service query.

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?

It gives explicit example queries ('which services are critical', 'what runs on host web01', 'which disk checks warn') and a direct alternative: use get_service_health when investigating one known service. This is clear when-to-use and when-not-to-use guidance.

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