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List servers

list_servers
Read-only

Servers of the project (machines running the Hyperping agent, agt_ uuids; not monitors or healthchecks): per server its name, hostname, status (online, stale = heartbeat late, offline, uninstalled), last_seen_at, OS, agent version, group, tags, current memory_pct and disk_pct of the root filesystem (live, last 5 min), and its ongoing incidents (offline/stale heartbeat or metric rule, with the outage_ uuid). Offline first. Also returns counts by status. At most 100 rows (truncated flag); filter with status, group, tag or name. CPU and 24 h peaks: get_server.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagNoTag filter "key:value", e.g. "env:production".
nameNoCase-insensitive substring of the display name or hostname.
groupNoExact group name (case-insensitive).
statusNoOnly servers in this status.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.2/5.0
Behavior4/5

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

Annotations cover readOnlyHint and openWorldHint, but the description adds substantial behavioral context: ordering (offline first), the 100-row cap with a truncated flag, status semantics (stale = heartbeat late), live metric windows (last 5 min), and count aggregation. It does not discuss auth or why rows truncate beyond the cap, but goes well beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Information-dense but front-loaded with the most important disambiguation early. However, it reads as a run-on sentence with field enumerations and parenthetical clarifications, sacrificing scannability for density.

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?

Given no output schema, the description helpfully enumerates returned fields (name, hostname, status, last_seen_at, OS, agent version, group, tags, memory_pct, disk_pct, incidents, counts) and the ordering. It is nearly complete for a list tool; only return-shape formalities are absent.

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?

Schema description coverage is 100% with a pattern for tag and an enum for status, so the schema carries parameter meaning. The description lists the filterable fields (status, group, tag, name), which adds navigational value but no syntax beyond what the schema provides.

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?

States a specific verb+resource (list servers) and immediately disambiguates what a 'server' is (machines running the Hyperping agent, agt_ uuids) versus monitors and healthchecks. This distinction is critical in a sibling set full of monitor/healthcheck tools.

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?

Explicitly names the sibling add-on: 'CPU and 24 h peaks: get_server'. It also states filtering options and the 100-row truncation limit, so an agent knows when this tool suffices and when to reach for get_server.

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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