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find_agents
Read-onlyIdempotent

Search Atera agents by machine name, logged-in user, IP, or customer name, with optional online/offline filter. Ideal for locating agents matching partial details.

Instructions

Search agents by machine name, logged-in user, IP or customer name (contains, case-insensitive), optionally only offline/online ones. For an exact machine name prefer get_agent_by_machine.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of matches to return (default 20)
queryNoPart of machine name, agent name, user, IP or customer name
onlineNotrue = online only, false = offline only
maxPagesNoMaximum pages of 50 items to scan (default 10, i.e. 500 records)
customerIdNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive/openWorld, so safety is covered. The description usefully adds matching semantics (substring, case-insensitive) and the optional status filter, which go beyond the annotations. It does not describe result shape or paging behavior in prose, but that is a minor gap.

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 sentences, zero waste, with the primary search scope front-loaded and the sibling routing placed last. Nothing redundant.

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 read-only search whose safety profile is fully carried by annotations and whose parameters are 80% documented, the description is sufficient to invoke it correctly. It does not discuss return volume or pagination, but that is not essential here.

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 80%, so the baseline is 3. The description adds meaning beyond the schema by specifying substring/case-insensitive matching for the query and clarifying that the boolean toggles online-only vs offline-only filtering.

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 (search) and resource (agents) plus the searchable fields, and explicitly distinguishes itself from get_agent_by_machine for exact-name lookups. An agent can select it without opening any schema.

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?

Gives explicit routing guidance: 'For an exact machine name prefer get_agent_by_machine', and explains the optional online/offline filter. This names the alternative and the condition that selects it.

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