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endpoint-aiops-mcp

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Python
Remote

endpoint_reboot

Preview an endpoint's online status, then request a reboot without undo. Use dry-run to verify before committing.

Instructions

[WRITE][risk=medium] Request an endpoint reboot (no safe inverse).

Records the endpoint's prior online state for the audit trail; a reboot cannot be undone, so no undo descriptor is offered. Pass dry_run=True to preview — for an operation with no inverse, knowing whether the endpoint is even online (and how long since it was last seen) before committing is the whole value of asking first.

Args: endpoint_id: Endpoint id as returned by endpoint_list. dry_run: If True, preview without rebooting. target: Endpoint-management target name from config; omit for the default.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
targetNo
dry_runNo
endpoint_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.10.3
    • addedInput schema / properties / dry_run
      Added value: +{
+  "default": false,
+  "title": "Dry Run",
+  "type": "boolean"
+}
  2. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses key behaviors: the operation is irreversible ('no safe inverse'), records prior online state for audit, and offers a dry_run preview. This is substantial, though it does not detail permissions, side effects on the endpoint, or failure behavior. Still, it is transparent about the most critical aspects.

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?

The description is well-structured with a front-loaded purpose, followed by explanatory context and a clear Args list. It is slightly verbose due to the contextual explanation, but every sentence adds value. The bracket notation [WRITE][risk=medium] is unconventional but informative. Overall, it is appropriately sized and organized.

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, no annotations, and three parameters, the description covers purpose, usage, parameter meanings, and irreversibility. It references endpoint_list for ID acquisition, which aids integration. It does not describe return values or failure modes, but for a request-type tool this is a minor gap. The description is sufficient for an agent to invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must compensate. It does so comprehensively: each parameter is explained in the Args section (endpoint_id from endpoint_list, dry_run for preview, target from config with default). This adds meaning far beyond the bare schema types and defaults.

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 clearly states the action: 'Request an endpoint reboot'. The verb and resource are specific and unambiguous. However, it does not explicitly differentiate from sibling tools (e.g., endpoint_get, endpoint_assign_profile) beyond the action itself, so it lacks the explicit sibling distinction seen in top-tier examples.

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?

The description provides clear context on when to use the dry_run parameter (preview before committing) and references endpoint_list for obtaining the endpoint_id. However, it does not explicitly state when to use this tool versus alternatives, nor does it mention any exclusions. It implies usage but doesn't offer explicit when-not scenarios.

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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