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hetzner-mcp-server

by lazyants
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TypeScript
Remote

Get Load Balancer Metrics

hetzner_get_lb_metrics
Read-onlyIdempotent

Retrieve load balancer metrics for a specified time range to monitor connections, requests, and bandwidth in Hetzner Cloud.

Instructions

Get metrics for a load balancer over a specified time range.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesResource ID
endYesEnd of the time range in ISO 8601 format
stepNoResolution of metric samples in seconds, e.g. 60
typeYesMetric type, e.g. "open_connections", "connections_per_second", "requests_per_second", "bandwidth.in", "bandwidth.out"
startYesStart of the time range in ISO 8601 format

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv3.0.0
    • addedInput schema / properties / step
      Added value: +{
+  "description": "Resolution of metric samples in seconds, e.g. 60",
+  "exclusiveMinimum": 0,
+  "type": "number"
+}
  2. First observedv2.2.0

TDQS

C2.9/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is covered. Beyond that, the description says nothing about rate limits, sample retention windows, what happens with ranges outside retention, or the shape/size of returned series. For a metrics endpoint that can return large time-series payloads, this is a real gap.

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?

One sentence, front-loaded with the verb and resource, no wasted words. It is terse to the point of being sparse, but nothing is redundant.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema and a time-series-returning tool, the description should indicate the shape of results or at least that raw sample points are returned. Combined with zero usage guidance and no behavioral notes beyond annotations, the definition is too thin for a data-query tool with five parameters.

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%, so all five parameters (id, type, start, end, step) are documented in the schema, including enum-like examples for type and ISO 8601 for timestamps. The description adds no parameter-level detail, so the baseline 3 applies.

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 states a specific verb and resource: 'Get metrics for a load balancer over a specified time range.' It is distinguishable from sibling hetzner_get_server_metrics by naming load balancer explicitly. However, it does not call out that distinction, relying on the name prefix alone.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this versus alternatives. There is a sibling hetzner_get_server_metrics for servers, and hetzner_get_load_balancer for LB properties, but the description never states when metrics retrieval is appropriate or what preconditions apply (e.g., LB must exist and have been active to yield samples).

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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