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librenms-mcp

by mhajder
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Python
Hybrid

Port Groups List

port_groups_list
Read-onlyIdempotent

Get port groups from LibreNMS in paginated batches. Specify limit for page size and offset to skip entries, allowing controlled retrieval of group data.

Instructions

List port groups from LibreNMS.

Returns: dict: The JSON response from the API.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of results to return
offsetNoNumber of results to skip (offset) for pagination

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.10.3
    • addedInput schema / properties / limit
      Added value: +{
+  "default": 100,
+  "description": "Maximum number of results to return",
+  "minimum": 1,
+  "type": "integer"
+}
    • addedInput schema / properties / offset
      Added value: +{
+  "default": 0,
+  "description": "Number of results to skip (offset) for pagination",
+  "minimum": 0,
+  "type": "integer"
+}
  2. First observedv1.9.0

TDQS

A3.5/5.0
Behavior2/5

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

The annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds 'Returns: dict' which is redundant with the output schema and provides no additional behavioral context such as pagination behavior, default limits, or whether all port groups or only accessible ones are returned.

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 short and front-loaded with the core purpose. The Returns line is somewhat redundant given the output schema, but the overall size is appropriate and there is no unnecessary verbosity.

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 simple, read-only list operation, the description is reasonably complete. Annotations cover the safety profile, the schema covers pagination parameters, and the output schema documents return values. It lacks usage guidance and behavioral detail, but the tool's simplicity keeps these gaps minor.

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 the limit and offset parameters are fully documented in the input schema. The description does not add any extra parameter semantics, so the baseline of 3 applies.

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 clearly states 'List port groups from LibreNMS', using a specific verb ('List') and resource ('port groups'). This distinguishes it from sibling tools like port_group_list_ports, which lists the ports within a group, and port_group_add/remove, which mutate group membership.

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

Usage Guidelines3/5

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

The description implies usage: call this when you want to see the available port groups. However, it provides no explicit guidance on when it should be preferred over alternatives, nor does it mention exclusions or related tools that might be more appropriate in certain 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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