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librenms-mcp

by mhajder
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Python
Hybrid

Switching Vlans

switching_vlans
Read-onlyIdempotent

Retrieve all VLANs from LibreNMS to view network segmentation. Use pagination controls to manage large result sets.

Instructions

List all VLANs 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

C2.9/5.0
Behavior2/5

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

Annotations already declare the operation as read-only and idempotent, so the description does not need to repeat that. However, the description says 'List all VLANs,' yet the parameters include limit and offset, implying pagination; this behavior is not disclosed. The return type note adds little value beyond the existing output schema.

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 very short and front-loaded with the core action. The returns line is somewhat generic and redundant given the output schema, but overall there is no filler or unnecessary detail.

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?

While annotations and output schema cover safety and return shape, the description omits important usage context. It does not clarify pagination behavior despite claiming to list 'all' VLANs, and it does not distinguish itself from the similar sibling device_vlans. An agent may still invoke it correctly for the first page, but the 'all' wording is misleading without pagination guidance.

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?

The input schema provides 100% coverage with clear descriptions for limit and offset, including defaults and value ranges. The description adds no additional parameter semantics, but none are needed beyond the schema.

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 operation: 'List all VLANs from LibreNMS.' The word 'all' suggests a global scope, which helps differentiate it from the sibling device_vlans that lists VLANs for a specific device. However, it does not explicitly name the sibling or state the distinction.

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 is given about when to use this tool versus alternatives. It does not mention that device_vlans should be used for per-device VLAN listing, nor does it explain any prerequisites or context. The intended use case is only implied by the name and short description.

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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