NexTool MCP for GLPI

List knowledge base items

glpi_list_knowbase_items

Read-onlyIdempotent

List knowledge base articles from GLPI with optional pagination, field selection, and JSON or markdown output.

Instructions

List knowledge base articles with optional pagination.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "glpi_list_knowbase_items"
  }
}

Input Schema

Name	Required	Description
`range`	No	Pagination range, e.g. 0-49
`fields`	No	Field set: 'essential' (default, trims internal GLPI fields) or 'all'
`format`	No	Output format: 'json' (default) or 'markdown' (a table for listings, key/value lines for one item; returned in both the text and the structured result)

Output Schema

Name	Required	Description
`data`	No
`note`	No	Pagination hint: how to fetch the next page
`count`	No	Items in this page
`format`	No	'markdown' when data holds the markdown rendering

Schema Changelog

Changes observed during successful MCP inspections.

First observedv3.5.2Oct 5, 2026

TDQS

B3.2/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered by structured data. The description adds only that pagination is optional, with no detail on default page size, total counts, or ordering. Marginal value beyond annotations.

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 short sentence with the resource and the pagination note front-loaded and no filler. It is efficient, though extremely terse given three parameters and an output schema.

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

Completeness3/5

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

An output schema exists, so return values need not be described, and all three parameters are fully documented in the schema. Still, for a listing tool in a large sibling set, the description omits any guidance on filtering or when to prefer an alternative, leaving it minimally viable.

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% and both enums (fields, format) are documented in the schema itself. The description's mention of 'optional pagination' loosely maps to the range parameter but adds no syntax or default beyond what the schema already states, 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?

States a specific verb ('List') and resource ('knowledge base articles'), which cleanly separates it from the singular glpi_get_knowbase_item and from glpi_list_knowbase_categories. It does not explicitly name or contrast those siblings, so it stops short of a 5.

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?

The only usage hint is 'optional pagination', which describes a parameter rather than when to choose this tool. It never mentions glpi_get_knowbase_item for single items, glpi_search for querying, or any precondition, so the agent must infer routing on its own.

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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