NexTool MCP for GLPI

Create problem

glpi_create_problem

Create a new problem in GLPI with fields such as name, content, requester, and entity to log ITIL issues and support service desk workflows via MCP.

Instructions

Create a new problem. Common fields: name, content, entities_id, users_id_requester.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "input": "<input>"
    },
    "name": "glpi_create_problem"
  }
}

Input Schema

Name	Required	Description	Default
`input`	Yes	Problem fields

Output Schema

Name	Required	Description	Default
`data`	No
`replayed`	No	True when an identical recent create was returned instead of repeated

Schema Changelog

Changes observed during successful MCP inspections.

First observedv3.5.2Oct 5, 2026

TDQS

C2.9/5.0

Behavior2/5

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

Annotations declare non-readonly, non-idempotent, non-destructive, closed-world — the description adds essentially nothing beyond that. It does not mention required permissions, what the created object contains, or whether a followup/solution must be added separately.

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?

Two short sentences, front-loaded with the action. Minimal but not padded; the field list earns its place by hinting at expected keys.

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?

For a mutation tool with a fully open input object (additionalProperties), an output schema present, and a large sibling set, the definition is thin: no required-field info, no note that the returned payload is the created problem, no routing to related tools like glpi_add_problem_task or glpi_add_problem_solution.

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 coverage is 100% (the input object is free-form with additionalProperties), and the description names four common fields: name, content, entities_id, users_id_requester. That is useful orientation but does not explain requiredness, types, or the full accepted field set, which the free-form schema also leaves open.

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?

Specific verb+resource: 'Create a new problem.' Sibling set contains glpi_create_ticket and glpi_create_change, so the resource distinction (problem vs ticket vs change) is the key disambiguation and is stated. It does not explicitly call out the sibling distinction, keeping it at 4.

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 when-to-use guidance, no prerequisites, no mention of alternatives such as glpi_update_problem or glpi_create_ticket. The reader must infer usage entirely from the name.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server