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USONDIG

GLPI MCP

by USONDIG

search_tickets

Search GLPI tickets by keywords in titles, descriptions, or followups, combined with status, category, or assignee filters to return matching tickets for analysis.

Instructions

Recherche avancée de tickets via l'API GLPI /search/Ticket. Tous les paramètres sont optionnels et combinables (combinés en ET).

Trois portées de recherche textuelle, à ne pas confondre :

  • keywords : le titre seulement. Rapide, mais aveugle au corps du ticket et aux suivis. C'est la portée historique de cet outil.

  • content_keywords : la description du ticket (corps initial).

  • followup_keywords : le contenu des suivis. Indispensable pour l'analyse historique : sur la plupart des instances, l'essentiel de la connaissance d'investigation vit dans les suivis, pas dans les titres. Le nom d'un outil ou d'un correctif mentionné uniquement en cours de diagnostic ne se trouve que par cette portée.

Note de performance : content_keywords et followup_keywords produisent un LIKE '%motif%' côté MySQL. Sans index FULLTEXT, ces recherches sont sensiblement plus lentes que par titre — les combiner avec status, category_id ou ticket_type pour réduire l'ensemble balayé.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusNo
keywordsNo
category_idNo
range_limitNo
range_startNo
ticket_typeNo
assigned_user_idNo
content_keywordsNo
followup_keywordsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It usefully discloses that parameters are AND-combined and that content/followup searches use MySQL LIKE '%motif%' and are slower without a FULLTEXT index — real behavioral value. It omits return format, pagination behavior and any auth/permission notes.

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?

Well front-loaded: purpose first, then the three scopes, then the performance caveat. The bulleted structure is scannable. Slightly longer than strictly necessary but essentially every sentence carries information.

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?

For a 9-parameter search tool with no annotations, no output schema and 0% schema coverage, the description covers the hardest-to-guess semantics well. However it omits pagination (range_limit default 50, range_start) and assigned_user_id, which an agent needs to call it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It richly explains the three non-obvious text parameters (keywords=title, content_keywords=body, followup_keywords=followups) and names three filters. It leaves range_limit, range_start and assigned_user_id undocumented, so it does not fully cover the 9 parameters.

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 (Recherche), resource (tickets) and even the underlying API endpoint (/search/Ticket). It clearly distinguishes the tool's three text scopes from each other. It does not differentiate from sibling list_tickets/get_ticket, 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 Guidelines4/5

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

It gives strong when-to-use guidance for the three keyword scopes ('à ne pas confondre', followup_keywords indispensable pour l'analyse historique) and advises combining filters with status/category_id/ticket_type to limit the scan. It never states when to prefer this over list_tickets, so no explicit alternative routing.

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