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GLPI MCP

GLPI MCP

by USONDIG
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

update_supplier

Modify existing supplier records in GLPI by passing only the fields to change, including restoring trashed suppliers with is_deleted: 0.

Instructions

Met à jour un fournisseur. Passer uniquement les champs à modifier. Exemples de champs : name, suppliertypes_id, address, town, phonenumber, email, website, comment, is_active Pour restaurer un fournisseur mis à la corbeille : {"is_deleted": 0}

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": {
      "supplier_id": "<supplier_id>",
      "update_fields": "<update_fields>"
    },
    "name": "update_supplier"
  }
}

Input Schema

NameRequiredDescriptionDefault
supplier_idYes
update_fieldsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
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 partial-update semantics and soft-delete restoration via is_deleted, but omits permissions, side effects, output behavior, and whether unspecified fields are preserved or cleared.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core action, then compact usage guidance and a concrete restore example. The field list is useful rather than filler, and no sentence is wasted.

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 an unannotated mutation tool with no output schema and 0% schema coverage, the description gives useful field examples and restore behavior but omits permission requirements, error semantics, and supplier_id meaning. Enough to attempt a call, not enough to call confidently in all cases.

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 coverage is 0%, so the description must compensate. It enumerates example update_fields and documents the special is_deleted restore pattern, which is valuable beyond the bare schema; however, supplier_id remains undocumented and the field list is explicitly non-exhaustive.

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?

States a specific verb and resource ('Met à jour un fournisseur') and distinguishes it from create_supplier, delete_supplier, and list_suppliers in the sibling set. The partial-update instruction further clarifies how it differs from bulk field replacement.

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?

Gives clear context: pass only the fields to modify, and use is_deleted:0 specifically to restore a trashed supplier. It does not explicitly name alternatives or list when-not-to-use cases, but the usage context is unambiguous for an update tool.

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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