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Search user by email

glpi_search_user_by_email
Read-onlyIdempotent

Search for a GLPI user by exact email address to retrieve their ID, login, real name, and first name.

Instructions

Find users by exact email address (returns the user items: id, login, real name, first name...).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailYesEmail address
rangeNoPagination range, e.g. 0-49
fieldsNoField set: 'essential' (default, trims internal GLPI fields) or 'all'
formatNoOutput 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

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
noteNoPagination hint: how to fetch the next page
countNoItems in this page
formatNo'markdown' when data holds the markdown rendering

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv3.5.2

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent and non-destructive, so safety is covered. The description adds the useful 'exact' match semantics and lists returned item fields, but says nothing about no-match behavior, rate limits, or result cardinality.

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?

A single front-loaded sentence that leads with the action and lookup key, with no filler. Slightly terse rather than wasteful.

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

Completeness4/5

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 needn't be explained, and annotations carry the safety profile. The description is complete enough to select and call the tool, with only minor gaps around match behavior.

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%, so the schema fully documents email, range, fields and format. The description adds no parameter syntax or format detail beyond what the schema already provides, so 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 (Find) and resource (users) plus the discriminating lookup key ('exact email address'). This distinguishes it from glpi_get_user and glpi_list_users, though it doesn't name those siblings explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

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

Usage is implied by 'by exact email address' – an agent can infer this is the email-lookup path. However, it gives no explicit when-to-use/when-not guidance versus glpi_search or glpi_list_users, and no exclusion for fuzzy/partial matching.

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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