Get user
zendesk_get_userFetch a single user by id. Zendesk REST: GET /users/{id}.json.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Numeric user id (required). |
zendesk_get_userFetch a single user by id. Zendesk REST: GET /users/{id}.json.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Numeric user id (required). |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, covering the read-only nature. The description adds the REST endpoint (GET /users/{id}.json), which is mild context. However, it does not disclose error behavior, authentication requirements, or other behavioral traits, so it adds limited value beyond the annotation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that states what the tool does and the API endpoint. There is no wasted wording, and it is immediately clear and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one parameter, no output schema, and a readOnlyHint annotation, the description is sufficient. It clearly identifies the resource and operation; the context needed to invoke it correctly is fully covered by the schema and annotation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides 100% coverage for the only parameter 'id', including its type and description. The description merely repeats 'by id' and adds no additional semantic meaning, so it does not elevate the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool fetches a single user by id, using the specific verb 'Fetch' and resource 'user'. It distinguishes this from sibling get_* tools by specifying the exact target (user vs organization, ticket, etc.), and also provides the REST endpoint for precision.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving a specific user's details by id, but it does not explicitly state when to use this tool versus alternatives like zendesk_current_user or zendesk_search_users. No exclusions or alternative guidance are provided, making the usage context merely implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have distinct purposes, but zendesk_search_users overlaps with zendesk_search (which can search users with type:user), and zendesk_update_ticket can also add a comment, overlapping with zendesk_add_ticket_comment. These create minor ambiguity but are clarified by descriptions.
All tools use a consistent 'zendesk_' prefix and snake_case, but naming patterns deviate slightly: zendesk_current_user lacks a 'get_' verb, and zendesk_execute_view uses 'execute' instead of 'list' or 'get'. Overall, the conventions are mostly uniform and readable.
19 tools is on the higher end but each corresponds to a distinct Zendesk API endpoint or operation. The count is well-scoped for a server covering tickets, users, organizations, views, macros, and satisfaction ratings, without excessive redundancy.
The ticket lifecycle is well covered (create, get, update, comment, list, search, metrics, views), and listing entities like orgs, groups, macros, and fields is supported. Minor gaps exist for user/organization updates and a plain list_users tool, but these are not critical for core support workflows.