zendesk_execute_viewRun a saved view by id and return the matching tickets. Zendesk REST: GET /views/{id}/execute.json.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Numeric view id (required; from zendesk_list_views). | |
| page | No | Page number for offset pagination. | |
| sort_by | No | Field to sort the resulting tickets by. | |
| per_page | No | Records per page (max 100). | |
| sort_order | No | Sort direction: asc or desc. |
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 declare readOnlyHint=true, which covers the non-destructive nature. The description adds the REST endpoint but doesn't disclose pagination behavior, sort semantics, or response format; no contradictions.
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 concise sentence that front-loads the action and result, followed by a useful endpoint reference. Every element earns its place.
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 read-only operation with an output described as 'matching tickets,' the description is reasonably complete. It includes the REST endpoint and the outcome, while the schema covers parameter details. Lacking an output schema, it could mention response structure, but this is a minor gap.
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?
All parameters have schema descriptions, so the schema carries the meaning. The description adds only the context that the id refers to a view, which the schema already says ('view id'). No additional semantic value.
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 uses a specific verb ('Run'), a clear resource ('a saved view'), and an outcome ('return the matching tickets'). It also provides the exact REST endpoint, distinguishing it from sibling tools like zendesk_list_views and zendesk_search.
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 lacks guidance on when to choose this tool over alternatives like search or list_tickets. It only implies usage by naming the operation, and the id schema references list_views as a prerequisite.
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.