zendesk_list_viewsList saved ticket views (curated ticket lists). Use zendesk_execute_view to run one. Zendesk REST: GET /views.json.
| Name | Required | Description | Default |
|---|---|---|---|
| access | No | Filter by access: 'personal' or 'shared'. | |
| active | No | If true, only active views. |
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?
The annotation readOnlyHint=true already indicates a safe read operation. The description adds the REST endpoint 'GET /views.json' and the notion of 'curated ticket lists', but it does not disclose additional behavioral traits like pagination, ordering, or output format. This is adequate but not rich.
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?
Two sentences, front-loaded with the core action, and every word earns its place. It efficiently includes the purpose, clarification, alternative tool, and REST endpoint without fluff.
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 simple list tool with no required parameters, no output schema, and a read-only annotation, the description fully covers what the tool does, how to run one of the views, and the underlying API call. No essential context is missing.
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?
Schema description coverage is 100%, with both parameters ('access' and 'active') having clear descriptions. The description does not add parameter details, but the schema carries the full semantic burden, so a baseline score of 3 is appropriate.
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 verb 'List' and the resource 'saved ticket views', and clarifies what views are with 'curated ticket lists'. It also distinguishes from the sibling zendesk_execute_view by saying 'Use zendesk_execute_view to run one.'
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?
It explicitly provides an alternative: 'Use zendesk_execute_view to run one.' This tells the agent when to use this list tool versus the execution tool. No further exclusions are needed for a straightforward listing operation.
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.