get_ticketRead one ticket and its full message thread. Each message has an author: you or staff — a staff message is a reply from support. Poll this to see new answers. The ticket code comes from create_ticket / list_tickets.
| Name | Required | Description | Default |
|---|---|---|---|
| ticket_code | Yes |
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?
With no annotations, the description carries the full burden of behavioral disclosure. It reveals that the tool returns the full message thread, that each message has an author field with values 'you' or 'staff', and that 'staff' messages are replies from support. This goes beyond a bare 'read' operation and gives useful behavioral context, though it omits details like error handling or rate limits.
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 three short sentences with no filler. The opening sentence immediately states the purpose, followed by useful message-thread details and a sourcing hint. Every sentence 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 simple one-parameter read tool with no output schema, the description covers the essential use case, message structure, and polling behavior. It could be slightly more explicit about the return shape, but it is complete enough for an agent to invoke correctly.
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 0%, so the description compensates by explaining what the single parameter 'ticket_code' is used for and where to obtain it ('comes from create_ticket / list_tickets'). This adds meaning beyond the schema's bare type/minLength definition, though it does not specify the exact format or length constraints.
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 ('Read') and resource ('one ticket and its full message thread'), clearly distinguishing it from sibling tools like list_tickets, create_ticket, reply_ticket, and close_ticket. It immediately conveys the tool's core function without ambiguity.
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 states when to use the tool ('Poll this to see new answers') and where the input comes from ('The ticket code comes from create_ticket / list_tickets'). It does not explicitly mention when not to use it, but the context is clear enough for an AI agent to select it appropriately.
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.
Tools are cleanly separated into auth, billing, VPS lifecycle, tickets, and delegation, and each maps to a distinct resource/action. A few pairs like set_password vs reset_password and pay_invoice vs topup_balance share surface similarity, but their descriptions draw clear boundaries.
Naming is strongly consistent with verb_noun snake_case patterns such as order_vps, list_tickets, and revoke_delegation. Minor deviations are the bare CLI-style verbs login and whoami, plus the slightly awkward topup_balance, but these do not undermine the overall pattern.
27 tools is on the high side, but the server covers several distinct subdomains—account management, billing, VPS operations, support tickets, and delegations—and each tool appears to earn its place. The count is heavy but not unreasonable for the breadth of functionality exposed.
Core workflows are covered end-to-end: account creation/login, ordering and provisioning, power/reinstall/cancel, ticket conversations, and delegation management all have the necessary operations. Minor gaps exist, such as no change-password tool, no explicit RDNS/console tool despite delegation mentioning them, and no plan upgrade/downgrade tool.