Logout
logoutSign out of this MCP session.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
logoutSign out of this MCP session.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 indicate the operation is not read-only and not destructive. The description adds useful scoping by stating this affects only the current MCP session, but it does not disclose side effects such as invalidated authentication or behavior when called without an active session.
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 short sentence with no filler or redundant restatement of the title. The action and its scope are front-loaded and immediately readable.
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 parameterless tool with no output schema, the description conveys the core action and scope, which is largely sufficient for invocation. It leaves minor gaps around post-conditions and error behavior, but the low complexity makes the definition acceptable.
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 tool has zero parameters and the schema coverage is complete, so there are no parameter semantics for the description to clarify. The baseline for parameterless tools applies and no additional parameter explanation is needed.
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 names a specific verb ('Sign out') and a specific scope ('this MCP session'), so the action is unmistakable. It does not explicitly compare with sibling tools like login or whoami, but the semantics are distinct enough to prevent selection errors.
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 intended usage is implied: call logout when the current MCP session should end. However, the description gives no explicit guidance about prerequisites, when not to call it, or how it relates to login/whoami, leaving the usage context mostly 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 clearly distinct purposes, and the descriptions carefully separate operations like attendance_report, list_classes, and get_class_roster. A few reads overlap conceptually (get_client, get_reservation_history, get_credit_history, get_client_notes all return client-related data), but each has a specific output that an agent can distinguish with reasonable effort.
Tool names overwhelmingly follow a consistent action_object pattern: add_client_note, cancel_class, freeze_membership, refund_order, set_client_tag, unfreeze_membership. The get_/list_ prefix distinction is used predictably, and auth tools (login, logout, whoami) are standard exceptions rather than inconsistent naming.
41 tools is well beyond the 25+ threshold for a heavy tool set. Although each tool appears to serve a real studio-operations need, the sheer number creates a large surface for an agent to navigate and places significant burden on selection accuracy.
The tool set covers the core lifecycle well across clients, classes, memberships, orders, payments, and communications, with no obvious dead ends. Minor gaps exist, such as no update_client profile tool and no class-scheduling creation, but staff workflows can generally be completed.