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Session Usage

get_session_usage
Read-only

Retrieve usage metrics for the current session: total tool calls, error count, aggregate duration and response size, per-tool counts, and timestamps. In-memory data resets when the server restarts or session goes idle.

Instructions

Return usage metrics for the current MCP session: total tool calls, error count, aggregate duration and response size, per-tool call counts, and session timestamps. Metrics are in-memory and reset when the server restarts or the session goes idle.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.1.1

TDQS

A4.3/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The readOnlyHint annotation already indicates the tool is read-only. The description adds valuable context by explaining that metrics are in-memory and reset on server restart or idle session, which clarifies the transient nature of the data. This goes beyond the annotation without contradicting it.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, with the primary action and target stated upfront. It uses two sentences without redundant phrases, listing the metrics in a clear and scannable manner. No fluff or unnecessary detail is present.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (no parameters, no output schema), the description fully covers what the tool returns (specific metrics) and its lifecycle behavior (in-memory, reset conditions). It provides enough context for an agent to call it correctly without additional clarifications.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

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 100% (empty schema). Per the rubric, a baseline of 4 is appropriate for 0 parameters. The description does not add parameter-specific meaning because there are none, but it correctly mentions session-bound behavior, which is not parameter-related.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function with a specific verb ('Return') and a well-defined scope ('usage metrics for the current MCP session'), enumerating the exact metrics returned. This distinguishes it from the many sibling get_* and list_* tools, which focus on other entities.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context by specifying 'for the current MCP session' and noting the reset behavior, but it does not explicitly state when to prefer this tool over alternatives or when not to use it. No mention of alternative tools like search or list operations is made, so guidance is only implicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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