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SightRadar MCP Server

SightRadar MCP Server

Official

Get usage

get_usage
Read-onlyIdempotent

Retrieve call and credit usage per operation, including daily series and stored-vector storage charges, to monitor SightRadar consumption over a selected date range.

Instructions

Calls and credits spent, per operation. granularity=summary (default) gives totals per op; daily gives a day-by-day series including storage charges; storage gives the daily stored-vector count and storage credits. Use days (1-365) or a from/to date range (YYYY-MM-DD). Free.

Input Schema

NameRequiredDescriptionDefault
toNoEnd date YYYY-MM-DD (with from; not for storage).
daysNoLook-back window in days (default 30; storage 90).
fromNoStart date YYYY-MM-DD (with to; not for storage).
granularityNoDefault summary.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already establish this as a read-only, idempotent, non-destructive, closed-world call, so the bar is lower. The description adds meaningful context beyond that: the call is free, and each granularity returns different content, including storage charges and stored-vector counts in the daily and storage modes.

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?

Three dense sentences with the core resource statement front-loaded, followed by mode behavior and date-window syntax. Nothing is redundant and every sentence carries distinct information.

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

Completeness4/5

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

There is no output schema, so the description carries the burden of describing returns, and it does so per granularity (per-op totals, day-by-day series, vector counts and storage credits). It stops short of specifying response field names or pagination, but the essential shape is conveyed.

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

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, with formats, min/max, and default notes already documented, so the baseline is 3. The description does add meaning for the enum, explaining what each granularity value actually returns, which goes modestly beyond the schema's terser 'Default summary.'

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

Purpose4/5

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

The description states a specific resource and measure: 'Calls and credits spent, per operation,' making clear this is a consumption-reporting tool. It does not explicitly name the closest sibling (get_balance) or distinguish itself from it, which keeps it short of a 5.

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 modes of use are implied through the granularity explanations, and the 'Free' note signals it costs nothing to call. However, there is no explicit when-to-use guidance or routing advice such as 'use get_balance for credit balance, get_usage for consumption breakdown,' so the agent must infer the division of labor.

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