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vantagemcp

vantage-mcp

by vantagemcp
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

get_usage

Read-onlyIdempotent

Check remaining quota units for the current billing period before running batch calls. See whether your citation checks will fit within the limit.

Instructions

Check how much of this billing period's quota is left, before spending any of it. Use this to answer 'how many checks do I have left' or to decide whether a batch call will fit before running it.

Costs 0 quota units - this never touches the paid data provider, it only reads Vantage's own record of what has been used.

Returns: {"tier", "period" (YYYY-MM), "units_used", "units_limit", "units_remaining"}. find_citation_leaders and find_cited_questions cost 10 units/call; analyze_citation_trend, analyze_citation_structure (and its batch form, per keyword), check_prompt_coverage (per keyword) and analyze_citation_gap cost 1, times samples where a tool takes it. get_check_history costs 0.

stdio/local-dev mode (no HTTP access token) has no metering at all - this returns tier "unmetered" with no real limit in that case.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.6.0

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the readOnly/idempotent annotations, the description discloses that the call costs 0 quota units, never touches the paid data provider, returns a specific field set, and behaves differently in unmetered stdio/local-dev mode. This is valuable non-obvious behavior.

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?

Every sentence carries essential information: purpose, use case, cost behavior, return fields, sibling costs, and environment-specific behavior. The main purpose is front-loaded and the additional details are compactly grouped.

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?

Even though there is no output schema, the description enumerates the returned fields. It also covers quota semantics, environment behavior, and the relationship to sibling tools, so an agent has everything needed to invoke and interpret this tool correctly.

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)Skip; the input schema is already fully complete. With no parameters to document, the description doesn't need to add parameter-level detail. Baseline 4 applies.

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 opens with a specific verb and resource: 'Check how much of this billing period's quota is left'. It also distinguishes itself from siblings by noting it 'never touches the paid data provider' and only reads Vantage's own usage record.

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

Usage Guidelines5/5

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

It explicitly states when to use the tool: before spending quota, to answer quota questions like 'how many checks do I have left', and to decide if a batch call fits. It also lists the quota costs of sibling tools, making the workflow context clear.

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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