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gingerlive-io

GingerLive MCP Server

Official
by gingerlive-io
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

Network stats

get_network_stats
Read-onlyIdempotent

Retrieve GingerLive's published network stats—streamer count, annual unique reach, monthly livestream viewing hours, and ad view-through rate—for scale and performance benchmarks.

Instructions

Returns GingerLive's network reach and performance figures: streamer count, annual unique reach, monthly hours of livestreams watched and ad view-through rate. Use when a user asks about scale or performance benchmarks; use list_case_studies for campaign-specific results. Read-only; figures are GingerLive's published network numbers.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
intentNoOptional: one short sentence on what the user is trying to accomplish, e.g. 'compare ad formats for a gaming product launch in Turkey'. Used only to improve this server's coverage. Do not include names, emails or other personal data.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.3.0
    • addedInput schema / properties / intent
      Added value: +{
+  "description": "Optional: one short sentence on what the user is trying to accomplish, e.g. 'compare ad formats for a gaming product launch in Turkey'. Used only to improve this server's coverage. Do not include names, emails or other personal data.",
+  "maxLength": 300,
+  "type": "string"
+}
  2. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive, and closed-world, so the safety profile is covered. The description adds provenance context ('GingerLive's published network numbers'), which tells the agent these are static published figures rather than live data — a useful behavioral detail beyond the annotations, though it doesn't cover freshness or caching.

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?

Two tightly packed sentences: the first front-loads what is returned, the second handles routing and read-only status. Every clause earns its place with no filler.

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?

Although there is no output schema, the description enumerates the returned figures precisely, and annotations cover the safety profile. An agent has everything needed to select and invoke this tool correctly.

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?

There is one optional parameter with 100% schema description coverage, so the schema already documents 'intent' fully. The description adds nothing about it, which is the expected baseline when the schema does the heavy lifting.

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?

States a specific verb+resource ('Returns GingerLive's network reach and performance figures') and enumerates the exact metrics returned (streamer count, unique reach, hours watched, view-through rate). This clearly separates it from sibling tools like list_case_studies or get_company_overview.

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?

Explicitly says when to use it ('when a user asks about scale or performance benchmarks') and names the alternative for the adjacent case ('use list_case_studies for campaign-specific results'). Nothing is left to inference.

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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