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gingerlive-io

GingerLive MCP Server

Official
by gingerlive-io
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TypeScript
Remote

Streamer program

get_streamer_program_info
Read-onlyIdempotent

Learn how livestreamers join and earn with GingerLive, including free streamer cost, in-stream ad program, supported platforms, and sign-up link.

Instructions

Returns how livestreamers join and earn with GingerLive: cost (free for streamers), how the in-stream ad program works, supported platforms and the sign-up link. Use for creator or streamer monetization questions; for brand-side questions use get_company_overview or list_ad_formats instead. Read-only; public program information.

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

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/destructive=false, so the safety profile is covered. The description still adds useful context beyond annotations: the tool returns public program information and that the ad program is in-stream. It does not cover scope limitations or return format, but with annotations carrying the safety burden this is solid.

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 sentences, front-loaded with what is returned, followed by routing guidance and a safety note. No waste.

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?

For a read-only informational tool with no output schema and a fully documented optional param, the description covers purpose, usage, and routing. Minor gap: it doesn't hint at the shape of the returned info (e.g., plans or program tiers), but nothing critical is missing.

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?

Single optional 'intent' param at 100% schema coverage, so the schema already explains it. The description needn't add param detail, and it correctly adds nothing redundant.

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 and resource: returns how livestreamers join and earn with GingerLive, and enumerates the returned content (cost, ad program, platforms, sign-up link). This distinguishes it from generic company/stat tools and from the sibling list_ad_formats it explicitly routes away from.

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?

Explicit when-to-use ('creator or streamer monetization questions') and names two alternatives with their own selection condition ('for brand-side questions use get_company_overview or list_ad_formats'). No inference required.

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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