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gingerlive-io

GingerLive MCP Server

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by gingerlive-io
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TypeScript
Remote

Get a case study

get_case_study
Read-onlyIdempotent

Retrieve a GingerLive campaign case study by slug, including title, date, URL, and full markdown write-up. Unknown slugs return a list of valid slugs.

Instructions

Returns one GingerLive campaign case study: title, date, URL and the full markdown write-up (brand, approach and results). Requires a slug from list_case_studies; an unknown slug returns the list of valid slugs. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesCase-study slug, e.g. 'turknet-x-gingerlive-case-study-gen-z-livestream-advertising-campaign'
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

A4.7/5.0
Behavior4/5

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

Annotations already declare read-only/idempotent/closed-world, so the 'Read-only' sentence is largely redundant. However the description adds real behavioral value beyond the annotations: the error semantics for an unknown slug and the warning that the payload is a full markdown write-up (i.e. potentially large). No pagination or size guidance, which keeps it short of a 5.

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, no filler, front-loaded with the return contents before the invocation requirement. Every sentence carries distinct information (what it returns, what it needs, what happens on error).

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?

There is no output schema, so the description carries the full burden of describing return values, and it does so field by field. Combined with the slug prerequisite and error behavior, an agent has everything needed to invoke this 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?

Schema coverage is 100%, so the schema alone would justify a baseline 3. The description adds provenance semantics the schema does not: the slug must come from list_case_studies and invalid values are recoverable. The optional 'intent' parameter is left to the schema, which documents it thoroughly.

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 precise verb (Returns) and a specific resource (one GingerLive campaign case study), then enumerates the returned fields (title, date, URL, full markdown write-up with brand/approach/results). The word 'one' plus the slug requirement cleanly separates it from the sibling list_case_studies.

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 names the prerequisite path ('Requires a slug from list_case_studies') and routes the agent to that sibling for discovery. It also states the failure mode ('an unknown slug returns the list of valid slugs'), so the agent knows both when to call this and what happens if it guesses wrong.

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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