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mcp-agrus-ai

mcp-agrus-ai

by phwizard
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

get_case_study

get_case_study

Retrieve NDA-protected Agrus case studies by slug or vertical, or list all, to verify prior work.

Instructions

Returns one or more Agrus case studies (NDA-protected; customer names are kept private, codenames + technology + outcomes are open). Filter by slug or vertical, or call with no args to list all. Use this for proof of prior work.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_case_study"
  }
}

Input Schema

NameRequiredDescriptionDefault
slugNoSpecific case-study slug. If omitted, returns all available case studies (filtered by vertical if provided).
verticalNoFilter case studies by vertical. Ignored if slug is provided.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.6/5.0
Behavior5/5

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

No annotations provided; the description fully bears the transparency burden. It discloses NDA protection, privacy of customer names, and openness of codenames/technology/outcomes, which is critical for safe agent usage. Implies read-only 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?

Two sentences with zero waste. Front-loaded with core purpose and constraints, followed by usage patterns. No unnecessary repetitions.

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 simple list tool with 0 required parameters and 2 optional parameters in the schema, the description provides sufficient context about the tool's output and constraints. No output schema is present, and the description hints at return content. Could mention pagination but not necessary for this use case.

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%, but the description adds meaningful context: slug for specific case study, vertical as filter, and the priority rule (slug overrides vertical). This adds value beyond the schema alone.

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 clearly states it returns one or more Agrus case studies with specific content (codenames, technology, outcomes). It uses a specific verb 'Returns' and distinguishes from sibling tools by stating 'Use this for proof of prior work'.

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

Usage Guidelines4/5

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

Provides explicit filtering options (slug or vertical, or call with no args) and a usage context ('for proof of prior work'). However, it does not specify when not to use it or mention alternative tools directly, though siblings are distinct enough.

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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