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MCP Trust Registry

MCP Trust Registry

by saagpatel
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

get_methodology

Discover how trust grades are calculated and the honesty model that underpins them, providing transparency for evaluating MCP server reliability.

Instructions

Explain how trust grades are computed and the honesty model behind them.

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_methodology"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A3.9/5.0
Behavior2/5

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

No annotations are provided, and the description only states the purpose ('Explain...') without disclosing any behavioral traits such as read-only nature, authentication requirements, potential side effects, or return behavior. It carries the full burden but offers no transparency beyond the core function.

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?

The description is a single, focused sentence that directly conveys the tool's purpose without any redundant words or extra detail. It is perfectly sized for a tool with no parameters.

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?

Given the tool's simplicity (no parameters) and the presence of an output schema, the description is sufficient. It states what the tool explains, and since an output schema exists, the description does not need to describe return values. The description fully covers the necessary context for an agent to invoke the tool.

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, so the schema covers 100% by default. The baseline is 4 for zero-parameter tools, and the description adds no parameter-related information because none is needed. No additional meaning is required.

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 a specific verb and resource: 'Explain how trust grades are computed and the honesty model behind them.' This distinguishes it from sibling tools list_servers and check_server, which focus on server information rather than methodology.

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

Usage Guidelines3/5

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

The description implies usage when a user needs to understand trust grade computation or the honesty model, but it does not explicitly mention when not to use it or reference alternative tools. Sibling tools have different purposes, so context is clear but no explicit exclusions or alternatives are given.

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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