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MCP Hello World Server

MCP Hello World Server

by Cedricnator
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript

calculate_sum

Add two numbers together to get their total sum. This tool performs basic arithmetic addition for any pair of numerical values.

Instructions

Calcula la suma de dos números

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "a": "<a>",
      "b": "<b>"
    },
    "name": "calculate_sum"
  }
}

Input Schema

NameRequiredDescriptionDefault
aYesEl primer número
bYesEl segundo número

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only describes the basic function (sum calculation) without mentioning any behavioral traits like error handling, performance limits, or output format. For a tool with no annotations, this is a significant gap in transparency.

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, efficient sentence in Spanish that directly states the tool's purpose without any wasted words. It is appropriately sized and front-loaded, making it easy to understand at a glance. Every word earns its place by conveying essential information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (simple arithmetic), no annotations, no output schema, and high schema coverage, the description is minimally adequate. It covers the basic purpose but lacks details on behavior, usage context, or output, which could be helpful for an AI agent. It meets the minimum viable standard but has clear gaps.

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?

The input schema has 100% description coverage, with clear descriptions for both parameters ('a' and 'b'). The description adds no additional meaning beyond what the schema provides, as it only restates that two numbers are involved. Given the high schema coverage, the baseline score of 3 is appropriate, as the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Calcula la suma de dos números' (Calculates the sum of two numbers). It specifies the verb (calculates) and resource (sum of two numbers), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from the sibling tool 'say_hello', which is a different function, so it doesn't reach the highest score.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It states what the tool does but offers no context about when it's appropriate, such as for arithmetic operations or in scenarios requiring addition. There are no exclusions or comparisons to other tools, leaving usage entirely implicit.

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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