Medical Calculator MCP Server

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get_related_tools

Find related medical calculators by analyzing shared parameters, specialty, and clinical context. Enter a tool ID to get a ranked list of similar tools for efficient discovery.

Instructions

🔗 取得相關工具 (High-Level 語義發現)

基於共享參數和專科自動發現相關工具。純 Python 算法，無 ML 依賴。

Args: tool_id: 工具 ID limit: 最多回傳幾個相關工具

Returns: 相關工具清單及相似度分數

Example:

get_related_tools("sofa_score")
# → {"related_tools": [
#      {"tool_id": "qsofa_score", "similarity": 0.85},
#      {"tool_id": "apache_ii", "similarity": 0.72},
#      ...
#    ]}

💡 相關性基於: 共享參數、相同專科、相同臨床情境

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No
`tool_id`	Yes

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.6.2Sep 1, 2026

TDQS

A3.8/5.0

Behavior4/5

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

With no annotations provided, the description carries the full behavioral burden. It discloses that the tool uses a pure Python algorithm with no ML dependency, performs high-level semantic discovery, and bases relevance on shared parameters, specialty, and clinical context. This adds meaningful behavioral context beyond a simple 'get related tools' statement.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a clear title, arg explanations, return note, and a compact example. It is slightly verbose with bilingual repetition and decorative emoji, but every substantive sentence contributes useful information.

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 straightforward discovery tool with two parameters and an output schema, the description is sufficiently complete. It explains what the tool does, how relatedness is determined, what arguments are needed, and what the response looks like. It does not discuss error cases or performance, but these are not critical given the tool's simplicity.

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 description coverage is 0%, so the description compensates by defining tool_id as the tool identifier and limit as the maximum number of related tools to return. The example further clarifies expected usage and output shape. It could add more detail about default behavior or edge cases, but the basics are well covered.

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 verb and resource: it 'gets related tools' based on shared parameters and specialty. It adds a high-level semantic discovery framing that helps distinguish it from sibling tools like find_tools_by_params, though it does not explicitly name a sibling for contrast.

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 when to use the tool—when related-tool discovery based on parameter/specialty similarity is needed—and gives an example. However, it does not explicitly state when not to use it or how it differs from alternatives such as discover or find_tools_by_params.

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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