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scienceon-mcp

scienceon-mcp

by rubatoyd
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

scienceON_status

Read-only

Diagnose ScienceON connection and token issues: returns cause hints and current public IP when checks fail.

Instructions

ScienceON 연결/토큰 상태 점검. 실패 시 원인 힌트와 현재 공인 IP 를 반환.

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": "scienceON_status"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.2.0

TDQS

A4.2/5.0
Behavior4/5

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

The description goes beyond the readOnlyHint and openWorldHint annotations by explaining that on failure it returns cause hints and the current public IP. This adds valuable behavioral context without contradicting the annotations.

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 immediately states the tool's purpose and failure behavior. No redundant or extraneous information is included.

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 zero-parameter read-only status check, the description covers the essential purpose and failure behavior. However, it does not specify what success returns (e.g., success status or token validity), which is a minor gap for a health-check 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 parameter semantics are trivially satisfied. The empty schema and lack of parameters mean the description does not need to explain parameter meaning; baseline 4 is appropriate.

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 specifies a clear action ('check ScienceON connection/token status') and resource, distinguishing it from sibling tools like scienceON_search or scienceON_detail. It also mentions the failure response, adding purpose specificity.

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?

Usage is implied (checking status before or during interactions with ScienceON), but there is no explicit guidance on when to use this tool versus alternatives, nor any exclusions. The name and description make the primary use case evident, but no direct guidance is provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

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