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nonmem-mcp-server

nonmem-mcp-server

by sueinchoi
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

check_r_setup

Verify R installation and essential packages for pharmacometric modeling workflows, ensuring compatibility with NONMEM analysis tools.

Instructions

Check R installation and required packages (mrgsolve, vpc, dplyr, ggplot2).

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": "check_r_setup"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior3/5

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

No annotations provided, so description carries full burden. Discloses what gets checked (R installation + 4 specific packages) but omits critical behavioral details: whether it auto-installs missing packages, throws errors, or returns structured status data. Lists packages but not failure modes.

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?

Single efficient sentence with no wasted words. Action verb front-loaded, specific package enumeration in parentheses provides clarity without verbosity. Appropriate length for the tool's scope.

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?

Given zero parameters and simple check purpose, description adequately covers inputs. Missing output specification (what constitutes pass/fail, return format) but sufficient for agent to understand tool's verification scope given the complexity level.

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?

Input schema contains zero parameters (empty object). Per scoring rules, 0 parameters establishes baseline score of 4. Description appropriately requires no additional parameter explanation.

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?

Description uses specific verb 'Check' with clear resource 'R installation and required packages', explicitly listing the four packages (mrgsolve, vpc, dplyr, ggplot2). Effectively distinguishes from sibling check tools like check_nonmem_setup and check_psn_status by specifying R ecosystem.

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?

No explicit when-to-use or when-not-to-use guidance provided. However, context implies usage before R-dependent operations (e.g., simulate_mrgsolve, generate_vpc_data). Lacks explicit prerequisites or sequencing guidance.

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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