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nonmem-mcp-server

nonmem-mcp-server

by sueinchoi
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

check_run_status

Monitor the progress and status of a submitted NONMEM pharmacometric modeling run using its job ID to track execution and completion.

Instructions

Check the status and progress of a submitted NONMEM run by job ID.

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": {
      "job_id": "<job_id>"
    },
    "name": "check_run_status"
  }
}

Input Schema

NameRequiredDescriptionDefault
job_idYesJob ID from submit_run

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

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 identifies the read-only nature of 'checking' but fails to disclose what status values mean, whether results are real-time or cached, error conditions (e.g., invalid job_id), or side effects.

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 that front-loads the verb ('Check') and contains no redundant or wasted words. The length is appropriate for the tool's simplicity.

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?

For a single-parameter tool with no output schema, the description adequately covers the basic invocation pattern. However, it misses opportunities to add value given the lack of annotations—specifically, it omits what status states to expect (running, completed, failed) or polling recommendations.

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?

With 100% schema description coverage, the schema fully documents the single 'job_id' parameter including its provenance from 'submit_run'. The description adds minimal semantic value beyond the schema ('by job ID'), meeting the baseline for high-coverage schemas.

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 specific action ('Check'), resource ('status and progress'), and scope ('submitted NONMEM run'). It implies distinction from sibling 'get_run_results' by emphasizing status/progress rather than final results, though it doesn't explicitly contrast with alternatives.

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 explicit guidance on when to use this tool versus alternatives like 'get_run_results' or 'list_runs'. While the schema notes the job_id comes from 'submit_run', the description lacks workflow context such as 'use this to monitor execution before retrieving final results'.

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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