nonmem-mcp-server

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parse_control_stream

Extract structured components from NONMEM control streams, including parameters, estimation options, and model specifications, for pharmacometric analysis.

Instructions

Parse a NONMEM control stream (.ctl/.mod) into structured components: $THETA, $OMEGA, $SIGMA, $EST options, input columns, data file, and ADVAN/TRANS.

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": {
      "file_path": "<file_path>"
    },
    "name": "parse_control_stream"
  }
}

Input Schema

Name	Required	Description	Default
`file_path`	Yes	Path to the .ctl or .mod file

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Mar 30, 2026

TDQS

A3.8/5.0

Behavior3/5

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

No annotations provided, so description carries full burden. It discloses what gets extracted (structural components) but omits safety characteristics (read-only vs. destructive), error handling for malformed files, or validation behavior. 'Parse' implies non-destructive reading but this isn't explicitly stated.

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 dense sentence with zero waste. Front-loaded with action ('Parse'), immediately identifies resource ('NONMEM control stream'), qualifies with extensions, and uses colon-delimited list for output specifics. Every clause earns its place.

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 no output schema exists, the description effectively compensates by listing specific extracted components ($THETA, $OMEGA, etc.), giving users clear expectations of return value structure. Slight gap regarding whether it returns JSON, nested objects, or flat structure.

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?

Schema has 100% coverage with clear description ('Path to the .ctl or .mod file'). The description reinforces the file type context but doesn't add additional semantics like path format requirements (absolute vs. relative) or file encoding expectations. Baseline 3 appropriate for high schema coverage.

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?

Excellent specificity: 'Parse' (clear verb), 'NONMEM control stream' (specific resource), file extensions (.ctl/.mod), and enumerated components ($THETA, $OMEGA, etc.) clearly distinguish it from sibling tools like read_lst_file or parse_psn_results which handle outputs rather than input control files.

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?

Provides implied usage through the specific components listed (parameter structures vs. execution/results), but lacks explicit guidance such as 'use this to inspect model structure before running' or contrasts with siblings like read_nm_dataset which reads data files rather than control files.

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