nonmem-mcp-server
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@nonmem-mcp-server Summarize the results for run001 and check for diagnostic warnings."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
nonmem-mcp-server
MCP (Model Context Protocol) server for NONMEM pharmacometric modeling workflows. Gives Claude (and any MCP-compatible client) structured access to NONMEM models, results, and simulation tools.
Supports Windows, macOS, and Linux.
Features
Parsing & Analysis (no NONMEM needed)
read_ext_file— Parse .ext files for parameter estimates, SEs, OFV, condition numberread_lst_file— Extract termination status, shrinkage, covariance step resultsparse_control_stream— Structural parsing of .ctl/.mod files (THETAs, OMEGAs, $EST options)read_nm_dataset— Dataset summary: subjects, observations, missing valuesread_nm_tables— Parse SDTAB/PATAB with statistics for CWRES, ETAs, PREDcompare_models— Multi-run OFV comparison with delta-OFV and AICsummarize_run— Combined .ctl + .ext + .lst summarylist_runs— Scan project directories for NONMEM runs
Execution & Diagnostics
submit_run— Start NONMEM runs (async, fire-and-poll pattern)check_run_status— Monitor iteration progress via .ext fileget_run_results— Retrieve parsed results when completecancel_run— Kill running NONMEM jobsrun_diagnostics— Automated checks: boundary, condition number, shrinkage, RSEexecute_psn_vpc— Run VPC via PsN (predcorr, stratify, lloq options)execute_psn_bootstrap— Run bootstrap via PsN (BCa, stratify)check_psn_status— Monitor PsN job progressparse_psn_results— Parse existing PsN output directories (no installation needed)check_nonmem_setup— Detect NONMEM, PsN, R installation status
Simulation (no NONMEM needed)
translate_to_mrgsolve— Convert NONMEM .ctl/.mod to mrgsolve model codesimulate_mrgsolve— Run PK simulations via mrgsolve (R)generate_vpc_data— Generate VPC data using mrgsolve + vpc R packagecheck_r_setup— Check R and package availability
Prompts
review_model— Model review checklistinterpret_results— Pharmacological interpretationtroubleshoot_run— Diagnose run failuressuggest_next_model— Suggest next modeling stepswrite_methods_section— Draft publication Methods text
Related MCP server: simple-fal-mcp
Requirements
Python 3.12+
uv (recommended) or pip
Optional
NONMEM 7.3–7.6 — Required for
submit_run(commercial license)PsN — Required for
execute_psn_vpc,execute_psn_bootstrapR with
mrgsolve,vpc,dplyr,ggplot2— Required for simulation and GOF tools
Installation
Using uv (recommended)
git clone https://github.com/sueinchoi/nonmem-mcp-server.git
cd nonmem-mcp-server
uv syncUsing pip
pip install git+https://github.com/sueinchoi/nonmem-mcp-server.gitOr for development:
git clone https://github.com/sueinchoi/nonmem-mcp-server.git
cd nonmem-mcp-server
pip install -e .NONMEM Path Configuration
The server auto-detects NONMEM from common install locations. If auto-detection fails, set one of these environment variables:
Variable | Description | Example |
| Full path to nmfe executable |
|
| NONMEM installation root |
|
Auto-detected paths
macOS / Linux:
/opt/nm760/run/nmfe76,/opt/NONMEM/nm75/run/nmfe75, etc./usr/local/NONMEM/nm76/run/nmfe76~/NONMEM/nm76/run/nmfe76
Windows:
C:\nm760\run\nmfe76.bat,C:\NONMEM\nm76\run\nmfe76.batC:\Program Files\NONMEM\nm76\run\nmfe76.batD:\NONMEM\nm76\run\nmfe76.bat
Usage with Claude Code
Basic (no NONMEM)
claude mcp add nonmem -- nonmem-mcpWith uv (from source)
claude mcp add -s user nonmem -- \
uv run --directory /path/to/nonmem-mcp-server python -m nonmem_mcpWith NONMEM path
# macOS / Linux
claude mcp add -s user \
-e NONMEM_NMFE_PATH=/opt/nm760/run/nmfe76 \
nonmem -- \
uv run --directory /path/to/nonmem-mcp-server python -m nonmem_mcp# Windows (PowerShell)
claude mcp add -s user `
-e NONMEM_NMFE_PATH=C:\nm760\run\nmfe76.bat `
nonmem -- `
uv run --directory C:\path\to\nonmem-mcp-server python -m nonmem_mcpVerify
claude mcp list
# nonmem: ... - ✓ ConnectedUsage with Claude Desktop
Add to claude_desktop_config.json:
macOS / Linux
{
"mcpServers": {
"nonmem": {
"command": "uv",
"args": ["run", "--directory", "/path/to/nonmem-mcp-server", "python", "-m", "nonmem_mcp"],
"env": {
"NONMEM_NMFE_PATH": "/opt/nm760/run/nmfe76"
}
}
}
}Windows
{
"mcpServers": {
"nonmem": {
"command": "uv",
"args": ["run", "--directory", "C:\\path\\to\\nonmem-mcp-server", "python", "-m", "nonmem_mcp"],
"env": {
"NONMEM_NMFE_PATH": "C:\\nm760\\run\\nmfe76.bat"
}
}
}
}Examples
# Summarize a NONMEM run
"Summarize the run in /path/to/run001/"
# Compare covariate models
"Compare OFV across all models in the covariate analysis directory"
# Diagnose a failed run
"Why did this run fail? Check /path/to/run.lst"
# Systematic model development
"Develop a 2-compartment model with forward IIV addition"
# Translate to mrgsolve for simulation
"Convert my NONMEM model to mrgsolve and run a VPC"
# GOF plots
"Generate GOF plots for run015 with IPRED and CWRES"Capability Matrix
Feature | No NONMEM | + NONMEM | + PsN |
Parse .ext/.lst/.ctl | ✓ | ✓ | ✓ |
Model comparison | ✓ | ✓ | ✓ |
Diagnostics | ✓ | ✓ | ✓ |
mrgsolve simulation | ✓ | ✓ | ✓ |
mrgsolve VPC | ✓ | ✓ | ✓ |
NONMEM execution | ✗ | ✓ | ✓ |
PsN VPC | ✗ | ✗ | ✓ |
PsN Bootstrap | ✗ | ✗ | ✓ |
Parse PsN results | ✓ | ✓ | ✓ |
Included Examples
The examples/theopp/ directory contains a complete model development workflow using the Theophylline dataset:
run001.ctl — 1-compartment base model (ADVAN2, FO)
run002.ctl — 2-compartment model (ADVAN4 TRANS4)
run003–005.ctl — 2-comp base models with different initial estimates (no IIV)
run006–010.ctl — Single IIV forward addition (CL, V2, Q, V3, KA)
run011–014.ctl — Double IIV forward addition (V2+CL, V2+KA, V2+Q, V2+V3)
run015.ctl — Final 1-comp model with FOCE+INTER, IPRED, CWRES
gof_plot_v2.R — GOF plotting script (DV vs PRED/IPRED, CWRES, QQ plot)
License
MIT
Available Tools
22 toolscancel_runA
Cancel a running NONMEM job.
Inputs: job_id (required).
check_nonmem_setupA
Check NONMEM, PsN, R, and mrgsolve installation status and paths.
Inputs: no named parameters.
check_psn_statusC
Check status and progress of a PsN VPC or bootstrap job.
Inputs: job_id (required).
check_r_setupA
Check R installation and required packages (mrgsolve, vpc, dplyr, ggplot2).
Inputs: no named parameters.
check_run_statusB
Check the status and progress of a submitted NONMEM run by job ID.
Inputs: job_id (required).
compare_modelsA
Compare multiple NONMEM runs by OFV, delta-OFV, parameter counts, and AIC. Accepts a list of run directories or .ext file paths.
Inputs: models (required).
execute_psn_bootstrapA
Run bootstrap using PsN (async). Returns job ID for polling. Requires PsN + NONMEM.
Inputs: model_path (required), samples, options.
execute_psn_vpcA
Run VPC using PsN (async). Returns job ID for polling. Requires PsN + NONMEM.
Inputs: model_path (required), samples, options.
generate_vpc_dataA
Generate VPC data using mrgsolve + vpc R package. No NONMEM needed. Requires observed data and model.
Inputs: observed_data_path (required), model_code, model_file, n_sim, +4 more.
get_run_resultsB
Get full parsed results of a completed NONMEM run by job ID.
Inputs: job_id (required).
list_runsA
Scan a project directory for NONMEM run files and list their status (completed/failed/running).
Inputs: project_dir (required), recursive.
parse_control_streamA
Parse a NONMEM control stream (.ctl/.mod) into structured components: $THETA, $OMEGA, $SIGMA, $EST options, input columns, data file, and ADVAN/TRANS.
Inputs: file_path (required).
parse_psn_resultsA
Parse results from an existing PsN output directory (VPC or bootstrap). No PsN/NONMEM installation needed.
Inputs: results_dir (required).
read_ext_fileA
Parse a NONMEM .ext file to extract parameter estimates, standard errors, OFV, eigenvalues, and condition number.
Inputs: file_path (required).
read_lst_fileA
Parse a NONMEM .lst file for termination status, minimization success, shrinkage, condition number, and warnings.
Inputs: file_path (required).
read_nm_datasetA
Read and summarize a NONMEM dataset: subject count, observation count, dose records, missing values, and column overview.
Inputs: file_path (required), input_columns.
read_nm_tablesB
Parse NONMEM table output files (SDTAB, PATAB, etc.) and compute summary statistics for key columns (CWRES, PRED, IPRED, ETAs).
Inputs: file_path (required).
run_diagnosticsA
Run comprehensive post-run diagnostics: boundary checks, condition number, shrinkage, precision (RSE), convergence warnings. No NONMEM needed.
Inputs: run_dir (required), run_name.
simulate_mrgsolveA
Run a simulation using mrgsolve (R). No NONMEM needed. Provide model code or model file path.
Inputs: model_code, model_file, data_path, n_subjects, +6 more.
submit_runA
Submit a NONMEM run (async). Returns a job ID for polling. Requires NONMEM installation.
Inputs: ctl_path (required), work_dir, nmfe_path, run_name.
summarize_runB
Generate a comprehensive summary of a NONMEM run by combining control stream, .ext, and .lst results.
Inputs: run_dir (required), run_name.
translate_to_mrgsolveA
Translate a NONMEM control stream (.ctl/.mod) to mrgsolve model code. Handles ADVAN1-13, THETAs, OMEGAs, $PK, $DES, $ERROR.
Inputs: ctl_path (required), output_path, parameter_values.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 22 tools
Most tools have clearly distinct purposes, such as 'cancel_run' for job cancellation versus 'submit_run' for job submission. However, some overlap exists, like 'check_run_status' and 'list_runs' both providing run status information, which could cause mild confusion in selection.
Tool names follow a highly consistent verb_noun pattern throughout, such as 'cancel_run', 'check_nonmem_setup', and 'parse_control_stream'. There are no deviations in naming conventions, making the set predictable and readable.
With 22 tools, the count is borderline high for a NONMEM-focused server, potentially feeling heavy. While many tools are specialized for tasks like diagnostics and parsing, the number might overwhelm agents, though it aligns with the comprehensive scope of NONMEM modeling workflows.
The tool surface provides complete coverage for NONMEM modeling, including setup checks, job submission, status monitoring, result parsing, diagnostics, and simulation. There are no obvious gaps, supporting full lifecycle management from data input to analysis and visualization.
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