nonmem-mcp-server
An MCP server for NONMEM pharmacometric modeling that provides structured access to model parsing, execution, and results analysis. It enables users to perform diagnostics, manage PsN workflows, and translate models to mrgsolve for PK simulations through natural language.
README
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.
Features
Phase 1: 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
Phase 2: 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
Phase 3: 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
Requirements
- Python 3.12+
- uv (recommended) or pip
Optional
- NONMEM — Required for
submit_run(commercial license) - PsN — Required for
execute_psn_vpc,execute_psn_bootstrap - R with
mrgsolve,vpc,dplyr— Required for simulation tools
Installation
git clone https://github.com/sueinchoi/nonmem-mcp-server.git
cd nonmem-mcp-server
uv sync
Usage with Claude Code
claude mcp add -s user nonmem -- \
uv run --directory /path/to/nonmem-mcp-server python -m nonmem_mcp
With NONMEM installed:
claude mcp add -s user \
-e NONMEM_NMFE_PATH=/opt/NONMEM/nm75/run/nmfe75 \
nonmem -- \
uv run --directory /path/to/nonmem-mcp-server python -m nonmem_mcp
Verify:
claude mcp list
# nonmem: ... - ✓ Connected
Usage with Claude Desktop
Add to claude_desktop_config.json:
{
"mcpServers": {
"nonmem": {
"command": "uv",
"args": ["run", "--directory", "/path/to/nonmem-mcp-server", "python", "-m", "nonmem_mcp"],
"env": {
"NONMEM_NMFE_PATH": "/opt/NONMEM/nm75/run/nmfe75"
}
}
}
}
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"
# Translate to mrgsolve for simulation
"Convert my NONMEM model to mrgsolve and run a VPC"
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 | ✓ | ✓ | ✓ |
License
MIT
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.