cdm-mcp-server 0.2.3

Develop MCP Servers for automate the work processes of the Clinical Data Manager.

Clinical Data Management MCP Server

A unified MCP (Model Context Protocol) server for automating Clinical Data Manager (CDM) workflows. Provides Excel comparison, DVS validation, PDF comparison, and more through any MCP-compatible AI agent.

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Available Tools

Excel & DB Spec

• read_excel_info: Reads an Excel file and returns its structure — sheet names, column names, row counts, and a preview of the first few rows. Use this first when sheet names or column names are unknown.
• compare_common_excel: Compares specific sheets of two Excel files and generates a difference report. Requires specifying the sheet name, header row, and primary key column.
• compare_db_spec: Compares full CDM DB Spec workbooks. Automatically detects header positions and updates the Revision History sheet.

DVS (Data Validation Specifications)

• download_dvs_grammar: Copies the bundled DVS Specification Grammar reference file (DVS_SPEC_GRAMMAR.md) to a specified directory. Use this when a user needs the grammar definition for writing or reviewing DVS Specifications column entries.
• validate_dvs_specifications: Reads a DVS Excel file, validates all Specification entries against the DVS grammar, and generates a detailed validation report. Reports syntax errors and auto-corrected suggestions where possible.
• check_dvs_consistency (requires MCP Sampling): Checks whether the natural language Description is logically consistent with the formal Specification for each DVS entry. Results are written to a new Excel report.

Google Calendar Integration

• download_timeline_template: Copies the bundled DM Timeline Excel template to a specified directory. Use this before filling in timeline data and calling make_google_calendar_csv.
• make_google_calendar_csv: Extracts key schedules from a Timeline Excel file and converts them into a CSV formatted for Google Calendar import.

Blank eCRF PDF Comparison

• compare_ecrf_pdf_single: Compares two Blank eCRF PDF files and produces a single side-by-side comparison PDF. Changed pages are shown with Before (left) and After (right) layouts. Annotation colors: red = deleted, green = added, yellow = modified.

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Installation

Windows users: This server must be run inside WSL (Windows Subsystem for Linux). All commands below should be run in a WSL terminal, not PowerShell or CMD. If WSL is not installed, follow Microsoft's WSL setup guide first.

After installing WSL, open a WSL terminal and execute below commands.

Step 1. Install uv

uv is a fast Python package manager. Installing it also gives you uvx, which runs packages without a separate Python installation.

Mac / Linux / WSL

curl -LsSf https://astral.sh/uv/install.sh | sh

Step 2. Set Up Your AI Agent

Follow the section for your AI agent. Each section covers registration, skill installation, and connection verification.

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Claude Code

Register the MCP server

claude mcp add --scope user cdm-server uvx cdm-mcp-server@latest

Install skills (optional)

uvx --from cdm-mcp-server cdm-install-skills --tool claude

Skills are installed into .claude/skills/ in your project directory.

Verify the connection

claude mcp list

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Gemini CLI

Prerequisite — Node.js

Gemini CLI requires Node.js. Install it via nvm if you don't have it.

Mac / Linux

curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.40.3/install.sh | bash
nvm install --lts

Windows — Download and install nvm-windows, then:

nvm install lts
nvm use lts

Install Gemini CLI and register the MCP server

npm install -g @google/gemini-cli
gemini mcp add cdm-server uvx --args cdm-mcp-server@latest --scope user

Install skills (optional)

uvx --from cdm-mcp-server cdm-install-skills --tool gemini

Skills are installed into .gemini/skills/ in your project directory.

Verify the connection

gemini mcp list

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Codex CLI

Register the MCP server

codex mcp add cdm-server -- uvx cdm-mcp-server@latest

Install skills (optional)

uvx --from cdm-mcp-server cdm-install-skills --tool codex

Skills are installed into .agents/skills/ in your project directory.

Verify the connection

codex mcp list

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You should see cdm-server listed as connected.

Install skills for all agents at once

If you use multiple AI tools in the same project directory, run:

uvx --from cdm-mcp-server cdm-install-skills --all

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Usage

Once connected, simply describe what you need in natural language:

"Compare the previous and current DB Spec files and generate a difference report."

"Validate the DVS file and report any syntax errors."

"Download the Timeline template, then convert the completed file into a Google Calendar CSV."

The AI agent will automatically select and call the appropriate tool.

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Troubleshooting

MCP server shows as disconnected

The most common cause is that uvx is not in the PATH when the AI tool launches the MCP server process.

1. Find the uvx location

which uvx

2. Add its directory to PATH

Replace ~/.local/bin with the directory from the output above:

echo 'export PATH="$HOME/.local/bin:$PATH"' >> ~/.bashrc && source ~/.bashrc

For zsh:

echo 'export PATH="$HOME/.local/bin:$PATH"' >> ~/.zshrc && source ~/.zshrc

Then restart the AI tool and verify the connection again.

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Project Structure

src/
└── cdm_mcp_server/
    ├── __init__.py
    ├── server.py                   # MCP server entry point
    ├── templates/
    │   └── DM Timeline 20251120.xlsx  # Bundled Timeline template
    └── modules/
        ├── excel_theme.py          # Shared Excel formatting standards
        ├── excel_compare.py        # Excel & DB Spec comparison engine
        ├── excel_info.py           # Excel structure inspector
        ├── calendar_maker.py       # Timeline parsing & Calendar CSV generator
        ├── dvs_parser.py           # DVS specification grammar parser
        ├── dvs_excel_writer.py     # DVS validation report writer
        ├── dvs_consistency_checker.py  # LLM-powered DVS consistency checker
        └── pdf_ecrf_compare.py     # Blank eCRF PDF comparison engine