TealFlowMCP

An MCP (Model Context Protocol) server that enables LLMs to discover, understand, and generate Teal R Shiny applications for clinical trial data analysis.

Currently supports two Teal module packages:

• teal.modules.general - General-purpose analysis modules
• teal.modules.clinical - Clinical trial-specific modules

Documentation

• Quickstart Guide - Get started with VSCode and GitHub Copilot
• Tool Reference - Complete reference for all 14 MCP tools
• Configuration Guide - Setup, usage examples, and FAQs

Quick Start

New to TealFlowMCP? Check out the Quickstart Guide for step-by-step instructions to get up and running with VSCode and GitHub Copilot.

Prerequisites

• Python 3.10+
• R (required for running generated Teal applications)

For development/source installation only:

• uv (Python project manager) - Installation guide

MCP Compatibility

This server implements the Model Context Protocol (MCP) standard and works with any MCP-compatible LLM client, including:

• Claude Code
• GitHub Copilot
• Cursor
• Other MCP-compatible tools that support the MCP stdio protocol

The server is LLM-agnostic—it provides tools that any LLM can use to build Teal applications.

Adding to Your Editor/IDE

For PyPI installation:

{
  "tealflow-mcp": {
    "command": "tealflow-mcp"
  }
}

For source installation:

{
  "tealflow-mcp": {
    "command": "uv",
    "args": ["--directory", "/absolute/path/to/TealFlowMCP", "run", "tealflow_mcp.py"]
  }
}

Replace /absolute/path/to/TealFlowMCP with the actual absolute path to your cloned repository.

Consult your editor's documentation for the exact location of the MCP configuration file. See the Quickstart Guide and Configuration Guide for detailed setup instructions.

Architecture

The MCP server is organized as a modular Python package for maintainability and extensibility:

TealFlowMCP/
├── tealflow_mcp.py            # Backward-compatibility wrapper
├── tealflow_mcp/              # Main package
│   ├── core/                  # Constants and enums
│   ├── data/                  # Data loaders
│   ├── knowledge_base/        # Metadata and templates
│   ├── models/                # Pydantic input models
│   ├── server.py              # MCP server implementation
│   ├── tools/                 # MCP tool implementations
│   └── utils/                 # Utilities and formatters
├── docs/                      # Documentation
├── tests/                     # Automated tests
├── sample_data/               # Sample ADaM datasets
├── .github/                   # CI/CD workflows
├── pyproject.toml             # Project metadata & dependencies
├── uv.lock                    # Lockfile for exact versions
└── README.md

Installation

Option 1: Install from PyPI (Recommended)

pip install tealflow-mcp

... View full README on GitHub