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DROMA MCP Server

DROMA MCP Server

Local
github.com/mugpengHealth1Updated 49w ago

About DROMA MCP Server

DROMA MCP Server connects AI assistants to DROMA cancer pharmacogenomics data and analysis. Researchers can manage datasets, load normalized molecular and drug-response data, explore associations, and export results.

Key features

  1. 01Manage and select datasets
  2. 02Load normalized molecular profiles
  3. 03Load drug-response data
  4. 04Query projects, samples, and features
  5. 05Analyze drug-omics associations
  6. 06Export data as CSV, Excel, or JSON

Use cases

  1. 01Load CCLE data for analysis
  2. 02Explore samples and features by project
  3. 03Analyze a drug and omic-feature pair
  4. 04Export cached data for further analysis

MCP support

It exposes DROMA dataset management, database queries, data loading, analysis, visualization, and export tools to MCP clients. It supports STDIO, HTTP, and SSE transports.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

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DROMA MCP Server

A Model Context Protocol (MCP) server for DROMA (Drug Response Omics association MAp) - enabling natural language interactions with drug-omics association analysis.

Website Python 3.10+ FastMCP Version

🚀 Overview

DROMA MCP Server bridges the gap between AI assistants and cancer pharmacogenomics analysis by providing a natural language interface to the DROMA.R and DROMA.Set packages.

It is a part of DROMA project. Visit the official DROMA website for comprehensive documentation and interactive examples.

Key Features
  • 🔗 Natural Language Interface: Ask questions about drug-omics associations in plain English
  • 📊 Dataset Management: Load and manage DROMA datasets (CCLE, gCSI, etc.) in memory
  • 📈 Data Loading & Normalization: Load molecular profiles and treatment response data with automatic z-score normalization
  • 🗂️ Multi-Project Support: Seamlessly work with data across multiple research projects
  • 💾 Smart Caching: Efficient data caching with metadata tracking for faster access
  • 📤 Data Export: Export analysis results to various formats (CSV, Excel, JSON)
  • ⚡ Multi-Modal Support: Works with various transport protocols (STDIO, HTTP, SSE)
  • 🔄 R Integration: Seamless integration with existing DROMA R packages via rpy2

📦 Installation

Prerequisites
  • Python 3.10+
  • R 4.0+ with DROMA.Set and DROMA.R packages
  • DROMA SQLite database
  • FastMCP 2.13+ (automatically installed)
Install via pip
pip install droma-mcp
Development Installation
git clone https://github.com/mugpeng/DROMA_MCP
cd DROMA_MCP
pip install -e .
R Dependencies

Ensure you have the DROMA R packages installed:

# Install DROMA.Set and DROMA.R packages
# devtools::install_github("mugpeng/DROMA_Set")
# devtools::install_github("mugpeng/DROMA_R")

🚀 Quick Start

1. Start the Server
# STDIO mode (for AI assistants) - default
droma-mcp run --db-path path/to/droma.sqlite

# HTTP mode (for web applications)
droma-mcp run --transport http --port 8000 --db-path path/to/droma.sqlite
2. MCP Client Configuration

Add to your MCP client configuration:

{
  "mcpServers": {
    "droma-mcp": {
      "command": "droma-mcp",
      "args": ["run", "--db-path", "path/to/droma.sqlite"]
    }
  }
}

🖥️ CLI Commands

CommandDescription
runStart the MCP server
testTest configuration and dependencies
validateValidate complete setup
export-configExport MCP client configuration

For detailed help: droma-mcp --help or droma-mcp run --help

🛠️ Available Tools

Dataset Management
  • load_dataset: Load DROMA datasets (CCLE, gCSI, etc.) into memory from database
  • list_loaded_datasets: Show which datasets are currently loaded in memory
  • set_active_dataset: Set the active dataset for subsequent operations
  • unload_dataset: Remove datasets from memory to free up resources
Data Loading & Analysis
  • load_molecular_profiles_normalized: Load molecular profiles (mRNA, CNV, methylation, etc.) with z-score normalization
  • load_treatment_response_normalized: Load drug response data with normalization
  • load_multi_project_molecular_profiles_normalized: Load data across multiple projects
  • load_multi_project_treatment_response_normalized: Load treatment response across projects
  • check_zscore_normalization: Verify normalization status of cached data
  • get_cached_data_info: Get information about cached datasets
  • export_cached_data: Export data to CSV/Excel/JSON formats
Database Query & Exploration
  • get_droma_annotation: Retrieve sample or drug annotation data from the database
  • list_droma_samples: List all available samples for a project with filtering options
  • list_droma_features: List all available features (genes, drugs) for a project and data type
  • list_droma_projects: List all projects available in the DROMA database
Visualization & Analysis
  • plot_drug_sensitivity_rank: Create drug sensitivity rank plots
  • analyze_drug_omic_pair: Analyze associations between drugs and omic features

💬 Example Usage

Essential Workflow

⚠️ Important: Before using any data loading functions, you must first load the dataset into memory:

"Load the CCLE dataset from the database and set it as active"

"Load mRNA expression data for ABCB1 gene from the CCLE dataset with z-score normalization"

"List all projects available in the DROMA database"

"Show me all available samples for the gCSI project that have mRNA data"

🔧 Configuration

Environment Variables
  • DROMA_DB_PATH: Default path to DROMA SQLite database
  • R_LIBS: Path to R libraries
  • DROMA_MCP_MODULE: Server module to load (all, data_loading, database_query, dataset_management, visualization, analysis)
  • DROMA_MCP_VERBOSE: Enable verbose logging

🔧 Troubleshooting

Common Issues

Import Errors: Run droma-mcp validate to check dependencies

R Integration Issues: Ensure R and DROMA packages are installed correctly

Database Connection: Verify database path with droma-mcp test --db-path path/to/droma.db

For more help, see the official DROMA website or open an issue on GitHub.

🤝 Contributing

Contributions are welcome! Please see our Contributing Guidelines for details.

📄 License

This project is licensed under the MPL-2 License - see the LICENSE file for details.

🔗 Related Projects

📞 Support

Citation

If you use DROMA MCP in your research, please cite:

Li, S., Peng, Y., Chen, M. et al. Facilitating integrative and personalized oncology omics analysis with UCSCXenaShiny. Commun Biol 7, 1200 (2024). https://doi.org/10.1038/s42003-024-06891-2


DROMA MCP - Bridging AI and Cancer Pharmacogenomics 🧬💊🤖

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.