biovis-mcp 0.1.0

A FastMCP server for publication-quality bioinformatics visualization

🧬 BioVis-MCP: Automated Bioinformatics Visualization

"From raw data to publication-ready figures in seconds."

BioVis-MCP is a high-performance Model Context Protocol (MCP) server that empowers Large Language Models (like Claude) with the ability to generate publication-quality (300 DPI) bioinformatics visualizations directly from raw biological data.

No more manual Matplotlib tweaking. Just send the data, and get a verified, manuscript-ready image path.

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✨ Features (Phases 1-3)

📊 Visualization Suite

• Volcano Plots: High-resolution visualization of differential expression, with automated significance highlighting (Up/Down regulated).
• PCA Plots: Principal Component Analysis for sample relationship and variance insights.
• Expression Heatmaps: Professional heatmaps with hierarchical clustering and customizable colormaps.
• MA Plots: Classic M-versus-A plots for global genomic trends.
• Pathway Enrichment: Horizontal bar charts and dynamic Bubble Charts (Gene Count vs. Significance).

📝 Reporting & AI Integration

• Smart Figure Captions: Context-aware, statistically accurate scientific captions generated automatically.
• Comprehensive Reports: Multi-figure assembly into professional PDF and DOCX documents.
• High DPI Standards: All figures are generated at 300 DPI using bbox_inches='tight' for Q1 journal compliance.

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🛠️ Tech Stack

• Framework: FastMCP
• Libraries: Pandas, Scikit-learn, Scipy, Matplotlib, Seaborn
• Export Formats: PNG (Figures), PDF & DOCX (Reports)

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🚀 Installation & Setup

1. Prerequisites

Ensure you have Python 3.10+ installed.

# Option A: Install from PyPI (Recommended)
pip install biovis-mcp

# Option B: Clone for development
git clone https://github.com/ZaEyAsa/biovis-mcp.git
cd biovis-mcp
pip install -e .

2. Connect to Claude Desktop

To integrate BioVis-MCP into your Claude Desktop, edit your claude_desktop_config.json file:

Location (Windows): %APPDATA%\Claude\claude_desktop_config.json

Add this configuration:

{
  "mcpServers": {
    "BioVis-MCP": {
      "command": "C:\\path\\to\\python.exe",
      "args": [
        "C:\\path\\to\\biovis-mcp\\server.py"
      ],
      "env": {
        "PYTHONPATH": "C:\\path\\to\\biovis-mcp"
      }
    }
  }
}

[!IMPORTANT]

• Replace C:\\path\\to\\python.exe with your actual Python executable path (find it using where python in CMD).
• Replace C:\\path\\to\\biovis-mcp with the absolute path to your project directory.
• Restart Claude Desktop after saving the configuration.

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📖 Available Tools

• generate_volcano_plot(data, title, fc_threshold, pval_threshold)
• generate_bar_enrichment(data, title, top_n, color)
• generate_heatmap_plot(data, title, cluster, cmap)
• generate_pca_plot(data, metadata, title, group_col)
• generate_bubble_enrichment(data, title, top_n)
• generate_ma_plot(data, title, pval_threshold)
• get_figure_caption(tool_type, stats)
• create_report(figures_with_captions, format, report_name)

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📁 Output Structure

• /figures: High-resolution PNG files.
• /reports: Formatted PDF and DOCX documents.

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Developed by ZaEyAsa — Your Advanced Agentic Bio-Visualization Assistant.

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