Precision Medicine MCP Platform

An estimated 40 hours of manual bioinformatics → 2-5 hours with AI-orchestrated MCP tools (8-20x faster)

15 specialized MCP servers | 80 analysis tools | Multi-provider AI (Claude or Gemini) | Stage IV Ovarian Cancer demo

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💰 For Decision-Makers

• Executive Summary of Precision Medicine MCP
• Why MCP for Healthcare?
• <5 minute demo video - shows a subset of available functionality

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🚀 Quick Start by Role

You Are...	Start Here
🏥 Hospital IT/Admin	Hospital Deployment
🔬 Bioinformatician	Researcher Guide
💻 MCP Developer	Developer Guide
🎓 Educator/Student	Educational Guide
👥 Patient/Family	Patient Resources
💰 Funder/Grant Reviewer	FUNDING.md

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System Overview

graph LR
    subgraph Users["👥 Users"]
        U[Clinicians<br/>Bioinformaticians<br/>Researchers]
    end

    subgraph AI["🤖 AI Orchestration"]
        CLAUDE[Claude<br/>Native MCP]
        GEMINI[Gemini<br/>SSE-based MCP]
        CUSTOM[Custom<br/>Custom Orchestration MCP]
    end

    subgraph ServerTypes["🔧 MCP ServerTypes"]
        S1[Clinical<br/>FHIR]
        S2[Genomics<br/>VCF/FASTQ]
        S3[Multi-omics<br/>RNA/Protein/Phospho]
        S4[Spatial<br/>Visium]
        S5[Imaging<br/> H&E/MxIF]
        S6[Perturbation<br/>GEARS/GNN + scRNA-seq]
        S7[Quantum<br/>Qiskit + spatial transcriptomics]
        S8[Patient Reports<br/>PDF Generation]
        S9[Genomic Results<br/>Somatic/CNV/HRD]
    end

    subgraph Output["📊 Orchestrated Outputs"]
        O[Treatment Targets<br/>Predictions<br/>Visualizations<br/>Patient Reports]
    end

    U --> CLAUDE
    U --> GEMINI
    U --> CUSTOM
    CLAUDE --> ServerTypes
    GEMINI --> ServerTypes
    CUSTOM --> ServerTypes
    S1 --> Output
    S2 --> Output
    S3 --> Output
    S4 --> Output
    S5 --> Output
    S6 --> Output
    S7 --> Output
    S8 --> Output
    S9 --> Output

    style Users fill:#e1f5ff
    style AI fill:#fff3cd
    style ServerTypes fill:#d4edda
    style Output fill:#d1ecf1

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Featured Use Case: PatientOne

Stage IV High-Grade Serous Ovarian Cancer - Platinum-resistant, 70% 5-year mortality

What This Demonstrates:

• Clinical data (Epic FHIR) + Genomics (VCF) + Multi-omics (RNA/Protein/Phospho)
• Spatial transcriptomics (10x Visium) + Imaging (H&E, MxIF)
• Natural language queries → AI orchestration → 35-minute analysis (DRY_RUN data)

Learn More

• 📖 Full Case Study: PatientOne Documentation
• 📚 Prompt Library
• 🏗️ Architecture Details
• 📚 Documentation Hub

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