Precision Medicine MCP Platform

Dedicated to PatientOne -- a dear friend who passed from High-Grade Serous Ovarian Carcinoma in 2025.

This platform automates multi-modal data processing for clinical decision support — all results require clinician review before any clinical action.

The Problem

Standard oncology workup (BRCA1/2, HRD panel, tumor genomic panel) generates no immunotherapy or investigational hypotheses. For preventive health, standard lipid panels and population genetic screens miss key risk factors. Manual multi-modal analysis across genomics, spatial transcriptomics, and clinical data is clinically impractical -- the platform automates it.

The Platform

A multi-server MCP architecture orchestrated by AI (Claude + Gemini) executes a 5-stage pipeline:

flowchart LR
    A["1 Data<br/>Acquisition"] --> B["2 Spatial<br/>Deconvolution"]
    B --> C["3 Target<br/>Profiling"]
    C --> D["4 Causal<br/>Inference"]
    D --> E["5 Report"]

    subgraph servers [" "]
        direction TB
        S1["EHR · GEO · TCGA"]
        S2["Spatial · DeepCell · CIBERSORTx"]
        S3["OpenTargets · Neoantigen"]
        S4["Perturbation · Quantum"]
        S5["Patient Report"]
    end

    A --- S1
    B --- S2
    C --- S3
    D --- S4
    E --- S5

    AI(["AI Orchestrator<br/>Claude + Gemini"]) -.-> A
    AI -.-> B
    AI -.-> C
    AI -.-> D
    AI -.-> E

Architecture at a glance

                  +--------------------------------------+
                  |           CLIENT LAYER               |
                  |  Claude Desktop / Hospital EHR       |
                  |  Adapter / Research Notebook         |
                  +----------------+-----------------+
                                   |
                         MCP (FastMCP >= 2.13)
                                   |
   +---------------------------------------------------------------+
   |                                                               |
   |  DATA ACQUISITION      ANALYSIS & INFERENCE      REPORTING   |
   |                                                               |
   |  mockepic              spatialtools              patient-     |
   |  epic                  multiomics                report       |
   |  geodownload           perturbation                           |
   |  mocktcga              quantum-fidelity                       |
   |  genomic-results       opentargets                            |
   |  fgbio                 neoantigen                             |
   |                        cibersortx                             |
   |                        openimagedata                          |
   |                        deepcell                               |
   |                        cell-classify                          |
   |                        cardiometabolic                        |
   +---------------------------------------------------------------+

All tools accessible via natural language. Every AI result requires clinician APPROVE/REVISE/REJECT. HIPAA-compliant. Current server and tool counts: Server Registry.

The Results

The platform surfaces clinically actionable findings that standard workup cannot reach — 6 investigational hypotheses across 2 cancer types plus 3 preventive health evidence gaps, validated across three independent use cases:

| Use Case | Patient | Key Finding Missed by Stand

... View full README on GitHub