🧬 Spatial MCP Demonstration POC

AI-Orchestrated Spatial Transcriptomics Bioinformatics Pipeline

🤖 MCP Host: Claude Desktop

AI-driven orchestration • Workflow coordination • Context management • Result interpretation

1

Data Ingestion

FASTQ files, spatial barcodes, quality control

2

Segmentation

Spatial regions, histology integration

3

Alignment

Reference genome mapping, BAM generation

4

Quantification

UMI counting, expression matrix

5

Analysis

Cell typing, pathways, clinical integration

🔧 MCP Server Architecture (7 Specialized Servers)

🧬

mcp-FGbio

Genomic Reference Data
FGbio toolkit • FASTQ validation • UMI extraction • Reference genomes

🎗️

mcp-mocktcga

TCGA Cancer Genomics
GDC Portal • Expression data • Mutation profiles • Clinical annotations

⚙️

mcp-spatialtools

Core Processing
STAR alignment • QC filtering • Spatial mapping • UMI counting

🖼️

mcp-openImageData

Histology Integration
H&E images • Image registration • Feature extraction • Visualization

🤗

mcp-huggingFace

ML Foundation Models
DNABERT-2 • Geneformer • scGPT • Sequence embeddings

🔬

mcp-deepcell

Cell Segmentation
Deep learning models • Nuclear detection • Cell phenotyping

🏥

mcp-mockEpic

Mock EHR System
Synthetic patient data • Clinical metadata • FHIR-compliant

Data Acquisition
Processing
ML & AI
Clinical & Workflows

🎯 Modular Design

Single-responsibility servers with clear interfaces. Easy to extend, test, and maintain.

🔒 Security First

4-layer security model. HIPAA-like patterns for clinical data. Input validation throughout.

🚀 Production Ready

Containerized deployment. Horizontal scaling. Monitoring and observability built-in.

🧠 AI-Orchestrated

Claude coordinates workflow execution, interprets results, and provides biological insights.

📊 Enterprise Tools

FGbio, TCGA, Hugging Face integration with industry-standard tools.

⚡ High Performance

50M reads in <30 min. GPU acceleration. Distributed processing with Nextflow.