HomeCare Cohort MCP Server

HomeCare Cohort MCP (Step 1)

FastMCP server that powers the TopGun HomeCare demo Step 1 agents. It exposes tools to surface the high‑risk cohort and produce the Step 1b care gap closure plan from the synthetic OMOP-like dataset.

Prerequisites

• macOS / Linux shell
• Conda (recommended) or Python 3.11
• Repo cloned at /Users/mdnasir/Documents/proj/TopGun/code/homecare-cohort-mcp

Environment Setup

conda create -n homecare-mcp python=3.11 -y
conda activate homecare-mcp
pip install -r requirements.txt

Build DuckDB Dataset

The synthetic CSVs live in ../synthetic_data. Rebuild the DuckDB file whenever the CSVs change:

cd /Users/mdnasir/Documents/proj/TopGun/code/homecare-cohort-mcp
python -c "from db import ensure_database; ensure_database(force_rebuild=True)"

This creates/overwrites data/homecare.duckdb and materializes helper views (latest_sbp, latest_eye_exam, etc.).

Run the MCP Server Locally

cd /Users/mdnasir/Documents/proj/TopGun/code/homecare-cohort-mcp
uvicorn server:app --reload --port 8010

The Streamable HTTP transport is available at http://127.0.0.1:8010/mcp.

Example Tool Calls

Using the MCP CLI (from the same conda env):

# Identify Step 1a cohort
mcp run server.py:mcp --call get_highrisk_cohort --data '{"limit": 6}'

# Build Step 1b care gap plan
mcp run server.py:mcp \
  --call care_gap_closure_plan \
  --data '{"patient_ids": ["PAT-00042", "PAT-00058"]}'

Or use MCP Inspector (mcp dev server.py:mcp) to interactively inspect Markdown and structured JSON.

Smoke Test

python smoke_test.py

(Ensures both Step 1 tools execute and return non-empty results.)

Deployment Notes

• Optional build step (if rebuilding DB on deploy):

  python -c "from db import ensure_database; ensure_database()"
  

• Configure MCP_ALLOWED_HOSTS / MCP_ALLOWED_ORIGINS and future API keys (CMS, HDI, Medical Research).

Repository Structure

homecare-cohort-mcp/
├── api/index.py          # Vercel entrypoint
├── data/homecare.duckdb  # Generated DuckDB file (ignored by default)
├── db.py                 # DuckDB loader + helper views
├── requirements.txt
├── server.py             # FastMCP server with Step 1 tools
├── smoke_test.py         # Regression script
└── vercel.json