🏥 FHIR MCP Server

A FastMCP server that exposes healthcare data from the Public HAPI FHIR R4 Server using the Model Context Protocol (MCP).

This project demonstrates how AI applications can interact with standardized Electronic Health Record (EHR) data through FHIR resources.

Features

• Search patients by name

• Retrieve patient demographics

• Retrieve medical conditions

• Retrieve observations

• Retrieve medication requests

• Async communication using HTTPX

• Compatible with MCP Inspector

• Built using FastMCP

Related MCP server: Healthcare FHIR MCP Server

Technologies

• Python 3.11+

• FastMCP

• MCP

• HTTPX

• FHIR R4

• Public HAPI FHIR Server

Project Structure

fhir-mcp-server/
│
├── server.py
├── requirements.txt
├── README.md
├── LICENSE
├── .gitignore
│
├── screenshots/
│   ├── home.png
│   ├── search_patient.png
│   ├── get_patient.png
│   ├── get_conditions.png
│   ├── get_observations.png
│   ├── get_medications.png
│   └── architecture.png
│
└── docs/
    └── architecture.md

Installation

Clone the repository:

git clone https://github.com/baala-saravanan/fhir-mcp-server.git
cd fhir-mcp-server

Create a virtual environment:

python -m venv .venv

Activate the environment:

Windows:

.venv\Scripts\activate

Install dependencies:

pip install -r requirements.txt

Running the Project

Launch the MCP development server:

mcp dev server.py

The MCP Inspector will open automatically in your browser.

Available MCP Tools

Data Source

Public HAPI FHIR R4 Test Server

https://hapi.fhir.org/baseR4

This server provides synthetic healthcare data for development and testing.

Architecture

The application follows the Model Context Protocol (MCP) architecture.

See:

• docs/architecture.md

• screenshots/architecture.png

Screenshots

The project includes screenshots demonstrating the available MCP tools.

• Home

• Search Patient

• Get Patient

• Get Conditions

• Get Observations

• Get Medications

• Architecture Diagram

Future Improvements

• Patient Timeline

• Clinical Summary

• Laboratory Trend Analysis

• Medication Intelligence

• Clinical Decision Support

• AI-powered Patient Summaries

• Streamlit Dashboard

• FastAPI Backend

• LLM Integration

License

This project is licensed under the MIT License.

See the LICENSE file for details.

Author

Bala Saravanan Muthukumar

• Data Scientist

• Biomedical Engineer

• AI & Healthcare Enthusiast