Rehabilitation Monitoring MCP Server

An MCP (Model Context Protocol) server for rehabilitation monitoring built with the Python SDK. The server exposes rehabilitation datasets, monitoring tools, reporting workflows, and research retrieval capabilities through a standardized MCP interface.

Development Approach

This project was developed using an LLM-assisted development workflow inspired by the MCP tutorial on building MCP servers with LLMs. Functionality was designed, implemented, tested, and refined iteratively through prompt-driven development, MCP tool testing, and human review.

The project evolved from basic rehabilitation-monitoring tools into more advanced workflows, including risk assessment, decline detection, intervention planning, alert generation, and an agentic rehabilitation workflow for reviewing and updating patient plans.

Reference:

• https://modelcontextprotocol.info/docs/tutorials/building-mcp-with-llms/

Related MCP server: openemr-mcp

What it provides

Tools

• get_patient_information

• calculate_patient_risk_scores

• identify_declining_rehabilitation_outcomes

• generate_rehabilitation_reports

• create_patient_alerts

• create_intervention_plan

• review_and_update_patient_plan

• search_rehabilitation_research

Prompts

• generate_patient_progress_summaries

• create_rehabilitation_monitoring_reports

• explain_risk_classifications

• recommend_follow_up_actions

Resources

• rehab://data/patients.csv

• rehab://data/therapy_sessions.csv

• rehab://data/wearable_measurements.csv

• rehab://data/medication_adherence.csv

• rehab://alerts

Data directory

By default the server reads CSV files from ./data. You can override that with REHAB_DATA_DIR.

Expected filenames:

• patients.csv

• therapy_sessions.csv

• wearable_measurements.csv

• medication_adherence.csv

Firecrawl research search

The research search tool uses the Firecrawl API. Set:

• FIRECRAWL_API_KEY

• optionally FIRECRAWL_API_URL if you use a different endpoint

The tool uses Firecrawl to retrieve rehabilitation-related research papers and summaries from external sources.

Example MCP Usage

Examples:

• Calculate patient risk scores

• Generate rehabilitation reports

• Identify declining rehabilitation outcomes

• Create patient alerts

• Retrieve rehabilitation-related research

Example prompts:

• Use the rehab-monitor MCP server to calculate patient risk scores.

• Use the rehab-monitor MCP server to generate a rehabilitation report for patient P001.

• Use the rehab-monitor MCP server to search rehabilitation research related to stroke recovery.

Sample Data

The repository includes synthetic rehabilitation monitoring datasets containing:

• patient records

• therapy session data

• wearable sensor measurements

• medication adherence records

These datasets are intended for MCP development and testing purposes only and do not contain real patient information.

Run

uv run rehab-monitor

Or connect the script path directly from an MCP host.