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Healthcare MCP Server

Healthcare MCP Server

A Model Context Protocol (MCP) server providing AI assistants with access to healthcare data and medical information tools.

Overview

Healthcare MCP Server is a specialized Node.js server that implements the Model Context Protocol (MCP) to provide AI assistants with access to healthcare data and medical information tools. It enables AI models to retrieve accurate, up-to-date medical information from authoritative sources. This repository provides a single DXT package containing the complete Node.js implementation.

DXT Extension

This repository includes a packaged DXT (Desktop Extension) file for easy installation in compatible development environments. Download healthcare-mcp.dxt for one-click installation.

Features

  • FDA Drug Information: Search and retrieve comprehensive drug information from the FDA database (improved response parsing)
  • PubMed Research: Search medical literature from PubMed's database of scientific articles
  • Health Topics: Access evidence-based health information from Health.gov (updated to API v4)
  • Clinical Trials: Search for ongoing and completed clinical trials (updated API parameters)
  • Medical Terminology: Look up ICD-10 codes and medical terminology definitions
  • medRxiv Search: Search for pre-print articles on medRxiv
  • Medical Calculator: Calculate Body Mass Index (BMI)
  • NCBI Bookshelf Search: Search the NCBI Bookshelf for biomedical books and documents
  • DICOM Metadata Extraction: Extract metadata from a DICOM file
  • Caching: Efficient caching system with connection pooling to reduce API calls and improve performance
  • Usage Tracking: Anonymous usage tracking to monitor API usage
  • Error Handling: Robust error handling and logging
  • Multiple Interfaces: Support for both stdio (for CLI) and HTTP/SSE interfaces
  • API Documentation: Interactive API documentation with Swagger UI
  • Comprehensive Testing: Extensive test suite with Node.js testing and API verification

Installation

  1. Download healthcare-mcp.dxt from this repository
  2. Open with your compatible MCP client (such as Claude Desktop)
  3. Follow the installation prompts
  4. Configure optional settings through the GUI

Option 2: Installing via Smithery

To install Healthcare Data and Medical Information Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @Cicatriiz/healthcare-mcp-public --client claude

Option 3: npm Installation

  1. Install the package:
    npm install healthcare-mcp
  2. Run the server:
    npx healthcare-mcp

Option 4: Manual Installation from Source

  1. Clone the repository:
    git clone https://github.com/Cicatriiz/healthcare-mcp-public.git cd healthcare-mcp-public/server
  2. Install dependencies:
    npm install
  3. Set up environment variables (optional):
    # Create .env file from example cp .env.example .env # Edit .env with your API keys (optional)
  4. Run the server:
    npm start

Usage

Running the Server

  • stdio mode (default, for MCP clients):
    npm start
  • HTTP/SSE mode (for web clients):
    npm run server:http

Testing the Tools

You can test the MCP tools using the built-in test scripts:

# Test all tools npm test # Test individual tools npm run test:fda # Test FDA drug lookup npm run test:pubmed # Test PubMed search npm run test:health # Test Health Topics npm run test:trials # Test Clinical Trials search npm run test:icd # Test ICD-10 code lookup

API Reference

The Healthcare MCP Server provides both a programmatic API for direct integration and a RESTful HTTP API for web clients.

RESTful API Endpoints

When running in HTTP mode, the following endpoints are available:

Health Check
GET /health

Returns the status of the server and its services.

FDA Drug Lookup
GET /api/fda?drug_name={drug_name}&search_type={search_type}

Parameters:

  • drug_name: Name of the drug to search for
  • search_type: Type of information to retrieve
    • general: Basic drug information (default)
    • label: Drug labeling information
    • adverse_events: Reported adverse events

Example Response:

{ "status": "success", "drug_name": "aspirin", "search_type": "general", "total_results": 25, "results": [ { "brand_name": "ASPIRIN", "generic_name": "ASPIRIN", "manufacturer": "Bayer Healthcare", "product_type": "HUMAN OTC DRUG", "route": "ORAL", "active_ingredients": [ { "name": "ASPIRIN", "strength": "325 mg/1" } ] } ] }
GET /api/pubmed?query={query}&max_results={max_results}&date_range={date_range}

Parameters:

  • query: Search query for medical literature
  • max_results: Maximum number of results to return (default: 5, max: 50)
  • date_range: Limit to articles published within years (e.g. '5' for last 5 years)

Example Response:

{ "status": "success", "query": "diabetes treatment", "total_results": 123456, "date_range": "5", "articles": [ { "pmid": "12345678", "title": "New advances in diabetes treatment", "authors": ["Smith J", "Johnson A"], "journal": "Journal of Diabetes Research", "publication_date": "2023-01-15", "abstract": "This study explores new treatment options...", "url": "https://pubmed.ncbi.nlm.nih.gov/12345678/" } ] }
Health Topics
GET /api/health_finder?topic={topic}&language={language}

Parameters:

  • topic: Health topic to search for information
  • language: Language for content (en or es, default: en)

Example Response:

{ "status": "success", "search_term": "diabetes", "language": "en", "total_results": 15, "topics": [ { "title": "Diabetes Type 2", "url": "https://health.gov/myhealthfinder/topics/health-conditions/diabetes/diabetes-type-2", "last_updated": "2023-05-20", "section": "Health Conditions", "description": "Information about managing type 2 diabetes", "content": ["Diabetes is a disease...", "Treatment options include..."] } ] }
GET /api/clinical_trials?condition={condition}&status={status}&max_results={max_results}

Parameters:

  • condition: Medical condition or disease to search for
  • status: Trial status (recruiting, completed, active, not_recruiting, or all)
  • max_results: Maximum number of results to return (default: 10, max: 100)

Example Response:

{ "status": "success", "condition": "breast cancer", "search_status": "recruiting", "total_results": 256, "trials": [ { "nct_id": "NCT12345678", "title": "Study of New Treatment for Breast Cancer", "status": "Recruiting", "phase": "Phase 2", "study_type": "Interventional", "conditions": ["Breast Cancer", "HER2-positive Breast Cancer"], "locations": [ { "facility": "Memorial Hospital", "city": "New York", "state": "NY", "country": "United States" } ], "sponsor": "National Cancer Institute", "url": "https://clinicaltrials.gov/study/NCT12345678", "eligibility": { "gender": "Female", "min_age": "18 Years", "max_age": "75 Years", "healthy_volunteers": "No" } } ] }
ICD-10 Code Lookup
GET /api/medical_terminology?code={code}&description={description}&max_results={max_results}

Parameters:

  • code: ICD-10 code to look up (optional if description is provided)
  • description: Medical condition description to search for (optional if code is provided)
  • max_results: Maximum number of results to return (default: 10, max: 50)

Example Response:

{ "status": "success", "search_type": "description", "search_term": "diabetes", "total_results": 25, "codes": [ { "code": "E11", "description": "Type 2 diabetes mellitus", "category": "Endocrine, nutritional and metabolic diseases" }, { "code": "E10", "description": "Type 1 diabetes mellitus", "category": "Endocrine, nutritional and metabolic diseases" } ] }
Generic Tool Execution
POST /mcp/call-tool

Request Body:

{ "name": "fda_drug_lookup", "arguments": { "drug_name": "aspirin", "search_type": "general" }, "session_id": "optional-session-id" }

MCP Tools

When using the MCP server through compatible clients, the following tools are available:

FDA Drug Lookup
fda_drug_lookup(drug_name, search_type = "general")

Parameters:

  • drug_name: Name of the drug to search for
  • search_type: Type of information to retrieve
    • general: Basic drug information (default)
    • label: Drug labeling information
    • adverse_events: Reported adverse events
pubmed_search(query, max_results = 5, date_range = "")

Parameters:

  • query: Search query for medical literature
  • max_results: Maximum number of results to return (default: 5)
  • date_range: Limit to articles published within years (e.g. '5' for last 5 years)
Health Topics
health_topics(topic, language = "en")

Parameters:

  • topic: Health topic to search for information
  • language: Language for content (en or es, default: en)
clinical_trials_search(condition, status = "recruiting", max_results = 10)

Parameters:

  • condition: Medical condition or disease to search for
  • status: Trial status (recruiting, completed, active, not_recruiting, or all)
  • max_results: Maximum number of results to return
ICD-10 Code Lookup
lookup_icd_code(code = null, description = null, max_results = 10)

Parameters:

  • code: ICD-10 code to look up (optional if description is provided)
  • description: Medical condition description to search for (optional if code is provided)
  • max_results: Maximum number of results to return
medrxiv_search(query, max_results = 10)

Parameters:

  • query: Search query for medRxiv articles
  • max_results: Maximum number of results to return
Calculate BMI
calculate_bmi(height_meters, weight_kg)

Parameters:

  • height_meters: Height in meters
  • weight_kg: Weight in kilograms
ncbi_bookshelf_search(query, max_results = 10)

Parameters:

  • query: Search query for NCBI Bookshelf
  • max_results: Maximum number of results to return
Extract DICOM Metadata
extract_dicom_metadata(file_path)

Parameters:

  • file_path: Path to the DICOM file

Data Sources

This MCP server utilizes several publicly available healthcare APIs:

License

MIT License

Install Server
A
security – no known vulnerabilities
A
license - permissive license
A
quality - confirmed to work

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

A Model Context Protocol server providing AI assistants with access to healthcare data tools, including FDA drug information, PubMed research, health topics, clinical trials, and medical terminology lookup.

  1. Overview
    1. Features
      1. Installation
        1. Installing via Smithery
        2. Manual Installation
      2. Usage
        1. Running in Different Transport Modes
        2. Testing the Tools
      3. API Reference
        1. RESTful API Endpoints
        2. Programmatic API
      4. Data Sources
        1. Premium Version (still being built)
          1. License

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