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Healthcare Mcp Public
What is Healthcare Mcp Public
Healthcare-mcp-public is a Model Context Protocol (MCP) server designed to provide AI assistants with access to a variety of healthcare data tools, including FDA drug information, PubMed research, health topics, clinical trials, and medical terminology lookup.
Use cases
Use cases include AI-driven health assistants providing drug information, researchers accessing medical literature, healthcare professionals searching for clinical trials, and applications needing to look up medical terminology.
How to use
To use healthcare-mcp-public, you can install it via the Cline Marketplace or manually by cloning the repository, setting up a virtual environment, and installing the required dependencies. After installation, you can interact with the server through its API or command-line interface.
Key features
Key features include access to FDA drug information, PubMed research articles, evidence-based health topics, clinical trial searches, medical terminology lookups, efficient caching, anonymous usage tracking, robust error handling, multiple interfaces, interactive API documentation, and comprehensive testing.
Where to use
Healthcare-mcp-public can be used in various fields including healthcare, medical research, clinical trials, and any application requiring reliable medical information and data retrieval.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Healthcare Mcp Public
Healthcare-mcp-public is a Model Context Protocol (MCP) server designed to provide AI assistants with access to a variety of healthcare data tools, including FDA drug information, PubMed research, health topics, clinical trials, and medical terminology lookup.
Use cases
Use cases include AI-driven health assistants providing drug information, researchers accessing medical literature, healthcare professionals searching for clinical trials, and applications needing to look up medical terminology.
How to use
To use healthcare-mcp-public, you can install it via the Cline Marketplace or manually by cloning the repository, setting up a virtual environment, and installing the required dependencies. After installation, you can interact with the server through its API or command-line interface.
Key features
Key features include access to FDA drug information, PubMed research articles, evidence-based health topics, clinical trial searches, medical terminology lookups, efficient caching, anonymous usage tracking, robust error handling, multiple interfaces, interactive API documentation, and comprehensive testing.
Where to use
Healthcare-mcp-public can be used in various fields including healthcare, medical research, clinical trials, and any application requiring reliable medical information and data retrieval.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
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 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.
Features
- FDA Drug Information: Search and retrieve comprehensive drug information from the FDA database
- PubMed Research: Search medical literature from PubMed’s database of scientific articles
- Health Topics: Access evidence-based health information from Health.gov
- Clinical Trials: Search for ongoing and completed clinical trials
- Medical Terminology: Look up ICD-10 codes and medical terminology definitions
- 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 pytest and coverage reporting
Installation
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
Manual Installation
-
Clone the repository:
git clone https://github.com/Cicatriiz/healthcare-mcp-public.git cd healthcare-mcp-public -
Create a virtual environment:
python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate -
Install dependencies:
pip install -r requirements.txt -
Set up environment variables (optional):
# Create .env file from example cp .env.example .env # Edit .env with your API keys (optional) -
Run the server:
python run.py
Usage
Running in Different Transport Modes
-
stdio mode (default, for Cline):
python run.py -
HTTP/SSE mode (for web clients):
python run.py --http --port 8000
Testing the Tools
You can test the MCP tools using the new pytest-based test suite:
# Run all tests with pytest and coverage
python -m tests.run_tests --pytest
# Run a specific test file
python -m tests.run_tests --test test_fda_tool.py
# Test the HTTP server
python -m tests.run_tests --server --port 8000
For backward compatibility, you can still run the old tests:
# Run all tests (old style)
python -m tests.run_tests
# Test individual tools (old style)
python -m tests.run_tests --fda # Test FDA drug lookup
python -m tests.run_tests --pubmed # Test PubMed search
python -m tests.run_tests --health # Test Health Topics
python -m tests.run_tests --trials # Test Clinical Trials search
python -m tests.run_tests --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 forsearch_type: Type of information to retrievegeneral: Basic drug information (default)label: Drug labeling informationadverse_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"
}
]
}
]
}
PubMed Search
GET /api/pubmed?query={query}&max_results={max_results}&date_range={date_range}
Parameters:
query: Search query for medical literaturemax_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 informationlanguage: 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..."
]
}
]
}
Clinical Trials Search
GET /api/clinical_trials?condition={condition}&status={status}&max_results={max_results}
Parameters:
condition: Medical condition or disease to search forstatus: 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"
}
Programmatic API
When using the MCP server programmatically, the following functions are available:
FDA Drug Lookup
fda_drug_lookup(drug_name: str, search_type: str = "general")
Parameters:
drug_name: Name of the drug to search forsearch_type: Type of information to retrievegeneral: Basic drug information (default)label: Drug labeling informationadverse_events: Reported adverse events
PubMed Search
pubmed_search(query: str, max_results: int = 5, date_range: str = "")
Parameters:
query: Search query for medical literaturemax_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: str, language: str = "en")
Parameters:
topic: Health topic to search for informationlanguage: Language for content (en or es, default: en)
Clinical Trials Search
clinical_trials_search(condition: str, status: str = "recruiting", max_results: int = 10)
Parameters:
condition: Medical condition or disease to search forstatus: 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: str = None, description: str = None, max_results: int = 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
Data Sources
This MCP server utilizes several publicly available healthcare APIs:
- FDA OpenFDA API
- PubMed E-utilities API
- Health.gov API
- ClinicalTrials.gov API
- NLM Clinical Table Search Service for ICD-10-CM
Premium Version (still being built)
This is the free version of Healthcare MCP Server with usage limits. For advanced features and higher usage limits, check out our premium version:
- Unlimited API calls
- Advanced healthcare data tools
- Custom integrations
- Priority support
License
MIT License
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.










