by Cicatriiz
A Model Context Protocol (MCP) server providing AI assistants with access to healthcare data and medical information tools, including FDA drug info, PubMed, medRxiv, NCBI Bookshelf, clinical trials, ICD-10, DICOM metadata, and a medical calculator.
# Add to your Claude Code skills
git clone https://github.com/Cicatriiz/healthcare-mcp-publicGuides for using ai agents skills like healthcare-mcp-public.
Last scanned: 5/30/2026
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}healthcare-mcp-public is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by Cicatriiz. A Model Context Protocol (MCP) server providing AI assistants with access to healthcare data and medical information tools, including FDA drug info, PubMed, medRxiv, NCBI Bookshelf, clinical trials, ICD-10, DICOM metadata, and a medical calculator. It has 124 GitHub stars.
healthcare-mcp-public returned warnings in SkillsLLM's automated security scan. It has no critical vulnerabilities, but review the flagged issues in the Security Report section before adding it to your workflow.
Clone the repository with "git clone https://github.com/Cicatriiz/healthcare-mcp-public" and add it to your Claude Code skills directory (see the Installation section above).
healthcare-mcp-public is primarily written in JavaScript. It is open-source under Cicatriiz on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh healthcare-mcp-public against similar tools.
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Requires a passing catalog security scan. Resolve the flagged issues and resubmit to enable featuring.
A Model Context Protocol (MCP) server providing AI assistants with access to healthcare data and medical information tools.
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.
This repository includes a packaged DXT (Desktop Extension) file for easy installation in compatible development environments. Download healthcare-mcp.dxt for one-click installation.
healthcare-mcp.dxt from this repositoryTo install Healthcare Data and Medical Information Server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @Cicatriiz/healthcare-mcp-public --client claude
Install the package:
npm install healthcare-mcp
Run the server:
npx healthcare-mcp
Clone the repository:
git clone https://github.com/Cicatriiz/healthcare-mcp-public.git
cd healthcare-mcp-public/server
Install dependencies:
npm install
Set up environment variables (optional):
# Create .env file from example
cp .env.example .env
# Edit .env with your API keys (optional)
Run the server:
npm start
stdio mode (default, for MCP clients):
npm start
HTTP/SSE mode (for web clients):
npm run server:http
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
The Healthcare MCP Server provides both a programmatic API for direct integration and a RESTful HTTP API for web clients.
When running in HTTP mode, the following endpoints are available:
GET /health
Returns the status of the server and its services.
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 retrieve
general: Basic drug information (default)label: Drug labeling informationadverse_events: Reported adverse eventsExample 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 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/"
}
]
}
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..."]
}
]
}
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"
}
}
]
}
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"
}
]
}
POST /mcp/call-tool
Request Body:
{
"name": "fda_drug_lookup",
"arguments": {
"drug_name": "aspirin",
"search_type": "general"
},
"session_id": "optional-session-id"
}
When using the MCP server through compatible clients, the following tools are available:
fda_drug_lookup(drug_name, search_type = "general")
Parameters:
drug_name: Name of the drug to search forsearch_type: Type of information to retrieve
general: Basic drug information (default)label: Drug labeling informationadverse_events: Reported adverse eventspubmed_search(query, max_results = 5, date_range = "")
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(topic, language = "en")
Parameters:
topic: Health topic to search for informationlanguage: Language for content (en or es, default: en)clinical_trials_search(condition, status = "recru