MCP HuliHealth
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP HuliHealthList all patients with appointments today"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP HuliHealth
A production-ready Model Context Protocol (MCP) server for HuliHealth. This CLI allows n8n or other automation tools to invoke HuliHealth APIs through a standard MCP interface.
🚀 Features
Modular tool-per-file architecture in
src/tools/OpenAPI-based schemas for type safety
STDIO or SSE modes for integration flexibility
Designed for n8n and LLM agents
Related MCP server: n8n-MCP
📂 Project Structure
src/ TypeScript source
openapi.json Reference Huli API specification
PROMT.md Architecture notes🛠️ Setup
Install dependencies
npm installConfigure environment variables Copy
.env.exampleto.envand set your credentials.
Running the CLI
Use npx to start the server. Without arguments it runs in STDIO mode. Add --sse or set PORT to start an HTTP SSE server.
npx hulihealth-mcp-dacs # STDIO mode
npx hulihealth-mcp-dacs --sse # SSE mode on port $PORT or 3000Generating new tools
Create new MCP tools with the mcp-gen-tool helper:
npm run mcp-gen-tool create-tool --name=<toolName>The command scaffolds src/tools/<toolName>.ts with a basic template. After
editing the file remember to register the tool in src/mcp/toolRegistry.ts.
n8n Integration
Example configuration to run the MCP from an n8n workflow:
{
"mcpServers": {
"hulihealth-mcp": {
"command": "npx",
"args": ["-y", "hulihealth-mcp-dacs"],
"env": {
"HULIHEALTH_API_KEY": "YOUR-API-KEY",
"HULI_ORG_ID": "YOUR-ORG-ID"
}
}
}
}🔑 Environment Variables
HULIHEALTH_API_KEY– your API key (required)HULI_ORG_ID– your organization ID (required)PORT– optional port for SSE mode
Created by dacsdev.
This server cannot be deployed
Maintenance
Related MCP Connectors
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MCP server that lets AI assistants use all OneSchema features exposed via the public API.
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