A powerful MCP server built with NitroStack
Add via Cursor Settings UI (Settings > Features > MCP > Add New MCP Server):
{
"mcpServers": {
// your other mcp servers
"arogya-appointment-arc": {
"url": "https://arogya-appointment-arc-6a-strikers-amrita-university-coimbatore.app.nitrocloud.ai/mcp"
}
}
}
Connect remote tools directly via Claude's Web UI:
Configure custom tools directly via ChatGPT's Web UI:
Add the following configuration block under mcpServers in your Antigravity configuration file (~/.gemini/config/mcp_config.json):
{
"mcpServers": {
// your other mcp servers
"arogya-appointment-arc": {
"serverUrl": "https://arogya-appointment-arc-6a-strikers-amrita-university-coimbatore.app.nitrocloud.ai/mcp"
}
}
}
Add the following configuration block to your Codex configuration file (~/.codex/config.toml):
[mcp_servers.arogya-appointment-arc] url = "https://arogya-appointment-arc-6a-strikers-amrita-university-coimbatore.app.nitrocloud.ai/mcp"
Connect directly using the Server-Sent Events endpoint:
https://arogya-appointment-arc-6a-strikers-amrita-university-coimbatore.app.nitrocloud.ai/mcp
Find doctors in the Arogya provider directory by specialty and city. Returns doctor cards with photo, hospital, qualifications, consultation fee, rating and live slot availability. Use the returned `doctorId` values for compare-slots and book-appointment.
Compare the open consultation slots of two or more doctors on a specific date, side by side. Returns one column per doctor with every available slot (start time, end time, mode, fee) plus earliest/latest availability. Use the returned `slotId` to book.
Generate a comprehensive summary for a specific doctor, including experience, languages, specialty, hospital, and recommendations.
Book a consultation slot for a patient. Supply the doctorId, date, and slot time/id. Patient name and phone should be collected if possible, but are optional.
Cancel an existing appointment and release the slot back into inventory.
Reschedule an appointment by swapping it to a new slot while preserving the bookingId.
Retrieve a booked appointment by bookingId and render the confirmation card.
Assess patient symptoms, estimate urgency, classify risk severity, and recommend the correct medical specialty. Covers 17+ specialties. NEVER diagnoses diseases — only triages.
Trigger IMMEDIATELY for emergency phrases: "chest pain", "heart attack", "stroke", "can't breathe", "seizure", "unconscious", "heavy bleeding". Activates emergency protocol and directs the patient to emergency services.
Check availability of hospital beds (ICU, General, Emergency, Private, Semi-private). Supports fuzzy hospital name matching and city-level search. Returns available, occupied, reserved, and maintenance counts with a human-readable summary.
Search the pharmacy inventory for a medicine by name. Returns availability, stock level, dosage forms, and generic alternatives. Optionally checks for known class-level drug interactions.
Find available lab tests and prices from the hospital laboratory catalog. Supports partial name matching. Returns test name, category, price, turnaround time, and preparation instructions.
Check the status of a patient's lab report by test ID. Returns current status (Pending / Processing / Ready), expected delivery time, and notes.
Parses complex natural-language hospital commands and produces a structured execution plan, delegating to specialist domains (Appointments, Beds, Emergency, Pharmacy). Returns a step-by-step decision path.
Model hypothetical hospital surge scenarios using real bed data. Returns quantitative predictions: time-to-capacity, ICU overflow hour, queue growth rate, and mitigation recommendations.
Generate a live executive briefing for hospital operations using real-time data from the MongoDB database. Returns appointment volume, bed utilization, top specialties, pharmacy alerts, and actionable recommendations.
Coordinates emergency response for single or mass casualty incidents. Routes to the correct department, generates a structured incident record with a persistent incidentId, and provides a step-by-step response timeline.