Nitrostack Local
v1.0.0A powerful MCP server built with NitroStack
Add via Cursor Settings UI (Settings > Features > MCP > Add New MCP Server):
{
"mcpServers": {
// your other mcp servers
"nitrostack-local": {
"url": "https://docnet-6a6d9e25-bruteforce-srmist.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
"nitrostack-local": {
"serverUrl": "https://docnet-6a6d9e25-bruteforce-srmist.app.nitrocloud.ai/mcp"
}
}
}
Add the following configuration block to your Codex configuration file (~/.codex/config.toml):
[mcp_servers.nitrostack-local] url = "https://docnet-6a6d9e25-bruteforce-srmist.app.nitrocloud.ai/mcp"
Connect directly using the Server-Sent Events endpoint:
https://docnet-6a6d9e25-bruteforce-srmist.app.nitrocloud.ai/mcp
Perform basic arithmetic calculations
Convert temperature units based on file content or direct input. Supports Celsius (C) and Fahrenheit (F).
Matches the patient clinical summary to an available specialist. Validates specialty against a strict catalog to prevent hallucination. Returns doctor details and booking slot, or a self-correcting error message.
Routes the patient to the default General Practitioner queue. This is the fail-closed escape hatch when specialist matching fails or confidence is low. Bypasses all specialist logic and guarantees a GP booking.
Safely extracts and persists long-term patient data (age, allergies, medical history) to the patient profile. Patient ID is resolved from ExecutionContext (never from user input). Returns success message to LLM.
Retrieves long-term patient data (age, allergies, medical history) to hydrate the LLM with persistent context. Patient ID is resolved from ExecutionContext (never from user input). Returns structured JSON or graceful "no history" message if no profile exists.
Cross-references symptom clusters against official WHO/Mayo Clinic guidelines to prevent hallucinated specialty routing
Saves clinical dossier to Supabase backend health_episodes table with pgvector embeddings
Find available doctors and appointment slots matching a medical specialty from relational database
Finds past clinical episodes semantically similar to the current symptom cluster.
Searches public health and seasonal medical context for symptoms.
Queries Wikipedia REST API for clinical diagnostic guidelines and medical condition details.