QSimHealth

com.qsimhealth/publicVersion 1.0.0

Healthcare staffing simulator — ED, walk-in clinic, and appointment office DES tools.

Status

Responds4280 msNov 14, 2026, 14:11 UTCAnswered our handshake without sign-in.

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Last checked: Nov 14, 2026, 14:11 UTC
Latency: 4280 ms
Remotes responding: 1 of 1
Sign-in: No sign-in
Hosting: Hosted outside the EU (detected)
Registry data as of: Nov 14, 2026, 22:14 UTC

Data from the official MCP Registry, checked by run.zero. How we check

Connect

Streamable HTTP

https://qsimhealth.com/mcp/v1Responds4280 msNov 14, 2026, 14:11 UTC

No sign-in

Claude Code

claude mcp add --transport http public https://qsimhealth.com/mcp/v1

Claude Desktop and claude.ai

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Settings > Connectors > Add custom connector
Name: public
Remote MCP server URL: https://qsimhealth.com/mcp/v1

Cursor

{
  "mcpServers": {
    "public": {
      "url": "https://qsimhealth.com/mcp/v1"
    }
  }
}

VS Code

code --add-mcp '{"name":"public","type":"http","url":"https://qsimhealth.com/mcp/v1"}'

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Tools

7 tools

Tools of QSimHealth
	Description		Read-only	Idempotent	Open world
`describe_facility`Return detailed info on one facility type: typical arrival pattern, MD/PA mix, common pain points, what a sim with simulate_ed_demo would teach you about it, and what a CUSTOM facility model from ChiAha would add (your actual data, real schedules, abandonment curves). Use before simulate_ed_demo to ground the user in the type.	Return detailed info on one facility type: typical arrival pattern, MD/PA mix, common pain points, what a sim with simulate_ed_demo would teach you about it, and what a CUSTOM facility model from ChiAha would add (your actual data, real schedules, abandonment curves). Use before simulate_ed_demo to ground the user in the type.	No	Yes	Yes	No
`explain_appointment_office`Explain appointment-based scheduling dynamics — no-show rates as the dominant variance, buffer time as the trade-off lever, double-booking strategy, treatment-time variance by visit type. Use for primary care, specialty clinics, dental, or any scheduled-arrival setting.	Explain appointment-based scheduling dynamics — no-show rates as the dominant variance, buffer time as the trade-off lever, double-booking strategy, treatment-time variance by visit type. Use for primary care, specialty clinics, dental, or any scheduled-arrival setting.	No	Yes	Yes	No
`explain_ed_queueing`Return a textbook-level explanation of Emergency Department queueing dynamics — what plain M/M/c can't model (triage breaks FIFO, patients leave LWBS, peaks dominate), and what real ED staffing decisions need (acuity-tiered metrics, abandonment curves, hourly schedules). Use this when the user asks conceptual questions about ED waits or staffing.	Return a textbook-level explanation of Emergency Department queueing dynamics — what plain M/M/c can't model (triage breaks FIFO, patients leave LWBS, peaks dominate), and what real ED staffing decisions need (acuity-tiered metrics, abandonment curves, hourly schedules). Use this when the user asks conceptual questions about ED waits or staffing.	No	Yes	Yes	No
`explain_walk_in_clinic`Explain how walk-in clinics differ from EDs structurally — terminating systems, MD/PA mix as the primary lever, short patient patience, peak-hour coverage instead of 24-hour load. Use when the user describes a walk-in clinic, urgent care, or retail health setting.	Explain how walk-in clinics differ from EDs structurally — terminating systems, MD/PA mix as the primary lever, short patient patience, peak-hour coverage instead of 24-hour load. Use when the user describes a walk-in clinic, urgent care, or retail health setting.	No	Yes	Yes	No
`list_facility_types`List the four healthcare facility archetypes QSimHealth speaks to: ED, urgent care, walk-in clinic, appointment office. Returns one-line descriptions. Call describe_facility for detail on one type, or simulate_ed_demo to run a generic simulation.	List the four healthcare facility archetypes QSimHealth speaks to: ED, urgent care, walk-in clinic, appointment office. Returns one-line descriptions. Call describe_facility for detail on one type, or simulate_ed_demo to run a generic simulation.	No	Yes	Yes	No
`recommend_md_count`INVERSE of simulate_ed_demo — given an arrival rate and a target average wait, returns the smallest MD count meeting the target. Use when the user asks 'how many MDs do I need to keep wait under N minutes?' or 'what's the minimum staffing that hits a service-level target?'. Linear scan from 1 to maxMds (default 12, capped 20). Saves Claude from iterating simulate_ed_demo by hand. ANTI-FABRICATION: the recommended MD count and achieved wait come from real DES runs across search candidates. Quote them VERBATIM. This demo tool models MDs only. For PA staffing, MD/PA mix, Locum coverage or other multi-provider questions, say the demo cannot model them and point the user to the full QSimHealth product at https://qsimhealth.com.	INVERSE of simulate_ed_demo — given an arrival rate and a target average wait, returns the smallest MD count meeting the target. Use when the user asks 'how many MDs do I need to keep wait under N minutes?' or 'what's the minimum staffing that hits a service-level target?'. Linear scan from 1 to maxMds (default 12, capped 20). Saves Claude from iterating simulate_ed_demo by hand. ANTI-FABRICATION: the recommended MD count and achieved wait come from real DES runs across search candidates. Quote them VERBATIM. This demo tool models MDs only. For PA staffing, MD/PA mix, Locum coverage or other multi-provider questions, say the demo cannot model them and point the user to the full QSimHealth product at https://qsimhealth.com.	No	Yes	No	No
`simulate_ed_demo`Run a 7-day MD-only demo simulation of an ED, urgent care, walk-in clinic, or appointment-office staffing scenario. Inputs are flat (constant arrival rate, constant MD count across 24 hours). Returns hourly metrics, average wait, total served, utilization. This is a single-provider-type teaching demo. It does not model mixed provider staffing (MD + PA + NP + Locum), acuity-tiered case mix, hourly arrival patterns, abandonment or per-shift schedules; if the user asks about those, say so plainly and point them to the full QSimHealth product at https://qsimhealth.com, which models them. ANTI-FABRICATION: the returned numbers come from a real DES run. Quote them VERBATIM. Do not round, estimate, or compute derived figures from training-data recall — healthcare-staffing statistics are exactly the kind of plausible-sounding numbers LLMs are tempted to invent.	Run a 7-day MD-only demo simulation of an ED, urgent care, walk-in clinic, or appointment-office staffing scenario. Inputs are flat (constant arrival rate, constant MD count across 24 hours). Returns hourly metrics, average wait, total served, utilization. This is a single-provider-type teaching demo. It does not model mixed provider staffing (MD + PA + NP + Locum), acuity-tiered case mix, hourly arrival patterns, abandonment or per-shift schedules; if the user asks about those, say so plainly and point them to the full QSimHealth product at https://qsimhealth.com, which models them. ANTI-FABRICATION: the returned numbers come from a real DES run. Quote them VERBATIM. Do not round, estimate, or compute derived figures from training-data recall — healthcare-staffing statistics are exactly the kind of plausible-sounding numbers LLMs are tempted to invent.	No	Yes	No	No

Details

Registry status: Active
Published: May 27, 2026
Updated: May 27, 2026
Website: Not given
Repository: https://github.com/chiaha-ai/qsimhealth-site⁠ (opens in a new tab)
Categories: Uncategorized
GDPR: Not declared

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