com.queuesim/public

up checked 2026-11-11T04:39:02.758Z

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Publisher-provided title

QueueSim

Publisher-provided description

Queueing simulation: M/M/c, staffing, Erlang C checks, and multi-step models built from nodes.

Summary by lookupd

Runs queueing simulations and Erlang-C checks, plus staffing recommendations and explainers, for modeling wait times and server counts.

Install

Claude Code, remote (streamable-http)

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

Codex, remote (streamable-http)

codex mcp add public --url https://queuesim.com/mcp/v1

Cursor, remote (streamable-http) → .cursor/mcp.json

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

Other clients: docs. Or tell your agent: Set up lookupd for me: read https://lookupd.com/agent.md and follow it.

Tools (14 tools)

Publisher-provided text

• simulate_mmc Run a generic M/M/c queue simulation. Provide an arrival rate (λ, arrivals/hour), a service rate per server (μ, customers/hour each server can finish), and a se
• list_scenarios List the four pre-built QueueSim scenarios. Returns key, title, and one-line description for each (Single Server, Coffee Shop, Grocery Checkout, Call Center). C
• describe_scenario Return full details for one preset scenario: title, description, teaching note, peak parameters, and per-hour arrival + staffing arrays. Use this before simulat
• simulate_scenario Run one of the four preset scenarios (single, coffee, grocery, callcenter) with optional overrides. Overrides apply UNIFORMLY across open hours — e.g. setting s
• simulate_schedule Run a queueing simulation against an arbitrary 24-hour staffing schedule. Take this when the user describes a custom day shape that doesn't match a preset (e.g.
• compare_separate_vs_pooled Run the classic operations-research teaching demo: pooled queueing (one shared queue, c servers) vs separate queues (c independent queues, one server each, λ/c
• explain_queueing_theory Return a ~500-word educational explainer of M/M/c queueing theory: Little's Law, utilization, why averages mislead, how simulation relates to Erlang-C. No input
• explain_advanced_patterns Return a textbook-level description of six queueing complexity patterns beyond basic M/M/c: abandonment/reneging, priority tiers, overflow routing, skills-based
• recommend_staffing INVERSE of simulate_mmc — given an arrival rate, service rate, and a target average wait time, returns the SMALLEST number of servers needed to meet the target.
• interpret_result Given an M/M/c configuration (arrivalRate, serviceRate, servers) and optionally an observed average wait, returns a queueing-theory framed interpretation: where
• compare_analytical_vs_simulated Run the same M/M/c configuration through BOTH the closed-form Erlang-C formula AND the discrete-event simulator, returning a side-by-side comparison with deltas
• queue_model_guide How to build a QueueSim Cloud model: the node types (arrivals, service, delay, split, settype, bytype, exit), staff groups, distributions, plan limits and a wor
• check_queue_model Check a QueueSim Cloud model (a multi-step queueing system built from nodes and staff groups) without running it. Returns every problem found (missing links, a
• run_queue_model Run a QueueSim Cloud model (a multi-step queueing system built from nodes and staff groups) on the QueueSim Cloud discrete event engine. Returns, per service no

Details

• Version: 1.3.0
• Transports: streamable-http
• Uptime (7 days): 100%
• Median latency: 250 ms
• First indexed: 2026-11-01T08:57:09.661Z
• Last seen in registry: 2026-11-10T03:17:09.909Z
• Repository: https://github.com/chiaha-ai/queuesim-site

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