MCP server that wraps the Dagster GraphQL API — manage runs, assets, schedules, sensors, and backfills from any MCP client
Nothing to run from here
QueueSim is installed from its publisher's own source and answers where it runs, so this marketplace is not in the path of a single call. There is no address here to send one to, and a panel that pretended otherwise would be showing you an answer we made up. Install it and call it from your own client — the Installation tab has the entry for each one.
11
tools declared
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trust score
remote
at its publisher
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calls last 7d
What it does
Run M/M/c queue simulations and four scenarios (call center, ER, coffee shop, single server).
Quickstart
# 1 — add it to Claude Code
claude mcp add --scope user --transport http queuesim-mcp https://queuesim.com/mcp/v1
# 2 — ask your agent for something these tools do
# simulate_mmc, list_scenarios, describe_scenario and 8 more
QueueSim costs nothing on mcprush: there is no plan to choose here, no cap to set and nothing mcprush can bill you for.
Publishernot claimed
QUAll 1 server
queuesim1 server
1 category
Collected from a public index. Nobody has claimed this account, so nothing here was written by its author — claim it if it is yours.
Installation
Where are you running it?
Every route below installs the same thing and ends at the same approval screen. Nothing here runs on your machine and nothing runs on ours: this server answers at its publisher’s own address, and what you install is the connection straight to it.
Claude Codedeclared by this listing
This is a public server: it answers at its publisher’s own address and this marketplace is not in the path. Claude Code registers it in one command; --scope user makes it available in every project. The transport below is http, as the publisher's own manifest declares it.
claude mcp add --scope user --transport http queuesim-mcp https://queuesim.com/mcp/v1Reconnect, or start a new session, and the tools appear in the model’s tool list.
Free on mcprush, and it answers at its publisher’s own address: this marketplace is not in the path, so there is no key of ours to hold and no card to add.
What it writes
One config entry pointing straight at the publisher’s own address — this marketplace is not in the path, and nothing from this listing executes on your machine.
What you approve
11 tools, with what each one reads, writes and reaches shown before you agree — the same list on every route above. Read the tool surface.
Tool surface
What the model actually sees. Descriptions are diffed on every release — see version history.
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 server count (c). Optional: distribution shapes, service coefficient of variation, run length. Returns per-hour metrics and an overall summary (avg wait, queue length, offered load, throughput). This is the primary tool for 'how many servers
| Parameter | Type | Required | Notes |
|---|---|---|---|
| arrivalRate | number | yes | Mean arrivals per hour (λ). Any positive value up to 200. |
| serviceRate | number | yes | Mean customers one server can finish per hour (μ). Must be > 0. |
| servers | integer | yes | Number of parallel servers (c). Integer 1-50. |
| arrivalDistribution | string | no | Shape of inter-arrival times. 'Exponential' = Poisson process (default). 'Constant' = evenly-spaced. |
| serviceDistribution | string | no | Shape of service-time distribution. 'Exponential' = classical M/M/c (default). |
| serviceCoV | number | no | Coefficient of variation for service time — used when serviceDistribution is 'Normal' or 'LogNormal'. Ignored for Exponential/Constant. Range 0-5. |
| simulationDays | integer | no | Days to simulate (default 7). Range 1-30 — longer runs are not supported on the public surface; for production-scale studies contact queuesim@chiaha.com. |
List the four pre-built QueueSim scenarios. Returns key, title, and one-line description for each (Single Server, Coffee Shop, Grocery Checkout, Call Center). Call this when the user's problem matches one of the preset shapes — use describe_scenario for more detail and simulate_scenario to run one.
No parameter schema on file.
Return full details for one preset scenario: title, description, teaching note, peak parameters, and per-hour arrival + staffing arrays. Use this before simulate_scenario to understand the default shape and what overrides make sense.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| name | string | yes | Scenario key from list_scenarios. |
Run one of the four preset scenarios (single, coffee, grocery, callcenter) with optional overrides. Overrides apply UNIFORMLY across open hours — e.g. setting servers=5 on 'coffee' replaces the 4/6/4 staffing pattern with a flat 5 during open hours (closed hours stay at zero). Use this for (a) faithful reproduction of a scenario's defaults, or (b) uniform scaling (everywhere it was open, use these
| Parameter | Type | Required | Notes |
|---|---|---|---|
| name | string | yes | Scenario key from list_scenarios. |
| overrides | object | no | Optional overrides applied uniformly across open hours (closed hours preserved at zero for scheduled scenarios). All fields optional — leave empty to run the scenario's published defaults. |
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., 'my coffee shop is open 6am–10pm with 4 baristas off-peak, 7 at the 8am rush, 5 at the 4pm rush'). Inputs: arrivalRates (24-element array of customers/hr per hour-of-day) and staffing (24-element array of servers/hr); optional uniform
| Parameter | Type | Required | Notes |
|---|---|---|---|
| arrivalRates | array | yes | 24 hourly arrival rates (customers/hr, one per hour-of-day 0-23). Use 0 for closed hours (terminating system). Range 0-200 per hour. |
| staffing | array | yes | 24 hourly staffing counts (servers/hr, one per hour-of-day 0-23). Use 0 for closed hours. Range 0-50 per hour. |
| serviceTimeMinutes | number | no | Mean service time in minutes per customer. Applies uniformly across hours. Range 0.1-180. |
| simulationDays | integer | no | Days to simulate. Range 1-30. |
| arrivalDistribution | string | no | — |
| serviceDistribution | string | no | — |
| serviceCoV | number | no | CoV for service time when distribution is Normal or LogNormal. Range 0-5. |
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 traffic to each). Both runs have identical total capacity (c × μ) and identical total arrivals (λ), so the offered load ρ is the same; the only structural difference is whether arrivals share a queue or split into c isolated streams. The po
| Parameter | Type | Required | Notes |
|---|---|---|---|
| arrivalRate | number | yes | Mean total arrival rate (λ). Pooled run takes all of it; separate run divides evenly across the c queues. |
| serviceRate | number | yes | Mean service rate per server (μ, customers/hour each server finishes). Identical across both runs. |
| servers | integer | yes | Number of servers (c). Pooled: one queue feeds all c. Separate: c independent queues, each with one server and λ/c traffic. Range 2-50 (with c=1 there's nothing to compare). |
| simulationDays | integer | no | Days to simulate (same for both runs). Range 1-30. |
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 inputs. Use this when the user asks a conceptual 'why' or 'how does this work' question rather than asking for a number.
No parameter schema on file.
Return a textbook-level description of six queueing complexity patterns beyond basic M/M/c: abandonment/reneging, priority tiers, overflow routing, skills-based routing, compound service, and server outages. Use this when the user describes real-world complexity (customers hanging up, VIP queues, specialist escalation, agent breaks, transfers) that plain M/M/c doesn't model. The tool frames each p
No parameter schema on file.
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. Use this when the user asks 'how many servers do I need?' / 'what staffing keeps wait under N minutes?'. The tool runs a binary search over candidate server counts (up to maxServers, default 50), invoking the simulator for each candidate.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| arrivalRate | number | yes | Mean arrivals per hour (λ). |
| serviceRate | number | yes | Mean customers one server can finish per hour (μ). Must be > 0. |
| targetAvgWaitMinutes | number | yes | Maximum average wait time you're willing to accept, in minutes. The tool returns the smallest server count that meets this target. |
| maxServers | integer | no | Search ceiling (default 50, max 50). If even this many servers can't meet the target, the tool returns null with the achieved wait. |
| simulationDays | integer | no | Days to simulate per candidate (default 7). Range 1-30. Lower = faster search; higher = less seed-to-seed variance. |
| arrivalDistribution | string | no | — |
| serviceDistribution | string | no | — |
| serviceCoV | number | no | — |
Given an M/M/c configuration (arrivalRate, serviceRate, servers) and optionally an observed average wait, returns a queueing-theory framed interpretation: where you sit on the utilization curve, what ρ means in plain language, what one more or fewer server would qualitatively do, and which complexity factors (priority, abandonment, skills routing) might be hiding in real data the M/M/c model can't
| Parameter | Type | Required | Notes |
|---|---|---|---|
| arrivalRate | number | yes | Mean arrivals per hour (λ). |
| serviceRate | number | yes | Mean customers one server finishes per hour (μ). |
| servers | integer | yes | Server count (c). |
| observedAvgWaitMinutes | number | no | Optional. The avg wait the user observed (from simulate_mmc, an Erlang-C calculator, or real measurements). If omitted, the tool computes ρ from the inputs and gives a parameter-only interpretation. |
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. Use this when the user is validating QueueSim's engine against textbook values, learning queueing theory by watching simulation converge on the formula, or auditing a result that 'feels off' — agreement within ~5%% is the canonical sanity
| Parameter | Type | Required | Notes |
|---|---|---|---|
| arrivalRate | number | yes | Mean arrivals per hour (λ). |
| serviceRate | number | yes | Mean customers one server can finish per hour (μ). Must be > 0. |
| servers | integer | yes | Number of parallel servers (c). Integer 1-50. |
| simulationDays | integer | no | Days to simulate on the DES side. Closed-form is instant. Range 1-30; longer runs converge closer to the formula. |
Free
$0 forever
- Every tool — any call limit is its publisher’s, not ours
- No card, and mcprush charges nothing for it
- Runs at its publisher’s own address — this marketplace is not in the path
- Nothing to cap, because mcprush bills nothing
What counts against your monthly calls
| Tool | Unit | Calls used | Out of the allowance |
|---|
Nothing here is billable: mcprush charges nothing to install QueueSim or to call it, at any volume.
Call allowance · this installenforced at the gateway
Monthly allowance, in calls
—
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Alert at 80% · then the tool returns a normal MCP error
Used this month: —
—Grade not published
No rule-by-rule report on file for this release
Two independent axes, because powerful and malicious are different questions. The grade is threat only. The capability level is blast radius, and it is never a penalty on the grade — it is priced as one subtract-only term in the score, where you can see it.
This listing is an address its publisher runs, and you connect to it directly — this marketplace is not in the path. The scanner reads packages and public source, and an address is neither. So there is no grade — not a withheld one, an unmeasured one.
Release history
This is an address its publisher runs: which release it serves is theirs to choose, so there is nothing here to pin. The history below is for reading; the current release on file is 1.0.0.
1.0.0
undated
latestNo release note was published with this version.
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One review per account, from a signed-in account that does not publish this listing. Nothing else is asked — you can say what you think before you install it. Publishers can reply once per review, and a review can be edited or deleted by whoever wrote it.
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