DiscreteRate

Run DRS demos (Fast-Slow Drain, Hamburger Duo, Valdez Tanker) and explore the paradigm.

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What it can do

    What data it sees

    Do you need an account

    No: the server works without sign-in

    Run DRS demos (Fast-Slow Drain, Hamburger Duo, Valdez Tanker) and explore the paradigm.

    How to connect

    How to connect DiscreteRate to Claude

    The server address to paste into Claude settings:

    https://discreterate.com/mcp/v1

    1. Open Claude (claude.ai or the desktop app).
    2. Go to Settings → Connectors.
    3. Click Add custom connector.
    4. Paste the server address copied below into Remote MCP server URL and click Add.
    5. In a chat, click + → Connectors and switch the new connector on.

    Custom connectors are available on Free, Pro, Max, Team and Enterprise plans (Free is limited to one). On Team and Enterprise an organization Owner adds the connector first under Organization settings → Connectors.

    Authorization

    After you click Add, a sign-in window for the service opens. Sign in with your own account and approve access. Claude never sees your password.

    How to connect DiscreteRate to ChatGPT

    The server address to paste into ChatGPT settings:

    https://discreterate.com/mcp/v1

    1. Open ChatGPT in a browser (chatgpt.com). A Plus, Pro, Business, Enterprise or Edu plan is required.
    2. Turn on developer mode once: Settings → Apps → Advanced settings → Developer mode.
    3. Open Settings → Connectors and click Create.
    4. Fill in the form: Name (anything), Description (one line about what the service does), MCP server URL (copy it below).
    5. Under Authentication choose OAuth if the service requires sign-in, otherwise None. Click Create.
    6. In a new chat open + → Apps/Connectors and enable the connector.

    OpenAI has renamed this section before (Connectors → Apps/Plugins). If the label differs, search settings for "developer mode". On Business/Enterprise workspaces an admin must allow custom connectors first.

    Authorization

    On first use ChatGPT opens the service's sign-in window. Sign in and approve access.

    How to connect DiscreteRate to Cursor

    The server address to paste into Cursor settings:

    https://discreterate.com/mcp/v1

    Fastest: click Open in Cursor below and confirm the prompt.

    Manually:

    1. In Cursor open Settings → Cursor Settings → MCP and click Add new global MCP server.
    2. Paste the JSON copied below into ~/.cursor/mcp.json (per project: .cursor/mcp.json in the repo root).
    3. Save the file. The server appears in the MCP list; authorize it there if asked.

    Authorization

    If the service needs sign-in, an authorize button appears next to the server in the MCP list.

    Server tool list (14)

    Raw names from tools/list. Only developers need these.

    run_fast_slow_drainRun the Fast-Slow Drain (FSD) demo — Damiron-Nastasi 2008 oscillating tank. The canonical DRS-vs-DES event-count demonstration. Returns engine output including the event counts (DES vs DRS), tank-level trace, and cycle summary. ANTI-FABRICATION: numbers come from a real DRS engine run; quote verbatim, don't recall from training data.
    run_hamburger_duoRun the Hamburger Duo (HAM) demo — Andy Siprelle's 5-stage finite-source line, executed as both DES and DRS implementations on the same model so the event-count and throughput numbers can be compared apples-to-apples. Returns engine output for the side-by-side run. ANTI-FABRICATION: numbers come from a real engine run; quote verbatim.
    run_valdez_tankerRun the Valdez Tanker (VALD) demo — Koelling-Remy 1983 Alaska Pipeline model, the paradigm-integration motivator. Crude flows continuously into the Valdez Marine Terminal storage tank (Flow); tankers arrive discretely to drain it (Item); DRS handles both via F2I / I2F transitions. Returns engine output including tanker arrival/departure events and tank-level trace. ANTI-FABRICATION: numbers come from a real engine run; quote verbatim.
    run_vegetable_plantRun the Vegetable Plant (VEG) demo — a Plant Builder distribution-control model. Two Making lines feed five Packing lines through eight surge bins; a DRS rate solver splits and rebalances the flow across the bins as the plant works through its campaign schedule. Returns the plant rollup (utilization, campaigns, active window), per-product goal attainment, per-system campaign timelines, and final surge-bin / delivered levels. ANTI-FABRICATION: numbers come from a real Plant Builder engine run; quote verbatim.
    run_chocolate_processingRun the Chocolate Processing (CHOC) demo — Plant Builder's joint DES↔DRS bridge. Three systems in series (Bean Processing → Cocoa Powder → Chocolate): DES schedules campaigns and injects equipment failures, a DRS rate solver carries the continuous flow, a bridge couples them. Exercises all 7 controllers + Goal blocks. Returns the plant rollup (schedule occupancy vs busy utilization, total downtime, campaigns), per-product attainment, and per-system campaign timelines with downtime. ANTI-FABRICATION: numbers come from a real Plant Builder engine run; quote verbatim.
    run_sku_capacityRun the Bottling Line / SKU-capacity (SKU) demo — a sim-foundation parameter-set example. One 5-machine bottling line run for several products (SKUs as parameter sets). Returns, per SKU, OEE (identical ~55% — time-based interrupts) and indexed real output (swings >3x: 100 / 50 / 30 / 42) plus the pacing machine. Shows you can't read per-SKU capacity off OEE. ANTI-FABRICATION: numbers come from a real sim-foundation engine run (indexed/anonymized); quote verbatim.
    run_tissue_lineRun the Tissue Line (TIS) demo — a sim-foundation parameter-set example. One tissue line (Reel supply → Converter → Winder), three strategic decisions (each a parameter set): bypass converter / run converter / add storage tower. Returns per-decision throughput as % of nameplate (75.4 / 75.4 / 73.4), the binding bottleneck (the upstream parent-reel supply in all three), and converter/storage detail. Shows the downstream decision barely moves throughput — invest at the constraint. ANTI-FABRICATION: numbers come from a real sim-foundation engine run (indexed/anonymized); quote verbatim.
    list_drs_demosList the seven DRS demos (Fast-Slow Drain · Hamburger Duo · Valdez Tanker · Vegetable Plant · Chocolate Processing · Bottling Line SKU capacity · Tissue Line). Each is reproducible against the engine via the run_* tools. Use this to discover what's available before calling describe_demo or a run_* tool.
    describe_demoFull per-demo write-up: history, what it teaches, what to expect from the run_* output. Use this to ground the user before triggering a sim run, or to explain WHY the demo exists when the user asks a conceptual question about it.
    explain_discrete_rate_simulationReturn a textbook-tier explainer of Discrete Rate Simulation: how it differs from DES and CT, the three primitives (Constraint / Buffer / Interrupt), paradigm integration via F2I / I2F. Use this for 'what is DRS?' / 'how is this different from DES?' / 'where does DRS fit in the simulation landscape?' style questions. Deterministic text — no engine call, no RNG.
    explain_three_primitivesReturn a focused write-up of the three DRS modeling primitives: Constraint (rate-limiter), Buffer (accumulated state), Interrupt (stoppage). Use this when the user asks specifically about modeling primitives or how to spell a system in DRS. Deterministic text.
    explain_paradigm_integrationReturn an explainer of paradigm integration — how DRS handles systems with both flows and items via F2I (Flow-to-Item) and I2F (Item-to-Flow) primitives. Use this when the user asks about Valdez-Tanker-style mixed-paradigm systems or 'how do flows and items coexist'. Deterministic text.
    explain_des_vs_drs_event_complexityReturn a focused write-up of the event-count complexity differences between DES and DRS, with the worked Fast-Slow Drain numbers (Continuous ~thousands vs DES ~500 vs DRS 10 events for the same 100-minute model). Use this when the user wants the practitioner-visible payoff of DRS — the 50× event-count reduction at the boundary-transition layer. Deterministic text.
    run_showcaseLIVE EXPERIMENT — run a DRS demo against the real engine with parameters you choose, and get its verbatim run envelope (metadata, execution stats, metrics, details). This is the only tool that COMPUTES fresh output: pick a demo_id and dial its knobs (e.g. `stop_time` run length, or the MTBF/MTTR/goal knobs on the plant demos) to see the real numbers for that exact configuration. IMPORTANT: a run_showcase result is NOT a verified reference number — unlike the run_* tools (run_fast_slow_drain / run_hamburger_duo / run_valdez_tanker / run_vegetable_plant / run_chocolate_processing), which return curated, canonical reference values. Present run_showcase output as a live experiment result for the parameters passed; don't blend it with the curated reference numbers. Quote any figures verbatim; do not round, average, or derive.