DiscreteRate

com.discreterate/publicVersion 1.0.0

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

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https://discreterate.com/mcp/v1Responds158 msNov 14, 2026, 13:54 UTC

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Claude Code

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

Claude Desktop and claude.ai

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

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

VS Code

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

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Tools

14 tools

Tools of DiscreteRate
	Description		Read-only	Idempotent	Open world
`describe_demo`Full 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.	Full 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.	No	Yes	Yes	No
`explain_des_vs_drs_event_complexity`Return 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.	Return 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.	No	Yes	Yes	No
`explain_discrete_rate_simulation`Return 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.	Return 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.	No	Yes	Yes	No
`explain_paradigm_integration`Return 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.	Return 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.	No	Yes	Yes	No
`explain_three_primitives`Return 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.	Return 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.	No	Yes	Yes	No
`list_drs_demos`List 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.	List 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.	No	Yes	Yes	No
`run_chocolate_processing`Run 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 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.	No	Yes	Yes	No
`run_fast_slow_drain`Run 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 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.	No	Yes	Yes	No
`run_hamburger_duo`Run 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 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.	No	Yes	Yes	No
`run_showcase`LIVE 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.	LIVE 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.	No	Yes	No	No
`run_sku_capacity`Run 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 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.	No	Yes	Yes	No
`run_tissue_line`Run 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.	Run 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.	No	Yes	Yes	No
`run_valdez_tanker`Run 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 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.	No	Yes	Yes	No
`run_vegetable_plant`Run 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 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.	No	Yes	Yes	No

Details

Registry status: Active
Published: May 27, 2026
Updated: May 27, 2026
Website: Not given
Repository: https://github.com/chiaha-ai/discreterate-site⁠ (opens in a new tab)
Categories (suggested): E-commerceSuggested categories are assigned automatically from the registry text and may be wrong. Verified operators can correct them.
GDPR: Not declared

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