이 MCP로 할 수 있는 일
Runs and explains Discrete Rate Simulation demonstrations, including industrial flow models, mixed flow-and-item systems, and DES comparisons.
기능
도구
14
도구
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.
읽기 전용
멱등성
입력 스키마
{'type': 'object', 'required': ['demo'], 'properties': {'demo': {'enum': ['fast_slow_drain', 'hamburger_duo', 'valdez_tanker', 'vegetable_plant', 'chocolate_processing', 'sku_capacity', 'tissue_line'], 'type': 'string', 'description': 'Which DRS demo to act on. See list_drs_demos for the catalog.'}}}
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.
읽기 전용
멱등성
입력 스키마
{'type': 'object', 'properties': {}}
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.
읽기 전용
멱등성
입력 스키마
{'type': 'object', 'properties': {}}
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.
읽기 전용
멱등성
입력 스키마
{'type': 'object', 'properties': {}}
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.
읽기 전용
멱등성
입력 스키마
{'type': 'object', 'properties': {}}
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.
읽기 전용
멱등성
입력 스키마
{'type': 'object', 'properties': {}}
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.
읽기 전용
외부 접근 가능
입력 스키마
{'type': 'object', 'properties': {}}
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.
읽기 전용
외부 접근 가능
입력 스키마
{'type': 'object', 'properties': {'simulation_minutes': {'type': 'integer', 'default': 100, 'maximum': 1000, 'minimum': 10, 'description': 'Total simulation horizon in minutes. Default 100. Range 10-1000.'}}}
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.
읽기 전용
외부 접근 가능
입력 스키마
{'type': 'object', 'properties': {'simulation_days': {'type': 'integer', 'default': 7, 'maximum': 30, 'minimum': 1, 'description': 'Days to simulate. Default 7. Range 1-30.'}}}
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.
읽기 전용
외부 접근 가능
입력 스키마
{'type': 'object', 'required': ['demo_id'], 'properties': {'knobs': {'type': 'object', 'description': 'Optional parameters as a map of name:number. fast_slow_drain / hamburger_duo accept `stop_time` (run length in minutes, 1–100000). valdez_tanker accepts `duration_days` (run length in days, 1–365; it drives the circulating-ship items loop). vegetable_full accepts `making_goal` (units, 0–100000), `making_mtbf` / `making_mttr` / `packing_mtbf` / `packing_mttr` (hours, 0–1000). chocolate_processing accepts `bp_goal` (units, 0–100000), `breaker_mtbf` / `breaker_mttr` (hours, 0–1000), `changeover_delay` (hours, 0–48). Unknown names are rejected; out-of-range values are clamped by the engine.'}, 'demo_id': {'enum': ['fast_slow_drain', 'hamburger_duo', 'valdez_tanker', 'vegetable_full', 'chocolate_processing'], 'type': 'string', 'description': 'Which DRS demo to run live against the real engine.'}}}
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.
읽기 전용
외부 접근 가능
입력 스키마
{'type': 'object', 'properties': {}}
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.
읽기 전용
외부 접근 가능
입력 스키마
{'type': 'object', 'properties': {}}
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.
읽기 전용
외부 접근 가능
입력 스키마
{'type': 'object', 'properties': {'simulation_days': {'type': 'integer', 'default': 30, 'maximum': 90, 'minimum': 1, 'description': 'Days to simulate. Default 30. Range 1-90.'}}}
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.
읽기 전용
외부 접근 가능
입력 스키마
{'type': 'object', 'properties': {}}
기록
최근 도구 변경
추가됨
run_showcase
2026년 9월 17일 12:34 PM
추가됨
explain_des_vs_drs_event_complexity
2026년 9월 17일 12:34 PM
추가됨
explain_paradigm_integration
2026년 9월 17일 12:34 PM
추가됨
explain_three_primitives
2026년 9월 17일 12:34 PM
추가됨
explain_discrete_rate_simulation
2026년 9월 17일 12:34 PM
추가됨
describe_demo
2026년 9월 17일 12:34 PM
추가됨
list_drs_demos
2026년 9월 17일 12:34 PM
추가됨
run_tissue_line
2026년 9월 17일 12:34 PM
추가됨
run_sku_capacity
2026년 9월 17일 12:34 PM
추가됨
run_chocolate_processing
2026년 9월 17일 12:34 PM
추가됨
run_vegetable_plant
2026년 9월 17일 12:34 PM
추가됨
run_valdez_tanker
2026년 9월 17일 12:34 PM
추가됨
run_hamburger_duo
2026년 9월 17일 12:34 PM
추가됨
run_fast_slow_drain
2026년 9월 17일 12:34 PM
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