MCP server

DiscreteRate Official

com.discreterate/public

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

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

Source

At a glance

Type

MCP server

Publisher

discreterate.com (verified by the MCP Registry)

Status

Working at last check

Tools

14

Token cost

About 2,512 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

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

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.public]
url = "https://discreterate.com/mcp/v1"

Gemini CLI

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

Cursor

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

VS Code

{"servers":{"public":{"type":"http","url":"https://discreterate.com/mcp/v1"}}}

Antigravity

agy mcp add public https://discreterate.com/mcp/v1

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"public","server_url":"https://discreterate.com/mcp/v1","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"public","server_url":"https://discreterate.com/mcp/v1"}

Tools

• describe_demo ~163 tokens
  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.
• explain_des_vs_drs_event_complexity ~137 tokens
  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-cou
• explain_discrete_rate_simulation ~135 tokens
  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?
• explain_paradigm_integration ~112 tokens
  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.
• explain_three_primitives ~104 tokens
  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.
• list_drs_demos ~113 tokens
  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_* t
• run_chocolate_processing ~192 tokens
  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 control
• run_fast_slow_drain ~170 tokens
  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 verbati
• run_hamburger_duo ~160 tokens
  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 fro
• run_showcase ~507 tokens
  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/goa
• run_sku_capacity ~160 tokens
  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 pa
• run_tissue_line ~195 tokens
  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),
• run_valdez_tanker ~190 tokens
  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 out
• run_vegetable_plant ~174 tokens
  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

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