mcpbeat

DiscreteRate MCP Server

com.discreterate/public
answering

DiscreteRate is answering right now. Last checked 4 min ago. It exposes 14 tools.

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

The linked repository no longer exists on GitHub — it was deleted or made private.

Uptime history 42 hours of history
42 hours agonow
100.0%
Uptime 24h
91 of 91 checks
14
Tools
read from the server
1379 ms
Response time
average over 24h
open, no key
Access
streamable-http

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 4 min ago.

run in your terminal
claude mcp add public --transport http https://discreterate.com/mcp/v1
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "public": {
      "url": "https://discreterate.com/mcp/v1"
    }
  }
}
~/.codex/config.toml
[mcp_servers.public]
url = "https://discreterate.com/mcp/v1"
.cursor/mcp.json
{
  "mcpServers": {
    "public": {
      "url": "https://discreterate.com/mcp/v1"
    }
  }
}
.vscode/mcp.json
{
  "mcpServers": {
    "public": {
      "url": "https://discreterate.com/mcp/v1"
    }
  }
}

Available tools 14

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

explain
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.
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.
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.
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.
chocolate
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.
describe
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.
drs
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.
fast
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.
hamburger
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.
showcase
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.
sku
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.
tissue
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.
valdez
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.
vegetable
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.

Endpoints

URLTransportStateLatencyChecked
https://discreterate.com/mcp/v1 streamable-http answering 382 ms 4 min ago

DiscreteRate — questions

Answers built from our own checks of this server.

What can DiscreteRate do?
It exposes 14 tools, read directly from the server on our last check. Among them: describe_demo, explain_des_vs_drs_event_complexity, explain_discrete_rate_simulation, explain_paradigm_integration, explain_three_primitives, list_drs_demos and 8 more. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README. How MCP servers expose tools in the first place →
Is DiscreteRate working right now?
We send a real MCP handshake every 15 minutes. Over the last 24 hours 91 of 91 checks got a reply (100.0%), average response time 1379 ms. The bar chart above shows every period we have measured.
Is DiscreteRate still maintained?
The linked repository no longer exists on GitHub — it was deleted or made private. We show this because it changes what you can expect: an unmaintained server may keep answering for months and then stop without warning.
How do I connect DiscreteRate?
Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.
Does DiscreteRate need an API key?
No. DiscreteRate completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 14 of them are readable on this page. This is what we observed, not what the docs claim.
How fast is DiscreteRate?
It answers our handshake in 1379 ms on average, which is faster than 2% of all working MCP servers we measure. That is on the slow side — worth knowing if the tool sits inside an interactive loop. The comparison comes from our own checks across the whole registry, every 15 minutes.