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SCModeling

by scmodeling.com in Onchain & crypto

MCP serverPassing, checked 2 h ago

Supply-chain network design via simulation, optimization, and greenfield analysis.

https://scmodeling.com/mcp
Tools
12
open to any client
Uptime
100%
last 30 days
Response time
315 ms
4.4 s slowest 5%
Last check
Passed
2 h ago, next in 4 h

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How to connect

Add it to any MCP client that supports remote servers.

{
  "mcpServers": {
    "scmodeling": {
      "type": "http",
      "url": "https://scmodeling.com/mcp"
    }
  }
}

12 tools

  • run_simulation

    Run a supply-chain simulation on a bundled SCModeling sample model (sdi-db). Returns metrics, inventory time-series, orders, shipments, routing and BOM. ANTI-FABRICATION: the returned numbers come from a real discrete-event simulation run on the sc-sim engine. Quote them…

  • list_models

    List the bundled SCModeling sample supply-chain models. Returns a catalog with each model's id and a short description. Use this before run_simulation to know which model_id values are valid.

  • get_sc_theory

    Reference guide to supply-chain simulation concepts: ordering policies, BOM, FDD formulas, event-driven simulation. Pure static text — no engine call, deterministic output. Use this when the user asks a conceptual 'how does this work' question rather than asking for a number.

  • explain_optimization

    Reference text on supply-chain network optimization — mixed-integer programming (MIP), the structure of decision variables and constraints, the objective function for landed-cost minimization, and the common problem classes (facility selection, sourcing, flow constraints…

  • explain_greenfield

    Reference text on greenfield analysis — clean-slate facility-location math. Covers the weighted center-of-gravity (Weber) formulation, Weiszfeld's iterative algorithm, Lloyd's-style alternating location-allocation for N facilities, service constraints (% demand vs % customers…

  • explain_simulation

    Reference text on supply-chain simulation — how a discrete-event model of a network behaves through time. Covers event-driven execution (future-event list, the consume / check-inventory / place-order / fill / ship / deliver vocabulary), why inventory POSITION rather than on-hand…

  • list_opt_demos

    List the bundled SCModeling optimization demos. Returns id + label + one-line summary for each (Tariff, Coffee Co-pack, SSO Basic). Use this before describe_opt_demo or get_opt_result to know which demo_id values are valid. All demos are precomputed sample-only fixtures — for…

  • describe_opt_demo

    Full detail on one optimization demo — controls, available scenario keys, sites, fixed parameters, citations, and the key finding the demo illustrates. Use this before get_opt_result to know what scenario_key values are accepted.

  • get_opt_result

    Get the precomputed result for one scenario of an optimization demo. Returns the verbatim engine output JSON (AMOS for tariff/coffee, SSO output for sso-basic) including the optimal sourcing/production/transport decisions, costs, and any open/close facility variables…

  • list_greenfield_demos

    List the bundled SCModeling greenfield demos. Returns id + label + one-line summary. Currently one demo (US, 189 customer points). Use this before describe_greenfield_demo or get_greenfield_result.

  • describe_greenfield_demo

    Full detail on one greenfield demo — region, customer count, available dc_count values, and the score-curve elbow finding. Use this before get_greenfield_result to know what dc_count values are precomputed.

  • get_greenfield_result

    Get the precomputed result for one DC count of a greenfield demo. Returns sited DCs (lat/lon + city/state, nearest-city snapped), customer-to-DC assignments, and the score for that DC count. ANTI-FABRICATION: every result is verbatim engine output from greenfield-cli — quote…

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