# SCModeling (remote · scmodeling.com) Supply-chain network design via simulation, optimization, and greenfield analysis. - Trust score: 72/100 (medium) - Change this week: +6 - Registry status: active - Liveness: live - Owner verified: no - Last scored: 2026-08-03 ## Components - remote · `scmodeling.com`: 72/100 (this document), [markdown](https://verifymcp.io/servers/com-scmodeling-public/scmodeling.md), [page](https://verifymcp.io/servers/com-scmodeling-public/scmodeling) ## Channel facts - Endpoint: `https://scmodeling.com/mcp` - Transports: `streamable-http` - Auth: `none` - Version: `1.0.1` ## Trust breakdown How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog) Scored 2026-08-03. - **Endpoint Security**: 80/100 - The endpoint's TLS certificate is valid, in date, and uses a strong key. - No authorisation is required to call this server. Every tool declares its destructiveHint and none is destructive, so open access doesn't expose one. - HTTPS is enforced; there's no plaintext access path. - The HSTS (Strict-Transport-Security) header is present. - DNSSEC check failed: this domain isn't protected by DNSSEC. - **Transport & Reachability**: 100/100 - Verified streamable-http transport via a live MCP handshake. - **Schema Quality & AI Usability**: 75/100 - AI-judged instruction clarity (excellent). - Context-footprint check failed: tool/resource definitions use about 1504 tokens (~136/item across 11 items; 11 tools + 0 resources), over budget; trim descriptions and params. - Usage-examples check failed: none of the tools include examples. - **Stability & Change Management**: 27/100 - Stability observed for 8 of 30 days with no destabilising changes; credit accrues until the full window elapses. - **Tool Coverage**: 100/100 - 100% of tools have a non-trivial description (not blank, and not just the tool's name). - 100% of tool parameters carry a description. - Structured output schemas are declared (100% of tools); any adoption earns full credit. - **Capabilities**: 20/100 - Spec-recency check failed: implements MCP spec 2024-11-05; the latest is 2026-07-28. ## Install ### Claude ```bash claude mcp add --transport http com-scmodeling-public https://scmodeling.com/mcp ``` ### Codex ```toml [mcp_servers.com-scmodeling-public] url = "https://scmodeling.com/mcp" ``` ### opencode ```json { "$schema": "https://opencode.ai/config.json", "mcp": { "com-scmodeling-public": { "type": "remote", "url": "https://scmodeling.com/mcp", "enabled": true } } } ``` ### OpenClaw ```bash openclaw mcp add com-scmodeling-public --url https://scmodeling.com/mcp --transport streamable-http ``` ### Hermes ```yaml mcp_servers: com-scmodeling-public: url: "https://scmodeling.com/mcp" ``` ### Other ```json { "mcpServers": { "com-scmodeling-public": { "type": "http", "url": "https://scmodeling.com/mcp" } } } ``` The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs. ## Changelog Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims. ### 2026-08-03 (score 72, +1) No change was recorded against any check on this day. Stability & Change Management went from 23 to 27. That category is still filling its 30-day observation window: 7 days of observed history at the previous scan, 8 at this one. The score rises as the window fills, whether or not the server changes. ### 2026-07-31 (score 71, +3) - [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server ### 2026-07-30 (score 68, +1) No change was recorded against any check on this day. Stability & Change Management went from 10 to 13. That category is still filling its 30-day observation window: 3 days of observed history at the previous scan, 4 at this one. The score rises as the window fills, whether or not the server changes. ### 2026-07-29 (score 67, +1) No change was recorded against any check on this day. Stability & Change Management went from 7 to 10. That category is still filling its 30-day observation window: 2 days of observed history at the previous scan, 3 at this one. The score rises as the window fills, whether or not the server changes. ### 2026-07-27 (score 66, +1) - [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server ### 2026-07-26 (score 65) First indexed and scored. ## MCP tools (11) ### `run_simulation` (~132 tokens) 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 VERBATIM in your reply. Do not round, estimate, average, or compute derived figures from training-data recall. If the user asks a follow-up about the same model, re-call this tool rather than recalling numbers from earlier in the conversation. Input parameters: - `model_id` (string, required): Which sample model to simulate Output parameters: - `details` (object): Full run detail: config, locations, materials, routing, demands, orders, shipments, inventory_timeseries - `metadata` (object): Model name, version, timestamp - `metrics` (array): Top-line scalar KPIs (orders, shipments, simulation_days) ### `list_models` (~47 tokens) 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. Output parameters: - `content` (array): MCP content blocks — single text block with the response body ### `get_sc_theory` (~64 tokens) 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. Output parameters: - `content` (array): MCP content blocks — single text block with the response body ### `explain_optimization` (~141 tokens) 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, multi-period, BOM/production, multi-objective). Also covers when to reach for optimization vs simulation. Pure static text — no engine call, deterministic output. Use this when the user asks a conceptual 'how does network optimization work' question. ChiAha's AMOS optimizer (open-source, Odin, GLOP/CBC via OR-Tools) powers the Tariff and Coffee Co-pack demos on the sandbox. Output parameters: - `content` (array): MCP content blocks — single text block with the response body ### `explain_greenfield` (~152 tokens) 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 within a distance band), and the inverse problem of solving for minimum N. Also covers when to use greenfield vs facility selection (the open/close MIP). Pure static text — no engine call, deterministic output. Use this when the user asks a conceptual 'how does greenfield analysis work' or 'where would I put my DCs' question. ChiAha's GreenfieldAnalysis engine powers the US Greenfield Design demo on the sandbox. Output parameters: - `content` (array): MCP content blocks — single text block with the response body ### `list_opt_demos` (~86 tokens) 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 optimization on real client data, the SCModeling desktop tool is the product. Output parameters: - `content` (array): MCP content blocks — single text block with the response body ### `describe_opt_demo` (~65 tokens) 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. Input parameters: - `demo_id` (string, required): Which optimization demo to describe Output parameters: - `content` (array): MCP content blocks — single text block with the response body ### `get_opt_result` (~240 tokens) 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. ANTI-FABRICATION: every numeric result is verbatim from the optimization engine that ran offline — quote them in your reply, do not round or recompute. Call describe_opt_demo first to learn valid scenario_key formats for each demo. Input parameters: - `demo_id` (string, required): Which optimization demo - `scenario_key` (string): Scenario key within the demo. Format varies per demo — call describe_opt_demo for the exact valid keys before guessing. Tariff uses 'APAC=' where N is one of 0, 7.5, 25, 50, 100. Coffee uses '