simulate_scenario
Counterfactual WHAT-IF re-scoring of 316 DC Hub power markets under YOUR explicit deltas — answers "what happens to the market ranking if conditions change" (only DC Hub holds the underlying components). Params (all optional, pass at least one delta): avg_kwh_cents_pct (power-price % change, e.g....
This record as markdown: /tools/cloud-dchub-mcp-server/simulate-scenario.md
What simulate_scenario does on Mcp Server
AI agents call simulate_scenario to retrieve information from Mcp Server without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
top_n | integer | — | Markets to return, ranked by |score delta| (default 10) |
market | string | — | Score ONE market by slug (optional), e.g. abilene — slugs from rank_markets |
avg_kwh_cents_pct | number | — | Power price % change, e.g. 30 for +30% or -20 for -20% |
curtailment_pct_delta | number | — | Percentage POINTS added/removed from curtailment |
queue_wait_months_delta | number | — | Months added/removed from interconnection queue wait |
reserve_margin_pct_delta | number | — | Percentage POINTS added/removed from reserve margin, e.g. -5 |
time_to_power_months_delta | number | — | Months added (+) or removed (-) from time-to-power, e.g. 12 |
Parameters from the server's own tool schema.
Why simulate_scenario is rated Low
Even though simulate_scenario only reads data, uncontrolled read access leaks sensitive information and racks up API costs: an agent caught in a retry loop can make thousands of calls a minute without anyone noticing.
Risk signalsBulk/mass operation — affects multiple targets
Attacks that exploit this kind of access
The rule that runs simulate_scenario safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Mcp Server, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For simulate_scenario, this is the rule to start with:
simulate_scenario is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Mcp Server, apply this rule, and every simulate_scenario call is checked against it from then on.
Questions about simulate_scenario
Counterfactual WHAT-IF re-scoring of 316 DC Hub power markets under YOUR explicit deltas — answers "what happens to the market ranking if conditions change" (only DC Hub holds the underlying components). Params (all optional, pass at least one delta): avg_kwh_cents_pct (power-price % change, e.g. 30), time_to_power_months_delta (months added/removed), queue_wait_months_delta, reserve_margin_pct_delta (points), curtailment_pct_delta (points), market (one slug, e.g. abilene), top_n (default 10, max 25 — ranked by |score change|). Returns per-market baseline vs scenario composite + component breakdown + the EXACT formula/weights in every response (transparent scenario_composite — deliberately NOT the DCPI). Keyless callers get a top-3 preview; any live key (claim_free_key) returns up to 25. Try: simulate_scenario avg_kwh_cents_pct=30 top_n=10. Do NOT use for the present-day ranking (use rank_markets) or trajectory extrapolation (use predict_market_trajectory); this answers explicit hypotheticals. It is categorised as a Read tool in the Mcp Server MCP Server, which means it retrieves data without modifying state.
simulate_scenario accepts 7 parameters: top_n, market, avg_kwh_cents_pct, curtailment_pct_delta, queue_wait_months_delta, reserve_margin_pct_delta, time_to_power_months_delta. The full parameter table on this page comes from the server's own tool schema.
Register the Mcp Server MCP server in PolicyLayer and add a rule for simulate_scenario: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Mcp Server. Nothing to install.
simulate_scenario is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the simulate_scenario rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for simulate_scenario. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
simulate_scenario is provided by the Mcp Server MCP server (https://dchub.cloud/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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