_ registry / mcp http-sse · checked 2h ago

ScenarioSim

https://scenariosim-mcp.pages.dev

Registry code: 8028c78581b55a2f

api record

Deterministic what-if & scenario simulation for AI agents: projections, sensitivity & break-even.

from a public catalogue that lists it, not from the operator

endpoint
https://scenariosim-mcp.pages.dev/mcp
protocol
http-sse ·2025-06-18
authentication
none observed
public key
none — nobody has proven they own this listing · is it yours? claim it
karma
0 · newcomer
_ is it live, free and safe measured by this hub
Is ScenarioSim live?
Yes — it answered the hub's last check (checked 2h ago). It answered 100% of checks over the last 30 days.
Is ScenarioSim free to use?
Yes — the hub reached it with no key and no payment.
What tools does ScenarioSim have?
6 tools: break_even, sensitivity_analysis, run_scenario, compare_scenarios, health_check, list_templates.
Is ScenarioSim safe to connect?
The hub found no text in its card or tool descriptions aimed at the agent reading them. It measures what the server answers, not its code — grant it only the access its tools need.
reachable
live
uptime, 30 days
99.8%

90 days 99.6%· all time 99.6%

latency
178ms

last good check

priced tools
0

of 6 tools

_ answered our checks, 90 days 552 checks · signed record
  • degraded → live
  • live → degraded· timeout after 20000ms
  • down → live
  • degraded → live
  • live → degraded· timeout after 20000ms
_ what it is for
topic
data & analytics analytics & metrics
used for
  • run a what-if business projection
  • compare scenarios side by side
  • solve for break-even
  • run sensitivity analysis on assumptions
takes → gives
data → data
tools
6 reads
_ usage and payments 30 days

Calls placed through this hub's router, from its own receipts. Every caller and every payer counts the same; the chain total is counted from three payers.

accounts
0

through this hub

calls served
0

successful

paid through this hub
0 USDC

what callers paid

_ what it can do 6 tools
2 open 4 never probed 2 of 6 classified

Price is per tool, not per server. An agent whose handshake is open can hold tools that demand a key or a payment, and one figure for the whole agent sends callers into a wall.

  • health_check reads open 11h ago

    Server health, version, and capabilities (tools, templates, period labels, max horizon). No parameters.

    mcp-tool

    {
  "type": "object",
  "properties": {}
}
    arguments 4 lines
  • list_templates reads open 11h ago

    Discovery tool: list every pre-built scenario template (id, label, category, description, primary output, documented inputs with defaults/units, and available output metrics), plus how to run a custom free-form scenario and the supported period labels. No required parameters.

    mcp-tool

    {
  "type": "object",
  "properties": {}
}
    arguments 4 lines
  • break_even reads unknown never probed

    Solve for the input value required to make an output metric hit a target value (deterministic bisection root-finding). Provide 'template', 'solve_for' (the input to solve), 'target_metric' (defaults to the primary output), and 'target_value'. Optionally pass 'bounds' [low, high] to constrain the search. Returns the required input value, the change from baseline, the achieved metric, and the residual. Assumes the metric is monotonic in the solved input over the range.

    mcp-tool

    {
  "type": "object",
  "required": [
    "template",
    "solve_for",
    "target_value"
  ],
  "properties": {
    "bounds": {
      "type": "array",
      "items": {
        "type": "number"
      },
      "description": "Optional [low, high] search range for the solved input. Auto-derived + expanded if omitted."
    },
    "inputs": {
      "type": "object",
      "description": "Scenario assumptions as {name: value}. Which keys are valid depends on the template (call list_templates). Unlisted keys fall back to documented defaults; unknown keys are ignored and reported in notes. You may also pass assumptions at the top level."
    },
    "horizon": {
      "type": "integer",
      "default": 12,
      "description": "Number of periods to project forward (1..1200). Default depends on template (usually 12)."
    },
    "template": {
      "type": "string",
      "description": "Pre-built scenario template id: saas_growth, pricing_change, churn_impact, cost_reduction, hiring_plan, cash_runway, unit_economics, marketing_funnel, compound_growth (aliases like 'saas','pricing','runway','ltv' also resolve). Omit (or use 'custom') to run a free-form 'metrics' projection."
    },
    "solve_for": {
      "type": "string",
      "description": "Name of the input variable to solve for."
    },
    "period_label": {
      "enum": [
        "day",
        "week",
        "month",
        "quarter",
        "year"
      ],
      "type": "string",
      "default": "month",
      "description": "Label for each period; also sets annualization (periods/year)."
    },
    "target_value": {
      "type": "number",
      "description": "The value the target_metric should reach."
    },
    "target_metric": {
      "type": "string",
      "description": "Output metric to hit (defaults to the template's primary output)."
    }
  }
}
    arguments 54 lines
  • sensitivity_analysis reads unknown never probed

    Vary one or more input assumptions and show the impact on a target output metric (one-at-a-time sensitivity). Provide 'template', the input to sweep via 'variable' (or 'variables' array), and 'target_metric' (defaults to the template's primary output). Control the sweep with 'variation' (fractional +/- around the baseline, default 0.2), 'steps' (default 5), or explicit 'values' / 'min'+'max'. Returns per-variable sweeps, an elasticity estimate, the output range, and a ranking of the most influential inputs.

    mcp-tool

    {
  "type": "object",
  "required": [
    "template"
  ],
  "properties": {
    "max": {
      "type": "number",
      "description": "Sweep upper bound (with 'min')."
    },
    "min": {
      "type": "number",
      "description": "Sweep lower bound (with 'max')."
    },
    "steps": {
      "type": "integer",
      "default": 5,
      "description": "Number of sweep points per variable (2-200)."
    },
    "inputs": {
      "type": "object",
      "description": "Scenario assumptions as {name: value}. Which keys are valid depends on the template (call list_templates). Unlisted keys fall back to documented defaults; unknown keys are ignored and reported in notes. You may also pass assumptions at the top level."
    },
    "values": {
      "type": "array",
      "items": {
        "type": "number"
      },
      "description": "Explicit sweep values for a single 'variable'."
    },
    "horizon": {
      "type": "integer",
      "default": 12,
      "description": "Number of periods to project forward (1..1200). Default depends on template (usually 12)."
    },
    "template": {
      "type": "string",
      "description": "Pre-built scenario template id: saas_growth, pricing_change, churn_impact, cost_reduction, hiring_plan, cash_runway, unit_economics, marketing_funnel, compound_growth (aliases like 'saas','pricing','runway','ltv' also resolve). Omit (or use 'custom') to run a free-form 'metrics' projection."
    },
    "variable": {
      "type": "string",
      "description": "A single input name to sweep."
    },
    "variables": {
      "type": "array",
      "items": {
        "type": "object",
        "required": [
          "name"
        ],
        "properties": {
          "max": {
            "type": "number"
          },
          "min": {
            "type": "number"
          },
          "name": {
            "type": "string"
          },
          "steps": {
            "type": "integer"
          },
          "values": {
            "type": "array",
            "items": {
              "type": "number"
            }
          },
          "variation": {
            "type": "number"
          }
        }
      },
      "description": "Multiple inputs to sweep (one at a time). Each: {name, variation?|values?|min?+max?, steps?}."
    },
    "variation": {
      "type": "number",
      "default": 0.2,
      "description": "Fractional sweep around the baseline (0<v<=1). 0.2 = +/-20%."
    },
    "period_label": {
      "enum": [
        "day",
        "week",
        "month",
        "quarter",
        "year"
      ],
      "type": "string",
      "default": "month",
      "description": "Label for each period; also sets annualization (periods/year)."
    },
    "target_metric": {
      "type": "string",
      "description": "Output metric to track (see a template's 'outputs' via list_templates). Defaults to the template's primary output."
    }
  }
}
    arguments 99 lines
  • run_scenario reads unknown never probed

    Main simulation tool. Run a deterministic what-if projection from a pre-built template (saas_growth, pricing_change, churn_impact, cost_reduction, hiring_plan, cash_runway, unit_economics, marketing_funnel, compound_growth) OR a free-form 'metrics' model. Returns period-by-period projections, headline key_results, the exact assumptions used (with defaults filled in), the methodology, notes, and a plain-language explanation. Pass 'template' + 'inputs' (assumptions), plus optional 'horizon' and 'period_label'. 100% deterministic (40-digit decimal math).

    mcp-tool

    {
  "type": "object",
  "properties": {
    "inputs": {
      "type": "object",
      "description": "Scenario assumptions as {name: value}. Which keys are valid depends on the template (call list_templates). Unlisted keys fall back to documented defaults; unknown keys are ignored and reported in notes. You may also pass assumptions at the top level."
    },
    "horizon": {
      "type": "integer",
      "default": 12,
      "description": "Number of periods to project forward (1..1200). Default depends on template (usually 12)."
    },
    "metrics": {
      "type": "array",
      "items": {
        "type": "object",
        "required": [
          "name",
          "start"
        ],
        "properties": {
          "mode": {
            "enum": [
              "compound",
              "linear"
            ],
            "type": "string",
            "default": "compound"
          },
          "name": {
            "type": "string"
          },
          "start": {
            "type": "number"
          },
          "growth_rate": {
            "type": "number"
          }
        }
      },
      "description": "For a CUSTOM free-form scenario (template omitted or 'custom'): a list of independently-growing metrics. Each: {name, start, growth_rate (per period, default 0), mode: 'compound' (default) | 'linear'}."
    },
    "template": {
      "type": "string",
      "description": "Pre-built scenario template id: saas_growth, pricing_change, churn_impact, cost_reduction, hiring_plan, cash_runway, unit_economics, marketing_funnel, compound_growth (aliases like 'saas','pricing','runway','ltv' also resolve). Omit (or use 'custom') to run a free-form 'metrics' projection."
    },
    "period_label": {
      "enum": [
        "day",
        "week",
        "month",
        "quarter",
        "year"
      ],
      "type": "string",
      "default": "month",
      "description": "Label for each period; also sets annualization (periods/year)."
    }
  }
}
    arguments 60 lines
  • compare_scenarios reads unknown never probed

    Run 2-3 scenarios and compare their key_results side by side, with deltas against the first (baseline) scenario. Provide a 'scenarios' array where each entry is {name?, template, inputs} (each may set its own horizon, or pass a shared top-level 'horizon'). Optionally rank on 'compare_metric' with 'goal' ('max' default | 'min') to pick a winner, and set include_projections:true to also return per-period series.

    mcp-tool

    {
  "type": "object",
  "required": [
    "scenarios"
  ],
  "properties": {
    "goal": {
      "enum": [
        "max",
        "min"
      ],
      "type": "string",
      "default": "max",
      "description": "Whether higher (max) or lower (min) is better for compare_metric."
    },
    "horizon": {
      "type": "integer",
      "description": "Optional shared horizon applied to scenarios that don't set their own."
    },
    "scenarios": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "name": {
            "type": "string"
          },
          "inputs": {
            "type": "object",
            "description": "Scenario assumptions as {name: value}. Which keys are valid depends on the template (call list_templates). Unlisted keys fall back to documented defaults; unknown keys are ignored and reported in notes. You may also pass assumptions at the top level."
          },
          "horizon": {
            "type": "integer",
            "default": 12,
            "description": "Number of periods to project forward (1..1200). Default depends on template (usually 12)."
          },
          "metrics": {
            "type": "array",
            "items": {
              "type": "object",
              "required": [
                "name",
                "start"
              ],
              "properties": {
                "mode": {
                  "enum": [
                    "compound",
                    "linear"
                  ],
                  "type": "string",
                  "default": "compound"
                },
                "name": {
                  "type": "string"
                },
                "start": {
                  "type": "number"
                },
                "growth_rate": {
                  "type": "number"
                }
              }
            },
            "description": "For a CUSTOM free-form scenario (template omitted or 'custom'): a list of independently-growing metrics. Each: {name, start, growth_rate (per period, default 0), mode: 'compound' (default) | 'linear'}."
          },
          "template": {
            "type": "string",
            "description": "Pre-built scenario template id: saas_growth, pricing_change, churn_impact, cost_reduction, hiring_plan, cash_runway, unit_economics, marketing_funnel, compound_growth (aliases like 'saas','pricing','runway','ltv' also resolve). Omit (or use 'custom') to run a free-form 'metrics' projection."
          },
          "period_label": {
            "enum": [
              "day",
              "week",
              "month",
              "quarter",
              "year"
            ],
            "type": "string",
            "default": "month",
            "description": "Label for each period; also sets annualization (periods/year)."
          }
        }
      },
      "description": "2-3 scenarios to compare. Each: {name?, template, inputs, horizon?, period_label?} or {name?, metrics:[...]} for a custom model."
    },
    "compare_metric": {
      "type": "string",
      "description": "Metric to rank scenarios on (optional)."
    },
    "include_projections": {
      "type": "boolean",
      "default": false,
      "description": "Include each scenario's full per-period projections."
    }
  }
}
    arguments 97 lines
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