scenariosim-mcp
Deterministic what-if & scenario simulation for AI agents: projections, sensitivity & break-even.
Should I use this
Quality & Safety
Based on automated analysis of tool definitions and protocol compliance.
Context Cost
This is the approximate number of tokens consumed each time the server's tools are loaded into a model's context. Higher counts reduce the attention available for other tasks.
Install
One-Click Install
Add this to your `claude_desktop_config.json` file:
{
"mcpServers": {
"scenariosim-mcp": {
"command": "npx",
"args": [
"scenariosim-mcp"
]
}
}
}Runnable packages
1.0.2stdioRemote endpoints
https://scenariosim-mcp.pages.dev/mcpstreamable-httpWhat it can do
Tool inventory
Tools (6)
⚪run_scenario(template, inputs, metrics, horizon, period_label)
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).
Input Schema
{
"type": "object",
"properties": {
"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."
},
"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."
},
"metrics": {
"type": "array",
"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'}.",
"items": {
"type": "object",
"properties": {
"name": {
"type": "string"
},
"start": {
"type": "number"
},
"growth_rate": {
"type": "number"
},
"mode": {
"type": "string",
"enum": [
"compound",
"linear"
],
"default": "compound"
}
},
"required": [
"name",
"start"
]
}
},
"horizon": {
"type": "integer",
"description": "Number of periods to project forward (1..1200). Default depends on template (usually 12).",
"default": 12
},
"period_label": {
"type": "string",
"enum": [
"day",
"week",
"month",
"quarter",
"year"
],
"default": "month",
"description": "Label for each period; also sets annualization (periods/year)."
}
}
}🟢sensitivity_analysis(template, inputs, target_metric, variable, variables, ...)
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.
Input Schema
{
"type": "object",
"properties": {
"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."
},
"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."
},
"target_metric": {
"type": "string",
"description": "Output metric to track (see a template's 'outputs' via list_templates). Defaults to the template's primary output."
},
"variable": {
"type": "string",
"description": "A single input name to sweep."
},
"variables": {
"type": "array",
"description": "Multiple inputs to sweep (one at a time). Each: {name, variation?|values?|min?+max?, steps?}.",
"items": {
"type": "object",
"properties": {
"name": {
"type": "string"
},
"variation": {
"type": "number"
},
"steps": {
"type": "integer"
},
"values": {
"type": "array",
"items": {
"type": "number"
}
},
"min": {
"type": "number"
},
"max": {
"type": "number"
}
},
"required": [
"name"
]
}
},
"variation": {
"type": "number",
"default": 0.2,
"description": "Fractional sweep around the baseline (0<v<=1). 0.2 = +/-20%."
},
"steps": {
"type": "integer",
"default": 5,
"description": "Number of sweep points per variable (2-200)."
},
"values": {
"type": "array",
"items": {
"type": "number"
},
"description": "Explicit sweep values for a single 'variable'."
},
"min": {
"type": "number",
"description": "Sweep lower bound (with 'max')."
},
"max": {
"type": "number",
"description": "Sweep upper bound (with 'min')."
},
"horizon": {
"type": "integer",
"description": "Number of periods to project forward (1..1200). Default depends on template (usually 12).",
"default": 12
},
"period_label": {
"type": "string",
"enum": [
"day",
"week",
"month",
"quarter",
"year"
],
"default": "month",
"description": "Label for each period; also sets annualization (periods/year)."
}
},
"required": [
"template"
]
}🟡break_even(template, inputs, solve_for, target_metric, target_value, ...)
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.
Input Schema
{
"type": "object",
"properties": {
"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."
},
"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."
},
"solve_for": {
"type": "string",
"description": "Name of the input variable to solve for."
},
"target_metric": {
"type": "string",
"description": "Output metric to hit (defaults to the template's primary output)."
},
"target_value": {
"type": "number",
"description": "The value the target_metric should reach."
},
"bounds": {
"type": "array",
"items": {
"type": "number"
},
"description": "Optional [low, high] search range for the solved input. Auto-derived + expanded if omitted."
},
"horizon": {
"type": "integer",
"description": "Number of periods to project forward (1..1200). Default depends on template (usually 12).",
"default": 12
},
"period_label": {
"type": "string",
"enum": [
"day",
"week",
"month",
"quarter",
"year"
],
"default": "month",
"description": "Label for each period; also sets annualization (periods/year)."
}
},
"required": [
"template",
"solve_for",
"target_value"
]
}🟡compare_scenarios(scenarios, compare_metric, goal, horizon, include_projections)
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.
Input Schema
{
"type": "object",
"properties": {
"scenarios": {
"type": "array",
"description": "2-3 scenarios to compare. Each: {name?, template, inputs, horizon?, period_label?} or {name?, metrics:[...]} for a custom model.",
"items": {
"type": "object",
"properties": {
"name": {
"type": "string"
},
"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."
},
"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."
},
"metrics": {
"type": "array",
"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'}.",
"items": {
"type": "object",
"properties": {
"name": {
"type": "string"
},
"start": {
"type": "number"
},
"growth_rate": {
"type": "number"
},
"mode": {
"type": "string",
"enum": [
"compound",
"linear"
],
"default": "compound"
}
},
"required": [
"name",
"start"
]
}
},
"horizon": {
"type": "integer",
"description": "Number of periods to project forward (1..1200). Default depends on template (usually 12).",
"default": 12
},
"period_label": {
"type": "string",
"enum": [
"day",
"week",
"month",
"quarter",
"year"
],
"default": "month",
"description": "Label for each period; also sets annualization (periods/year)."
}
}
}
},
"compare_metric": {
"type": "string",
"description": "Metric to rank scenarios on (optional)."
},
"goal": {
"type": "string",
"enum": [
"max",
"min"
],
"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."
},
"include_projections": {
"type": "boolean",
"default": false,
"description": "Include each scenario's full per-period projections."
}
},
"required": [
"scenarios"
]
}🟢list_templates
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.
Input Schema
{
"type": "object",
"properties": {}
}🟢health_check
Server health, version, and capabilities (tools, templates, period labels, max horizon). No parameters.
Input Schema
{
"type": "object",
"properties": {}
}Community
Evidence