Scenariosim MCP

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

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to Cursor Add to VS Code

Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag — we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON ▾

Client Config & Setup

Choose your client or environment

Target File:~/Library/Application Support/Claude/claude_desktop_config.json

claude_desktop_config.json

{
  "mcpServers": {
    "scenariosim-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "scenariosim-mcp"
      ]
    }
  }
}

💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Documentation Overview

ScenarioSim MCP

A transparent, 100% deterministic Model Context Protocol (MCP) server that gives LLM agents a reliable what-if / scenario simulation engine.

Agents are good at describing a plan but unreliable at projecting it: they drift on multi-period arithmetic, mishandle compounding, and can't show their work. ScenarioSim offloads the simulation to an exact, explainable engine. You provide assumptions (growth rates, churn, pricing, costs, starting metrics, a time horizon); it returns projected outcomes over time, key metrics, the exact assumptions used, plus sensitivity analysis and break-even solving — each with a plain-language explanation.

Every number flows through decimal.js at 40-digit precision (never floats), so identical inputs always produce byte-identical output. The server is stateless — no database, no sessions, no clocks or randomness in the result.

This is the third product in a suite built to the same engineering standard as PrecisionCalc MCP (deterministic high-precision finance/business math) and DecisionMatrix MCP (transparent multi-criteria decision analysis): identical project structure, output philosophy, and Cloudflare Pages deployment.

🌐 Live hosted server (free, no install)

A public remote MCP server runs on Cloudflare's edge — point any Streamable-HTTP MCP client at it:

Code

https://scenariosim-mcp.pages.dev/mcp

config.json

{ "mcpServers": { "scenariosim": {
    "type": "http", "url": "https://scenariosim-mcp.pages.dev/mcp" } } }

It runs in open mode on the free tier (no key, 20 calls/day per IP). Paid plans (Starter $12/mo · 5,000/day, Pro $39/mo · 50,000/day) are available via Stripe Checkout — buy a plan, get an API key instantly, and send it as X-API-Key. Self-host for unlimited calls with no keys. Landing page + pricing: https://scenariosim-mcp.pages.dev.

What it does

Six tools, all returning a uniform, agent-parseable envelope:

Tool	Purpose
`run_scenario`	Main tool. Project a pre-built template or a free-form model over time → per-period `projections`, headline `key_results`, the `assumptions_used`, `methodology`, `notes`, and a plain-language `explanation`.
`sensitivity_analysis`	Vary one or more inputs (one-at-a-time) and report the impact on a target metric — with an elasticity estimate, the output range, and a ranking of the most influential inputs.
`break_even`	Solve for the input value required to make a target metric hit a target value (deterministic bisection).
`compare_scenarios`	Run 2–3 scenarios side-by-side with deltas vs a baseline and an optional winner.
`list_templates`	Discovery: every template with its inputs (defaults + units) and available outputs.
`health_check`	Version, status, and capabilities.

Scenario templates

id	models	primary output
`saas_growth`	subscribers + MRR/ARR from acquisition (with its own growth) and churn	`ending_mrr`
`pricing_change`	revenue/profit impact of a price change via price elasticity	`cumulative_profit_after`
`churn_impact`	retention erosion + revenue lost vs a no-churn baseline	`cumulative_revenue_lost`
`cost_reduction`	profit + margin impact of cutting costs	`cumulative_savings`
`hiring_plan`	headcount, fully-loaded payroll, revenue capacity	`cumulative_payroll`
`cash_runway`	cash balance forward + months-to-zero runway	`runway_periods`
`unit_economics`	LTV, LTV:CAC, CAC payback, per-customer margin curve	`ltv_cac_ratio`
`marketing_funnel`	visitors → leads → customers → revenue	`total_revenue`
`compound_growth`	generic single-metric compound/linear projection	`ending_value`
`custom`	free-form: any number of independently-growing metrics	(first metric)

Every template accepts horizon (number of periods, 1–1200) and period_label (day/week/month/quarter/year, which also sets annualization). Inputs you don't provide fall back to documented defaults; unknown inputs are ignored and reported in notes. Call list_templates for the full input/output catalog.

Consistent response envelope

Every successful response contains: status, scenario, period_label, horizon, key_results (+ key_results_detail with units and full-precision value_exact), projections, assumptions_used, methodology, notes, and a natural-language explanation.

config.json

{
  "status": "success",
  "scenario": "saas_growth",
  "period_label": "month",
  "horizon": 12,
  "key_results": {
    "ending_customers": 449.7, "ending_mrr": 26982.1, "ending_arr": 323785.2,
    "total_churned_customers": 82.4, "cumulative_revenue": 232104.6
  },
  "projections": [
    { "period": 0, "customers": 200, "mrr": 12000, "new_customers": 0, "churned_customers": 0 },
    { "period": 1, "customers": 234, "mrr": 14040, "new_customers": 40, "churned_customers": 6 }
  ],
  "assumptions_used": {
    "template": "saas_growth", "starting_customers": "200", "new_customers_per_period": "40",
    "acquisition_growth_rate": "0", "churn_rate": "0.03", "arpu": "60",
    "horizon": 12, "period_label": "month"
  },
  "methodology": {
    "model": "SaaS Growth",
    "primary_output": "ending_mrr",
    "precision": "decimal.js (40 significant digits)",
    "deterministic": true,
    "period_convention": "Period 0 is the starting state; periods 1..12 are projected. 12 month(s) per year."
  },
  "notes": ["Churn is applied to the prior period's base before new customers are added."],
  "explanation": "Starting from 200 customers and adding 40 per month (churn 3%), after 12 months you reach ..."
}

Errors never cross the tool boundary as exceptions — they come back as a structured, actionable envelope:

config.json

{
  "status": "error",
  "error": {
    "type": "unknown_template",
    "message": "Unknown scenario template 'saaas'.",
    "hint": "Available templates: saas_growth, pricing_change, churn_impact, cost_reduction, hiring_plan, cash_runway, unit_economics, marketing_funnel, compound_growth. Call list_templates for details ..."
  }
}

Design note — exact numbers: headline numbers in key_results are deterministically rounded (6 dp) for easy consumption; key_results_detail[].value_exact and assumptions_used carry full-precision strings so no precision is lost in JSON. All internal math is exact 40-digit decimal.

Project structure

Code

scenariosim-mcp/
├── worker-src/
│   ├── index.mjs        # Cloudflare Pages Function (_worker.js): MCP over Streamable HTTP + billing routes
│   ├── engine.mjs       # The deterministic simulation engine: 9 templates + 6 tools + solver + validation
│   └── billing.mjs      # Stripe Checkout + KV-backed API keys, quota metering, webhook
├── server.mjs           # Local stdio MCP server (same engine, no network/state)
├── site/
│   ├── index.html       # Static landing / pricing / docs page
│   ├── mcp.json         # Machine-readable connection manifest
│   ├── llms.txt         # LLM-friendly summary
│   └── _worker.js       # Built bundle (esbuild output; git-ignored)
├── tests/
│   └── engine.test.mjs  # 29 core simulation-logic tests (node --test)
├── examples/
│   └── agent_example.mjs # End-to-end MCP client demo over HTTP
├── package.json         # build / deploy / dev / test scripts
├── wrangler.toml        # Cloudflare Pages config
├── .env.example         # Optional auth/rate-limit env reference
├── LICENSE              # MIT
└── README.md

Separation of concerns: engine.mjs is pure and transport-agnostic (import it directly in tests or any Node/Deno/edge runtime); index.mjs only handles the MCP JSON-RPC wiring, HTTP, CORS, and the auth/metering seam; server.mjs re-uses the same engine over stdio.

Requirements

Node 18+ (for the build, tests, and local dev). Only two dev/runtime deps: decimal.js (math) and esbuild (bundler).
A Cloudflare account (free tier is fine) to deploy the hosted version.

Run it locally

bash

git clone <your-fork> scenariosim-mcp && cd scenariosim-mcp
npm install

# Run the test suite (no server needed)
npm test

# Serve the MCP endpoint locally via Wrangler (builds + runs Pages dev)
npm run dev          # -> http://127.0.0.1:8788/mcp

# Try the end-to-end client demo (hosted by default, or pass a local URL)
node examples/agent_example.mjs
node examples/agent_example.mjs http://127.0.0.1:8788

# Or run the dependency-light stdio server directly
node server.mjs

Quick manual call:

Terminal

curl -s http://127.0.0.1:8788/mcp \
  -H 'content-type: application/json' \
  -H 'accept: application/json, text/event-stream' \
  -d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{
        "name":"list_templates","arguments":{}}}'

Install via npm (stdio, no hosting)

Run the server locally over stdio with a single command — nothing to deploy:

Terminal

npx -y scenariosim-mcp

Claude Desktop / any stdio MCP client (claude_desktop_config.json):

config.json

{ "mcpServers": { "scenariosim": { "command": "npx", "args": ["-y", "scenariosim-mcp"] } } }

This is the same deterministic engine as the hosted server, running on your machine.

Client configuration

Cursor — `~/.cursor/mcp.json`

config.json

{ "mcpServers": { "scenariosim": {
    "url": "https://scenariosim-mcp.pages.dev/mcp" } } }

Claude Desktop — `claude_desktop_config.json`

Claude Desktop launches stdio servers, so bridge to the HTTP endpoint with mcp-remote:

config.json

{ "mcpServers": { "scenariosim": {
    "command": "npx", "args": ["-y", "mcp-remote", "https://scenariosim-mcp.pages.dev/mcp"] } } }

VS Code — `.vscode/mcp.json`

config.json

{ "servers": { "scenariosim": {
    "type": "http", "url": "https://scenariosim-mcp.pages.dev/mcp" } } }

Read the full README →View source on GitHub →

Related MCP Servers

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Reviews

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Frequently Asked Questions about Scenariosim MCP

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "scenariosim-mcp": { "command": "npx", "args": ["-y", "scenariosim-mcp"] } }

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Technical Specs & Signals

CategoryDeveloper Tools

36Quality signal: Fair · 36/100How this signal is calculated ▾

Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20

Documentation & tools16/30

Adoption & activity1/15

Community engagement0/10

A guidance signal from public completeness & health data — not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

★ Featured

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The official MCP server for AllMCPs.com - submit and manage tools directly from your AI. The open directory for MCP servers. Connect Claude, Cursor, Windsurf, and AI agents to databases, tools, files, and APIs. Explore 10,000+ servers. AllMCPs is the premier, open directory for discovering, evaluating, and installing Model Context Protocol (MCP) servers to equip AI agents and LLMs with real-world superpowers.

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More in 💻 Developer Tools →Best MCP servers for Developers →Alternatives to Scenariosim MCP →Install in Claude Desktop Install in Cursor Install in VS Code

Scenariosim MCP

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

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to Cursor Add to VS Code

Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag — we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON ▾

Client Config & Setup

Choose your client or environment

Target File:~/Library/Application Support/Claude/claude_desktop_config.json

claude_desktop_config.json

{
  "mcpServers": {
    "scenariosim-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "scenariosim-mcp"
      ]
    }
  }
}

💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Documentation Overview

ScenarioSim MCP

A transparent, 100% deterministic Model Context Protocol (MCP) server that gives LLM agents a reliable what-if / scenario simulation engine.

🌐 Live hosted server (free, no install)

A public remote MCP server runs on Cloudflare's edge — point any Streamable-HTTP MCP client at it:

Code

https://scenariosim-mcp.pages.dev/mcp

config.json

{ "mcpServers": { "scenariosim": {
    "type": "http", "url": "https://scenariosim-mcp.pages.dev/mcp" } } }

What it does

Six tools, all returning a uniform, agent-parseable envelope:

Tool	Purpose
`run_scenario`	Main tool. Project a pre-built template or a free-form model over time → per-period `projections`, headline `key_results`, the `assumptions_used`, `methodology`, `notes`, and a plain-language `explanation`.
`sensitivity_analysis`	Vary one or more inputs (one-at-a-time) and report the impact on a target metric — with an elasticity estimate, the output range, and a ranking of the most influential inputs.
`break_even`	Solve for the input value required to make a target metric hit a target value (deterministic bisection).
`compare_scenarios`	Run 2–3 scenarios side-by-side with deltas vs a baseline and an optional winner.
`list_templates`	Discovery: every template with its inputs (defaults + units) and available outputs.
`health_check`	Version, status, and capabilities.

Scenario templates

id	models	primary output
`saas_growth`	subscribers + MRR/ARR from acquisition (with its own growth) and churn	`ending_mrr`
`pricing_change`	revenue/profit impact of a price change via price elasticity	`cumulative_profit_after`
`churn_impact`	retention erosion + revenue lost vs a no-churn baseline	`cumulative_revenue_lost`
`cost_reduction`	profit + margin impact of cutting costs	`cumulative_savings`
`hiring_plan`	headcount, fully-loaded payroll, revenue capacity	`cumulative_payroll`
`cash_runway`	cash balance forward + months-to-zero runway	`runway_periods`
`unit_economics`	LTV, LTV:CAC, CAC payback, per-customer margin curve	`ltv_cac_ratio`
`marketing_funnel`	visitors → leads → customers → revenue	`total_revenue`
`compound_growth`	generic single-metric compound/linear projection	`ending_value`
`custom`	free-form: any number of independently-growing metrics	(first metric)

Consistent response envelope

config.json

{
  "status": "success",
  "scenario": "saas_growth",
  "period_label": "month",
  "horizon": 12,
  "key_results": {
    "ending_customers": 449.7, "ending_mrr": 26982.1, "ending_arr": 323785.2,
    "total_churned_customers": 82.4, "cumulative_revenue": 232104.6
  },
  "projections": [
    { "period": 0, "customers": 200, "mrr": 12000, "new_customers": 0, "churned_customers": 0 },
    { "period": 1, "customers": 234, "mrr": 14040, "new_customers": 40, "churned_customers": 6 }
  ],
  "assumptions_used": {
    "template": "saas_growth", "starting_customers": "200", "new_customers_per_period": "40",
    "acquisition_growth_rate": "0", "churn_rate": "0.03", "arpu": "60",
    "horizon": 12, "period_label": "month"
  },
  "methodology": {
    "model": "SaaS Growth",
    "primary_output": "ending_mrr",
    "precision": "decimal.js (40 significant digits)",
    "deterministic": true,
    "period_convention": "Period 0 is the starting state; periods 1..12 are projected. 12 month(s) per year."
  },
  "notes": ["Churn is applied to the prior period's base before new customers are added."],
  "explanation": "Starting from 200 customers and adding 40 per month (churn 3%), after 12 months you reach ..."
}

Errors never cross the tool boundary as exceptions — they come back as a structured, actionable envelope:

config.json

{
  "status": "error",
  "error": {
    "type": "unknown_template",
    "message": "Unknown scenario template 'saaas'.",
    "hint": "Available templates: saas_growth, pricing_change, churn_impact, cost_reduction, hiring_plan, cash_runway, unit_economics, marketing_funnel, compound_growth. Call list_templates for details ..."
  }
}

Design note — exact numbers: headline numbers in key_results are deterministically rounded (6 dp) for easy consumption; key_results_detail[].value_exact and assumptions_used carry full-precision strings so no precision is lost in JSON. All internal math is exact 40-digit decimal.

Project structure

Code

scenariosim-mcp/
├── worker-src/
│   ├── index.mjs        # Cloudflare Pages Function (_worker.js): MCP over Streamable HTTP + billing routes
│   ├── engine.mjs       # The deterministic simulation engine: 9 templates + 6 tools + solver + validation
│   └── billing.mjs      # Stripe Checkout + KV-backed API keys, quota metering, webhook
├── server.mjs           # Local stdio MCP server (same engine, no network/state)
├── site/
│   ├── index.html       # Static landing / pricing / docs page
│   ├── mcp.json         # Machine-readable connection manifest
│   ├── llms.txt         # LLM-friendly summary
│   └── _worker.js       # Built bundle (esbuild output; git-ignored)
├── tests/
│   └── engine.test.mjs  # 29 core simulation-logic tests (node --test)
├── examples/
│   └── agent_example.mjs # End-to-end MCP client demo over HTTP
├── package.json         # build / deploy / dev / test scripts
├── wrangler.toml        # Cloudflare Pages config
├── .env.example         # Optional auth/rate-limit env reference
├── LICENSE              # MIT
└── README.md

Requirements

Node 18+ (for the build, tests, and local dev). Only two dev/runtime deps: decimal.js (math) and esbuild (bundler).
A Cloudflare account (free tier is fine) to deploy the hosted version.

Run it locally

bash

git clone <your-fork> scenariosim-mcp && cd scenariosim-mcp
npm install

# Run the test suite (no server needed)
npm test

# Serve the MCP endpoint locally via Wrangler (builds + runs Pages dev)
npm run dev          # -> http://127.0.0.1:8788/mcp

# Try the end-to-end client demo (hosted by default, or pass a local URL)
node examples/agent_example.mjs
node examples/agent_example.mjs http://127.0.0.1:8788

# Or run the dependency-light stdio server directly
node server.mjs

Quick manual call:

Terminal

curl -s http://127.0.0.1:8788/mcp \
  -H 'content-type: application/json' \
  -H 'accept: application/json, text/event-stream' \
  -d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{
        "name":"list_templates","arguments":{}}}'

Install via npm (stdio, no hosting)

Run the server locally over stdio with a single command — nothing to deploy:

Terminal

npx -y scenariosim-mcp

Claude Desktop / any stdio MCP client (claude_desktop_config.json):

config.json

{ "mcpServers": { "scenariosim": { "command": "npx", "args": ["-y", "scenariosim-mcp"] } } }

This is the same deterministic engine as the hosted server, running on your machine.

Client configuration

Cursor — `~/.cursor/mcp.json`

config.json

{ "mcpServers": { "scenariosim": {
    "url": "https://scenariosim-mcp.pages.dev/mcp" } } }

Claude Desktop — `claude_desktop_config.json`

Claude Desktop launches stdio servers, so bridge to the HTTP endpoint with mcp-remote:

config.json

{ "mcpServers": { "scenariosim": {
    "command": "npx", "args": ["-y", "mcp-remote", "https://scenariosim-mcp.pages.dev/mcp"] } } }

VS Code — `.vscode/mcp.json`

config.json

{ "servers": { "scenariosim": {
    "type": "http", "url": "https://scenariosim-mcp.pages.dev/mcp" } } }

Read the full README →View source on GitHub →

Related MCP Servers

View all in Developer Tools View all alternatives

Reviews

No reviews yet — be the first to share how this listing worked for you.

Frequently Asked Questions about Scenariosim MCP

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "scenariosim-mcp": { "command": "npx", "args": ["-y", "scenariosim-mcp"] } }

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Technical Specs & Signals

CategoryDeveloper Tools

36Quality signal: Fair · 36/100How this signal is calculated ▾

Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20

Documentation & tools16/30

Adoption & activity1/15

Community engagement0/10

★ Featured

AllMCPs Server

Explore Server →

Own this project?

Free dofollow backlink: add your website and place the AllMCPs badge on it — no claim needed. We detect it automatically and keep it verified as long as the badge stays live.

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More in 💻 Developer Tools →Best MCP servers for Developers →Alternatives to Scenariosim MCP →Install in Claude Desktop Install in Cursor Install in VS Code

Scenariosim MCP

Quick Install

Client Config & Setup

Documentation Overview

ScenarioSim MCP

🌐 Live hosted server (free, no install)

What it does

Scenario templates

Consistent response envelope

Project structure

Requirements

Run it locally

Install via npm (stdio, no hosting)

Client configuration

Cursor — ~/.cursor/mcp.json

Claude Desktop — claude_desktop_config.json

VS Code — .vscode/mcp.json

Related MCP Servers

Reviews

Frequently Asked Questions about Scenariosim MCP

AllMCPs Directory Badge

Technical Specs & Signals

AllMCPs Server

Own this project?

Share & Embed

Explore more

Scenariosim MCP

Quick Install

Client Config & Setup

Documentation Overview

ScenarioSim MCP

🌐 Live hosted server (free, no install)

What it does

Scenario templates

Consistent response envelope

Project structure

Requirements

Run it locally

Install via npm (stdio, no hosting)

Client configuration

Cursor — ~/.cursor/mcp.json

Claude Desktop — claude_desktop_config.json

VS Code — .vscode/mcp.json

Related MCP Servers

Reviews

Frequently Asked Questions about Scenariosim MCP

AllMCPs Directory Badge

Technical Specs & Signals

AllMCPs Server

Own this project?

Share & Embed

Explore more

Cursor — `~/.cursor/mcp.json`

Claude Desktop — `claude_desktop_config.json`

VS Code — `.vscode/mcp.json`

Cursor — `~/.cursor/mcp.json`

Claude Desktop — `claude_desktop_config.json`

VS Code — `.vscode/mcp.json`