MCP server

Scenariosim

io.github.inity13/scenariosim-mcp

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

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

Source

At a glance

Type

MCP server

Publisher

Not verified

Status

Working at last check

Tools

6

Token cost

About 2,864 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http scenariosim-mcp https://scenariosim-mcp.pages.dev/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.scenariosim-mcp]
url = "https://scenariosim-mcp.pages.dev/mcp"

Gemini CLI

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

Cursor

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

VS Code

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

Antigravity

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

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"scenariosim-mcp","server_url":"https://scenariosim-mcp.pages.dev/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"scenariosim-mcp","server_url":"https://scenariosim-mcp.pages.dev/mcp"}

Tools

• break_even ~577 tokens
  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 sea
• compare_scenarios ~765 tokens
  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 'g
• health_check ~55 tokens
  Server health, version, and capabilities (tools, templates, period labels, max horizon). No parameters.
• list_templates ~105 tokens
  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.
• run_scenario ~593 tokens
  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, headli
• sensitivity_analysis ~769 tokens
  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

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• GitHub and code hosting

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