Scenariosim MCP
Deterministic what-if & scenario simulation for AI agents: projections, sensitivity & break-even.
Connector by inity13 · GitHub account verified by the MCP Registry
Chalk Labs
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Install
Works with Claude Code, VS Code, Codex, Cursor, Windsurf, Claude Desktop. Read the repository before you give any tool access to your data.
npx agentmarket install connector/inity13-scenariosim-mcp
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
Remote endpoint
https://scenariosim-mcp.pages.dev/mcpRemote (HTTP)
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About
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this server can do and what it asks for, from its tool list, install config and code. Checked Oct 26, 2026.
- Tools
- 2 read · 1 write · 0 delete · 3 not yet classified
- Secrets
- None asked for
- Install scripts
- None found
- Runs as
- Node.js package
Tools by what they do 6
From the running server's own tool list (tools/list) on Oct 25, 2026.
Read 2 · Look things up without changing anything.
health_checklist_templates
Write 1 · Create, change, send or run things.
run_scenario
Not yet classified 3 · We could not tell from the name and description.
break_evencompare_scenariossensitivity_analysis
Network hosts it talks to 4
api.stripe.com· found in codegithub.com· found in codeglama.ai· found in codescenariosim-mcp.pages.dev· found in remote endpoint, install command, code
Tools (6)
As the server listed them on Oct 25, 2026. Descriptions are the server’s own words; hidden characters are shown as [U+…].
break_evenSolve 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.
compare_scenariosRun 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.
health_checkServer health, version, and capabilities (tools, templates, period labels, max horizon). No parameters.
list_templatesDiscovery 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_scenarioMain 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).
sensitivity_analysisVary 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.
Signals
- Stars
- 1
- Forks
- 0
- Open issues
- 1
- Last commit
- Oct 20, 2026 (17 days ago)
- Last release
- Aug 12, 2026 (2 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- Registry name
io.github.inity13/scenariosim-mcp- Version
- 1.0.2
- Auth
- Auth not stated
- Packages
- npm scenariosim-mcp
- License
- MIT
- Repository
- github.com/inity13/scenariosim-mcp
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
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Cite this page
Scenariosim MCP. Agent Mart. https://agentmart.dev/connectors/inity13-scenariosim-mcp (last updated 2026-10-24)