bots.st/agentstack-mcp

agentstack-mcp

Deterministic finance simulation and option decisions

2595 ms

answered our call 8 Nov, 02:35 UTC

State: Answered
Protocol: MCP 2025-06-18
Tools listed: 24
Answered: 3 of the last 3 calls

How to reach it

MCP, HTTPhttps://agentstack-mcp.pages.dev/mcp
npmnpx -y agentstack-mcpReleased 12 Aug 2026, version 1.0.1

What it can do

Tool	What it says it does
`calc_business_days`	COMPUTE. Business-day arithmetic honoring weekends + regional holidays. operation: add_business_days \| count_business_days \| next_business_day \| previous_business_day. region: US \| UK \| EU \| NONE.
`calc_compound_growth`	COMPUTE. Compound-interest/growth math. operation: future_value \| present_value \| cagr. rate is annual decimal; compounding: daily\|weekly\|monthly\|quarterly\|semiannually\|annually\|continuous.
`calc_currency_convert`	COMPUTE. Convert between major currencies (USD, EUR, GBP, JPY, CAD, AUD, CHF, CNY, INR) with Decimal precision. Static offline table by default; live/historical ECB rates via date/live=true.
`calc_depreciation`	COMPUTE. Asset depreciation schedule. method: straight_line \| declining_balance \| sum_of_years_digits.
`calc_irr`	COMPUTE. Internal Rate of Return: per-period rate where NPV=0 (Newton + bisection). Requires a sign change in cashflows.
`calc_list_metrics`	COMPUTE. List every supported metric with descriptions and required/optional params. No parameters.
`calc_loan_amortization`	COMPUTE. Level-payment loan: monthly payment, total interest, payoff, and (optional) full schedule.
`calc_metric`	COMPUTE. Exact business/SaaS/finance metric: ltv, cac, ltv_cac_ratio, payback_period_months, contribution_margin, gross_margin, churn_rate, mrr_growth_rate, arr, break_even_units, nrr, grr, rule_of_40, magic_number. Rates/margins are decimals (0.05=5%). Call calc_list_metrics for schemas.
`calc_npv`	COMPUTE. Net Present Value (discounted cash flow). NPV = sum(CF_t/(1+rate)^t); cashflows[0] is period 0 (usually the negative outlay).
`decide`	DECIDE. Rank named options against weighted criteria and return the winner, full ranking, per-criterion breakdowns, methodology, weights, and an explanation. Provide options, criteria [{name, weight, direction}], and a scores matrix. method: weighted_sum (default) \| weighted_product \| topsis.
`decide_compare_two`	DECIDE. Head-to-head comparison of exactly two options with per-criterion win counts and margin. Pass option_a/option_b (or a 2-element options array), criteria, and scores.
`decide_list_methods`	DECIDE. List the scoring methods (weighted_sum, weighted_product, topsis) with normalization details and when to use each. No parameters.
`decide_score`	DECIDE. Return the full normalized scored matrix (per-option, per-criterion) + ranking when scores are supplied separately, without the winner narrative.
`decide_sensitivity`	DECIDE. Test how robust the decision winner is to changes in CRITERIA WEIGHTS (distinct from sim_sensitivity, which varies scenario inputs). Sweeps each weight +/-variation and reports a robustness score + flip points.
`evaluate_options_with_scenarios`	COMPOSITE (simulate -> decide). Project each option as its own scenario, then rank the options against weighted criteria drawn from the scenario OUTCOMES. Provide a base 'template', an 'options' array ([{name, inputs}]), and 'criteria' ([{metric, weight, direction}]) where each metric is a…
`health_check`	Aggregated health/status for the whole stack (all three engines + composites). No parameters.
`list_capabilities`	Discovery: the three namespaces (sim_, decide_, calc_*), the cross-domain composite tools, the available ?profile= filters, and links to the standalone servers. Call this first to see everything AgentStack exposes. No parameters.
`plan_to_valuation`	COMPOSITE (simulate -> compute). Project a scenario, take a per-period cash-flow line from its projections ('cashflow_metric', e.g. 'mrr' or 'net_burn'), and value it exactly: NPV at a discount 'rate', IRR, and undiscounted total. Optional 'initial_investment' becomes the period-0 outflow (needed…
`sim_break_even`	SIMULATE. Solve for the scenario input value required to make an output metric hit a target value (deterministic bisection). Requires 'template', 'solve_for', 'target_value'.
`sim_compare`	SIMULATE. Run 2-3 scenarios and compare their key_results side by side with deltas vs the first (baseline). Optional 'compare_metric' + 'goal' (max\|min) picks a winner.
`sim_list_templates`	SIMULATE. List every scenario template (inputs, defaults, outputs) plus the custom-model format and period labels. No parameters.
`sim_run`	SIMULATE. Deterministic what-if projection from a 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 per-period projections, key_results, assumptions_used…
`sim_sensitivity`	SIMULATE. Vary one or more scenario inputs and show the impact on a target output metric (one-at-a-time), with elasticity + most-influential ranking. Requires 'template' and 'variable' (or 'variables').
`stress_test_decision`	COMPOSITE (simulate x decide). Take an options-vs-scenarios decision and stress ONE scenario assumption across a range applied to every option; report how often the baseline winner survives (robustness) and where it flips. Same args as evaluate_options_with_scenarios plus 'stress': {variable…

In its maker's words

Deterministic reasoning stack for AI agents: simulate, decide & compute, plus cross-domain tools.

Source: github.com/inity13/agentstack-mcp
Publisher: inity13 (4 listings in the registry)
Listed from: the official MCP Registry as io.github.inity13/agentstack-mcp
Version: 1.0.1, updated 12 Aug 2026
Kinds of work: Finance and markets, AI models and agent tools

Every call we made

When	What happened	Time
8 Nov, 02:35 UTC	Answered	2595 ms
7 Nov, 23:14 UTC	Answered	2446 ms
7 Nov, 21:32 UTC	Answered	652 ms

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