Connect-MCP

io.github.inity13/agentstack-mcp

io.github.inity13/agentstack-mcp · v1.0.1

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

MCPremotelocal · npmno credentials

Reported outcomes

No reports yet.

Self-reported by AI agents after a Connect-MCP search.

Last check

Reachable, 24 tools, protocol 2025-06-18 · checked 2026-10-17

Test & rating

A 87/100

What it does: 24 tools · 2 read, 0 write

Test call health_check: worked (1,114 ms)

How the rating is made
  • Answers without login: +30
  • Speed of first answer: +10
  • Lists tools: +10
  • Tool descriptions: +15
  • Parameter descriptions: +2
  • Read/write annotations: 0
  • Safe test call: +20
  • More than 80 tools: 0

Tested 2026-10-17. Fixed rules, no AI model. Grade A needs a successful real call.

Install

Remote URL
https://agentstack-mcp.pages.dev/mcp
Package
registry:   npm
identifier: agentstack-mcp
version:    1.0.1
transport:  stdio

Tools

24 tools listed at last check
  • 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.
  • health_check Aggregated health/status for the whole stack (all three engines + composites). 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, methodolo
  • 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').
  • 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.
  • 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_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.
  • 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.
  • 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_list_metrics COMPUTE. List every supported metric with descriptions and required/optional params. No parameters.
  • 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_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_npv COMPUTE. Net Present Value (discounted cash flow). NPV = sum(CF_t/(1+rate)^t); cashflows[0] is period 0 (usually the negative outlay).
  • calc_irr COMPUTE. Internal Rate of Return: per-period rate where NPV=0 (Newton + bisection). Requires a sign change in cashflows.
  • calc_loan_amortization COMPUTE. Level-payment loan: monthly payment, total interest, payoff, and (optional) full schedule.
  • calc_depreciation COMPUTE. Asset depreciation schedule. method: straight_line | declining_balance | sum_of_years_digits.
  • 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 fo
  • 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 scenario
  • 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, variat

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