AgentStack MCP: one deterministic reasoning stack for AI agents (simulate + decide + compute)

The fourth in a suite of deterministic MCP servers for AI agents — and the one that ties the first three together.

Over the last stretch I shipped three focused, deterministic MCP servers:

They're great on their own, but agents kept needing all three in the same task — and installing three servers, juggling three keys, and hand-gluing their outputs is friction. So here's AgentStack MCP: one endpoint, one key, all three — plus composite tools that chain them.

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

Free tier: no key, 20 calls/day. The tools are namespaced so an agent always knows which engine it's calling:

sim_*

— ScenarioSim (run, sensitivity, break-even, compare, templates)decide_*

— DecisionMatrix (decide, score, sensitivity, compare_two, methods)calc_*

— PrecisionCalc (metrics, currency, NPV, IRR, loan, depreciation, …)These chain the engines to do reasoning no single server can, deterministically end-to-end:

** evaluate_options_with_scenarios** (simulate → decide) — project each option as its own scenario, then rank the

{ "name": "evaluate_options_with_scenarios", "arguments": {
  "template": "saas_growth", "horizon": 12,
  "options": [
    { "name": "Aggressive", "inputs": { "new_customers_per_period": 60, "churn_rate": 0.05 } },
    { "name": "Lean",       "inputs": { "new_customers_per_period": 20, "churn_rate": 0.02 } }
  ],
  "criteria": [
    { "metric": "ending_mrr", "weight": 3, "direction": "benefit" },
    { "metric": "total_churned_customers", "weight": 1, "direction": "cost" }
  ]
} }

** plan_to_valuation** (simulate → compute) — project a plan, then value its cash-flow line: NPV, IRR, undiscounted total.

** stress_test_decision** (simulate × decide) — stress one scenario assumption across every option and report how often the chosen option survives (robustness) and where it flips.

Bundling 24 tools risks drowning an agent's tool-selection. So the endpoint takes a ?profile=

filter:

https://agentstack-mcp.pages.dev/mcp?profile=finance

finance

→ calc_*

• plan_to_valuation

decision

→ decide_*

• the two decision compositessimulation

→ sim_*

• all compositesall

(default) → everythingio.github.inity13/agentstack-mcp

If your agents plan, choose, and do the numbers, give them one calculator that does all three — and never drifts. Feedback welcome.