Ermöglicht KI-Agenten deterministisches Reasoning durch Szenario-Simulationen, Multi-Kriterien-Entscheidungsanalysen und hochpräzise Finanzberechnungen.
Auch bekannt als inity13/agentstack-mcp
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- Neueste Version
- 1.0.1
- Letzter Commit
- 20. Okt. 2026
- Lizenz
- MIT
Was ist AgentStack MCP?
AgentStack ist ein MCP server. Ermöglicht KI-Agenten deterministisches Reasoning durch Szenario-Simulationen, Multi-Kriterien-Entscheidungsanalysen und hochpräzise Finanzberechnungen. Er stellt 6 Tools bereit, etwa plan_to_valuation, evaluate_options_with_scenarios, stress_test_decision.
Zusammenfassung generiert aus dem README des Projekts
Über AgentStack MCP server
AgentStack MCP bietet einen einheitlichen Reasoning-Stack für KI-Agenten, um deterministische Simulationen, Multi-Kriterien-Entscheidungsanalysen und hochpräzise Finanzmathematik durchzuführen. Er bündelt drei spezialisierte Engines – ScenarioSim, DecisionMatrix und PrecisionCalc – in einem einzigen Endpoint. Das erlaubt es Agenten, komplexe Reasoning-Pipelines auszuführen, wie etwa die Projektion von Business-Szenarien und die sofortige Berechnung des Kapitalwerts oder des internen Zinsfußes, ohne die Latenz mehrerer separater Verbindungen.
Entwickler können diesen Server lokal via stdio über npx nutzen oder sich mit einer gehosteten Version via HTTP verbinden. Der Hosted-Service bietet einen Free Tier mit einem Limit von 20 Aufrufen pro Tag und IP, während kostenpflichtige Pläne höhere tägliche Quoten über einen API-Key bereitstellen. Das System nutzt decimal.js, um eine Präzision von 40 Stellen beizubehalten, wodurch sichergestellt wird, dass mathematische Outputs bei identischen Inputs byte-identisch bleiben. Nutzer können zudem spezifische Profile wie finance, decision oder simulation laden, um das verfügbare Toolset einzuschränken und Rauschen zu reduzieren.
Was du damit machen kannst
- 1Strategische Optionen bewertenEin Agent kann verschiedene Business-Optionen vergleichen, indem er deren Ergebnisse simuliert und sie anhand gewichteter Kriterien rankt.
- 2Stresstests durchführenEin Agent kann testen, wie sensibel eine Entscheidung auf Änderungen reagiert, indem er eine spezifische Annahme über alle verfügbaren Optionen hinweg variiert.
Geschrieben aus dem README des Projekts. Jeder Use Case wurde gegen ein Zitat daraus geprüft.
So installierst du AgentStack MCP
Formate geprüft am 10. Nov. 2026AgentStack MCP in Claude Code installieren
$ claude mcp add agentstack-mcp -- npx -y agentstack-mcpAgentStack MCP in Cursor installieren
~/.cursor/mcp.json
{
"mcpServers": {
"agentstack-mcp": {
"command": "npx",
"args": [
"-y",
"agentstack-mcp"
]
}
}
}AgentStack MCP in VS Code installieren
.vscode/mcp.json
{
"servers": {
"agentstack-mcp": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"agentstack-mcp"
]
}
}
}AgentStack MCP in Claude Desktop installieren
claude_desktop_config.json
{
"mcpServers": {
"agentstack-mcp": {
"command": "npx",
"args": [
"-y",
"agentstack-mcp"
]
}
}
}AgentStack MCP in Codex installieren
~/.codex/config.toml
[mcp_servers.agentstack-mcp] command = "npx" args = ["-y", "agentstack-mcp"]
AgentStack MCP in Gemini CLI installieren
~/.gemini/settings.json
{
"mcpServers": {
"agentstack-mcp": {
"command": "npx",
"args": [
"-y",
"agentstack-mcp"
]
}
}
}AgentStack MCP tools 6
Erkannt aus dem READMEplan_to_valuationevaluate_options_with_scenariosstress_test_decisionfinancedecisionsimulation
| plan_to_valuation | — | |
| evaluate_options_with_scenarios | — | |
| stress_test_decision | — | |
| finance | — | |
| decision | — | |
| simulation | — |
Automatisierte Checks
Geluften am 13. Nov. 2026Vollständiger Bericht →Unsere automatisierten Checks bestanden. Das ist kein Security-Audit: Lies den Code und gib dem Server nur den minimal notwendigen Zugriff. Wie die Checks funktionieren
- Source Repository verknüpft und erreichbarinity13/agentstack-mcp is public and reachablegithub.com/inity13/agentstack-mcp ↗Bestanden
- Paket nennt dieses Repository als Quelleagentstack-mcp names inity13/agentstack-mcp as sourcenpmjs.com/package/agentstack-mcp ↗Bestanden
- Build-Herkunft (Sigstore-Attestierung)No build attestation published for this releaseNicht geprüft
- Open Source Lizenz (OSI)MITspdx.org/licenses/MIT.html ↗Bestanden
- Commit oder Release im letzten JahrLast commit or release 2026-10-20github.com/inity13/agentstack-mcp ↗Bestanden
- OpenSSF ScorecardNicht geprüft
- Package-Name ähnelt keinem populären PackageNo popular package one edit away from agentstack-mcpBestanden
- Kein kritischer Hinweis im Paket oder seinen Abhängigkeiten2 resolved dependencies checked; no critical advisoryosv.dev ↗Bestanden
- Keine versteckten Anweisungen an das Modell6 tool descriptions and the README read; no override phrases, credential paths or hidden charactersBestanden
- Destruktive Tools sind markiertNo tool named like delete, drop or execBestanden
- Remote-Endpoint beantwortet den MCP-Handshakeinitialize answered with protocol 2025-06-18 in 67 msBestanden
README
Auf GitHub ansehenAgentStack MCP
One deterministic reasoning stack for AI agents — behind a single Model Context Protocol (MCP) endpoint and one API key:
simulate (ScenarioSim) → decide (DecisionMatrix) → compute (PrecisionCalc)
plus cross-domain composite tools that chain the three. Every number runs
through decimal.js at 40-digit precision
(never floats), so identical inputs always produce byte-identical output.
The server is stateless — no database, no sessions.
AgentStack bundles three standalone MCP servers so an agent installs one server, uses one key, and can run reasoning that spans all three domains. It imports the same engines directly (no HTTP proxying) — zero added latency, no cascading failure.
🌐 Live hosted server (free, no install)
https://agentstack-mcp.pages.dev/mcp
{ "mcpServers": { "agentstack": {
"type": "http", "url": "https://agentstack-mcp.pages.dev/mcp" } } }
Free tier: no key, 20 calls/day per IP. Paid plans (Starter $19/mo · 8,000/day,
Pro $59/mo · 80,000/day) return an API key sent as X-API-Key. One key covers
all three products and the composites — about half the cost of subscribing to them
separately. Landing page: https://agentstack-mcp.pages.dev.
The three namespaces (24 tools)
| namespace | engine | tools |
|---|---|---|
sim_* |
ScenarioSim — what-if / scenario simulation | sim_run, sim_sensitivity, sim_break_even, sim_compare, sim_list_templates |
decide_* |
DecisionMatrix — multi-criteria decision analysis | decide, decide_score, decide_sensitivity, decide_compare_two, decide_list_methods |
calc_* |
PrecisionCalc — exact finance/business math | calc_metric, calc_list_metrics, calc_currency_convert, calc_business_days, calc_compound_growth, calc_npv, calc_irr, calc_loan_amortization, calc_depreciation |
| meta | — | list_capabilities, health_check |
Note on two deliberately-namespaced collisions:
sim_sensitivityvaries scenario inputs;decide_sensitivityvaries criteria weights. They are different operations — the prefix disambiguates them for the agent.
Composite tools — the reason to use the stack
Deterministic end-to-end; each chains engines that no single server bundles:
| Tool | Pipeline | What it does |
|---|---|---|
plan_to_valuation |
simulate → compute | Project a scenario, take a per-period cash-flow line (cashflow_metric), and value it: NPV at a discount rate, IRR, undiscounted total. initial_investment becomes the period-0 outflow (needed for IRR). |
evaluate_options_with_scenarios |
simulate → decide | Project each option as its own scenario, then rank the options against weighted criteria drawn from the scenario outcomes (key_results). |
stress_test_decision |
simulate × decide | Stress one scenario assumption across every option and report how often the baseline winner survives (robustness) and where it flips. |
Composite responses report the pipeline they ran and carry each stage's
structured output, so an agent can drill into any step.
Profiles — fight tool-selection noise
Append ?profile= to the endpoint to load only a subset:
| profile | tools |
|---|---|
all (default) |
every tool (24) |
finance |
calc_* + plan_to_valuation + meta |
decision |
decide_* + evaluate_options_with_scenarios + stress_test_decision + meta |
simulation |
sim_* + all composites + meta |
{ "mcpServers": { "agentstack": {
"url": "https://agentstack-mcp.pages.dev/mcp?profile=finance" } } }
Response envelope
Namespaced tools return the exact envelope of their underlying product. Composite
tools add composite, pipeline, per-stage blocks, methodology, notes, and a
plain-language explanation. Errors are always structured data:
{ "status": "error", "error": { "type": "unknown_metric", "message": "...", "hint": "..." } }
Example — plan_to_valuation (trimmed):
{
"status": "success",
"composite": "plan_to_valuation",
"pipeline": ["scenariosim.run_scenario", "precisioncalc.net_present_value", "precisioncalc.internal_rate_of_return"],
"scenario": { "template": "saas_growth", "horizon": 12, "key_results": { "ending_mrr": 26982.1 } },
"cashflow_metric": "mrr",
"cashflows": [-150000, 14040, 15600, "..."],
"valuation": { "discount_rate": 0.01, "npv": 11157.386023, "irr": 0.02504, "value_creating": true },
"explanation": "Projecting 'saas_growth' over 12 month(s) and valuing the 'mrr' stream at 1%/period gives an NPV of ..."
}
Project structure
agentstack-mcp/
├── worker-src/
│ ├── index.mjs # Cloudflare Pages Function: MCP transport, namespacing, profiles, billing
│ ├── composites.mjs # the 3 cross-domain tools (simulate -> decide -> compute)
│ ├── billing.mjs # Stripe + KV: one key / one quota for the whole stack
│ └── engines/ # vendored, unmodified product engines (100% deterministic)
│ ├── scenariosim.mjs
│ ├── decisionmatrix.mjs
│ └── precisioncalc.mjs
├── server.mjs # local stdio MCP server (same engines + composites; AGENTSTACK_PROFILE env)
├── site/ # landing page + mcp.json + llms.txt + _worker.js (built)
├── tests/composites.test.mjs
├── examples/agent_example.mjs
├── scripts/sync-engines.sh # re-vendor engines from the sibling repos
├── package.json · wrangler.toml · server.json · smithery.yaml · Dockerfile · LICENSE
└── README.md
Why vendor the engines? So this repo is self-contained and reproducible. The
engines are the same deterministic modules that power the three standalone
servers; npm run sync-engines re-copies them from the sibling repos when an
upstream change lands.
Run it locally
git clone <your-fork> agentstack-mcp && cd agentstack-mcp
npm install
npm test # composite-logic tests (no network)
npm run dev # -> http://127.0.0.1:8788/mcp
node examples/agent_example.mjs # hosted demo
node examples/agent_example.mjs http://127.0.0.1:8788
node server.mjs # dependency-light stdio server (AGENTSTACK_PROFILE=finance to subset)
Quick manual call:
curl -s http://127.0.0.1:8788/mcp \
-H 'content-type: application/json' -H 'accept: application/json, text/event-stream' \
-d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"list_capabilities","arguments":{}}}'
Install via npm (stdio, no hosting)
Run the server locally over stdio with a single command — nothing to deploy:
npx -y agentstack-mcp
Claude Desktop / any stdio MCP client (claude_desktop_config.json):
{ "mcpServers": { "agentstack": { "command": "npx", "args": ["-y", "agentstack-mcp"] } } }
This is the same deterministic engine as the hosted server, running on your machine.
Client configuration
Cursor — ~/.cursor/mcp.json
{ "mcpServers": { "agentstack": { "url": "https://agentstack-mcp.pages.dev/mcp" } } }
Claude Desktop — claude_desktop_config.json (via mcp-remote)
{ "mcpServers": { "agentstack": { "command": "npx", "args": ["-y", "mcp-remote", "https://agentstack-mcp.pages.dev/mcp"] } } }
VS Code — .vscode/mcp.json
{ "servers": { "agentstack": { "type": "http", "url": "https://agentstack-mcp.pages.dev/mcp" } } }
Windsurf — ~/.codeium/windsurf/mcp_config.json
{ "mcpServers": { "agentstack": { "serverUrl": "https://agentstack-mcp.pages.dev/mcp" } } }
Add "headers": { "X-API-Key": "ssak_live_..." } once you have a key.
Example composite payloads
Rank growth strategies on their projected outcomes:
{ "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" }
]
} }
Value a plan's MRR stream:
{ "name": "plan_to_valuation", "arguments": {
"template": "saas_growth", "horizon": 12,
"inputs": { "new_customers_per_period": 60, "churn_rate": 0.05, "arpu": 60 },
"cashflow_metric": "mrr", "rate": 0.01, "initial_investment": 150000
} }
Stress-test the decision:
{ "name": "stress_test_decision", "arguments": {
"template": "saas_growth", "horizon": 12,
"options": [ { "name": "Aggressive", "inputs": { "churn_rate": 0.05 } },
{ "name": "Lean", "inputs": { "churn_rate": 0.02 } } ],
"criteria": [ { "metric": "ending_mrr", "weight": 3 } ],
"stress": { "variable": "churn_rate", "variation": 0.5, "steps": 5 }
} }
Deploy on Cloudflare Pages
npm install
npx wrangler login
npm run deploy # esbuild -> site/_worker.js, then wrangler pages deploy
Runs fully free / private with no bindings or secrets (fails open on the free
tier). For billing: bind a KV namespace AGENTSTACK_KV, set PRICE_STARTER /
PRICE_PRO in [vars], and add Stripe secrets:
wrangler pages secret put STRIPE_SECRET_KEY --project-name agentstack-mcp
wrangler pages secret put STRIPE_WEBHOOK_SECRET --project-name agentstack-mcp
Routes: /mcp (Streamable HTTP), /checkout, /success, /portal, /webhook, /metrics.
Auth & rate limiting
Enforced in worker-src/billing.mjs: identify() reads X-API-Key /
Authorization: Bearer and falls back to per-IP free tier; consumeQuota() is a
KV daily counter (the single gating point). One key / one quota spans the whole
stack. Marked NOTE (auth) / NOTE (rate limiting) seams show where to swap in
JWT/mTLS or a token-bucket. None of it touches the deterministic math.
Relationship to the standalone servers
AgentStack is additive, not a replacement. The three products keep running on their own for single-domain use:
- ScenarioSim — https://scenariosim-mcp.pages.dev/mcp
- DecisionMatrix — https://decisionmatrix-mcp.pages.dev/mcp
- PrecisionCalc — https://precisioncalc-mcp.pages.dev/mcp
License
MIT — see LICENSE.
AgentStack MCP Fragen
Wie füge ich AgentStack MCP zu Claude Code hinzu?
Führe claude mcp add agentstack-mcp -- npx -y agentstack-mcp in deinem Terminal aus. Füge --scope user hinzu, damit der Server in jedem Projekt verfügbar ist.
Wie füge ich AgentStack MCP zu Cursor hinzu?
Öffne ~/.cursor/mcp.json und füge den Server unter mcpServers hinzu, mit der Cursor-Config aus dem Installationsabschnitt oben.
Welche Tools bietet AgentStack MCP?
Er stellt 6 Tools bereit, darunter plan_to_valuation, evaluate_options_with_scenarios, stress_test_decision, finance, decision.
Speichert der Server Daten oder Nutzersitzungen?
Nein, der Server ist zustandslos und verwendet keine Datenbank oder Sitzungsverwaltung.
Kann ich die für den Agenten verfügbaren Tools einschränken?
Ja, du kannst Profile nutzen, um spezifische Subsets von Tools wie finance, decision oder simulation zu laden.
Gibt es eine kostenlose Version?
Ja, es gibt einen Free Tier, der 20 Aufrufe pro Tag und IP ohne API-Key ermöglicht.