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Prisoner Dilemma Simulator MCP
x402
Prisoner Dilemma Simulator MCP is a paid API for AI agents from api.m2mcent.com, paid per call via x402, $0.3/call, status unknown (last checked 2026-10-18).
Simulates prisoner's dilemma game theory scenarios, computing strategies, payoffs, and equilibrium outcomes for cooperative and competitive agent interactions.
Price / call$0.3
Success—
StatusUnknown
How this service works
The premier global index of 1,069 monetized MCP nodes across 205 specialized subdomains. Gasless USDC runtime settlements via x402 V2 Spec on Base L2. Save 95% token context.
Output
Returns simulation results including per-round outcomes, player payoffs, strategy evaluations, equilibrium analysis, and summary statistics on cooperation rates and total scores.
Example use cases
Testing AI cooperation strategies
“Run a prisoner's dilemma simulation where one agent always cooperates and the other uses a random strategy over 10 rounds — I want to see the total payoffs and which strategy wins.”
Classroom game theory demonstration
“Simulate a classic single-round prisoner's dilemma with the standard payoff matrix — both defect gets 1 each, both cooperate gets 3 each, one defects gets 5 while the other gets 0 — and explain the Nash equilibrium outcome.”
Evaluating iterated defection vs cooperation
“Can you model an iterated prisoner's dilemma over 20 rounds comparing a pure defection strategy against a tit-for-tat strategy and show me the cumulative payoffs and cooperation rate?”
Technical details
Endpoint
POSThttps://api.m2mcent.com/prisoner-dilemma-simulator-mcp/api/process?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to run game theory simulations specifically modeled on the prisoner's dilemma framework, especially for multi-agent cooperation research, AI strategy testing, or educational demonstrations. Prefer it over general optimization or decision engines when the scenario involves exactly two players, defined payoff matrices, and iterated or single-shot defect/cooperate choices.
Side effects
- Malformed or missing 'data' string field returns a 400 error
- Ambiguous or unparseable scenario description may yield unexpected simulation parameters
- Payment failure (402) if USDC is not supplied or insufficient
- Timeout if scenario complexity is too high for synchronous processing
Output
Schema · Response
{
"type": "json",
"example": {
"success": true
}
}Tags
x402
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