MCP For Claude Marketplace
Gacha Pity Simulator

Gacha Pity Simulator MCP Connector for Claude

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Analyze gacha mechanics including base rates, soft pity ramps, and hard pity guarantees to predict player costs.

3 tools Official Updated Jun 28, 2026 Official Vinkius Partner
More Details Connect to Claude

The Gacha Pity Simulator is a specialized tool for analyzing the mathematical impact of 'pity' mechanics in gacha games. It allows users to calculate expected pulls, generate probability curves, and estimate budgetary impacts using tools like calculate_pity_metrics, generate_probability_curve, and estimate_budgetary_impact. By simulating base rates, soft pity thresholds, and hard pity limits, players and developers can understand the true cost of obtaining rare items and identify worst-case scenarios based on specific percentiles.

gachapity-systemprobabilitystatisticsbudgeting

3 tools expose this connector's capabilities to your AI agent.

estimate_budgetary_impact

Estimate the financial cost of gacha pulls

calculate_pity_metrics

Calculate expected pulls with and without pity systems

generate_probability_curve

Generate a cumulative probability curve for gacha pulls

See how to talk to your AI agent using Gacha Pity Simulator.

Calculate the expected pulls for a 1% base rate with soft pity starting at 70 and hard pity at 90, with a 2% increment per pull.

Based on the parameters provided, the expected pulls without pity would be 100, while the expected pulls with the specified pity system is approximately 76.4.

Generate a probability curve for a 2% base rate, soft pity at 50, hard pity at 80, and 1% increment.

The cumulative probability curve shows a steady climb from pull 1, an accelerated increase starting at pull 50, and reaches 100% certainty exactly at pull 80.

If each pull costs 150 gems, how much will it cost me to be 95% sure I get the item using this probability data: [{"pullCount": 1, "cumulativeProbability": 0.02}, {"pullCount": 80, "cumulativeProbability": 1.0}]?

To reach a 95% confidence level, you would need to perform 80 pulls, resulting in an estimated cost of 12,000 gems.

Without pity, the expected number of pulls is simply the inverse of the base rate. With pity, the `calculate_pint_metrics` tool accounts for the increased probability during the soft pity period and the 100% guarantee at hard pity, typically resulting in a much lower average pull count.

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