nephyr-backtest
MCP ServerFreeStrategy backtesting with real on-chain Polymarket data. Backtest weather-based prediction market strategies, simulate copy-trading top wallets, and query available historical data. Validate your strategies against real market outcomes before risking capital.
Capabilities3 decomposed
real-time market data querying
Medium confidenceThis capability allows users to query historical Polymarket data in real-time, leveraging a direct integration with on-chain data sources. It employs a caching mechanism to optimize data retrieval speeds and reduce API call frequency, ensuring that users can access the most relevant market information without unnecessary delays. The architecture supports both RESTful and WebSocket connections for flexible data access patterns.
Utilizes a hybrid caching strategy that combines in-memory storage with on-chain data retrieval for improved speed and efficiency.
Faster data retrieval than traditional REST APIs by minimizing redundant calls through effective caching.
strategy simulation for copy-trading
Medium confidenceThis capability enables users to simulate copy-trading strategies based on the performance of top wallets in the Polymarket ecosystem. It uses historical transaction data to model potential outcomes and provides a user-friendly interface for adjusting parameters such as investment size and risk tolerance. The simulation engine is built on a robust event-driven architecture that processes historical data in real-time to generate accurate forecasts.
Employs an event-driven model to simulate trading scenarios dynamically, allowing for real-time adjustments based on user-defined parameters.
More accurate simulations than static models due to real-time data processing and event-driven architecture.
weather-based prediction strategy backtesting
Medium confidenceThis capability allows users to backtest weather-based prediction market strategies using real historical data. It integrates a comprehensive analytics engine that evaluates various strategies against actual market outcomes, providing detailed reports on performance metrics such as accuracy and profitability. The architecture supports modular strategy definitions, enabling users to easily plug in new algorithms for testing.
Features a modular architecture that allows users to define and test various prediction strategies dynamically, enhancing flexibility in backtesting.
Offers more granular performance metrics and customizable strategy definitions compared to traditional backtesting tools.
Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.
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Best For
- ✓traders analyzing market trends in real-time
- ✓investors looking to validate trading strategies without financial risk
- ✓data scientists developing predictive models for weather markets
Known Limitations
- ⚠Limited to Polymarket data; other sources not supported
- ⚠Rate limits apply based on API usage
- ⚠Simulations are based on historical data and may not predict future performance accurately
- ⚠Requires understanding of market dynamics for effective use
- ⚠Limited to weather-based strategies; other types not supported
- ⚠Requires significant historical data for meaningful results
Requirements
Input / Output
UnfragileRank
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About
Strategy backtesting with real on-chain Polymarket data. Backtest weather-based prediction market strategies, simulate copy-trading top wallets, and query available historical data. Validate your strategies against real market outcomes before risking capital.
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