AIAgentwithPineScript
MCP ServerFreetv-pinescript-backtest-mcp exposes a remote MCP endpoint so agents can: run strategy backtests by symbol/timeframe/date range, pass strategy inputs programmatically, receive structured backtest results (trades, win rate, profit, drawdown), keep long-running runs observable via progress notification
Capabilities5 decomposed
remote strategy backtesting execution
Medium confidenceThis capability allows users to execute strategy backtests remotely by specifying a symbol, timeframe, and date range. It utilizes a Model Context Protocol (MCP) to communicate with the backtest engine, ensuring that the requests and responses are structured and consistent. The architecture is designed to handle multiple backtest requests while enforcing rate limits, making it efficient for users who need to test various strategies in a timely manner.
The use of a remote MCP endpoint allows for seamless integration with various trading strategies without requiring local execution, providing flexibility and scalability.
More efficient than local backtesting tools as it allows for concurrent execution of multiple strategies without local resource constraints.
programmatic strategy input passing
Medium confidenceThis capability enables users to programmatically pass strategy inputs to the backtest engine, allowing for dynamic adjustments and testing of different parameters. It leverages structured data formats to ensure that inputs are correctly interpreted by the engine, facilitating a smooth integration with automated trading systems. This design choice enhances the flexibility and usability of the backtesting process.
Supports dynamic parameter passing through structured data, allowing for real-time adjustments during backtesting, which is not commonly found in traditional backtesting tools.
More versatile than static input methods, enabling rapid iteration and testing of strategies without manual intervention.
structured backtest results retrieval
Medium confidenceThis capability provides users with structured backtest results, including detailed metrics such as trades, win rate, profit, and drawdown. The results are formatted in a way that allows for easy interpretation and further analysis, supporting decision-making processes. The architecture ensures that results are consistently formatted and can be easily integrated into reporting tools or dashboards.
Delivers results in a structured format that is consistent across different backtests, making it easier to compare and analyze performance metrics.
More comprehensive than basic logging tools, providing detailed performance insights that are ready for analysis.
progress notification for long-running backtests
Medium confidenceThis capability keeps users informed about the progress of long-running backtests through real-time notifications. It employs a notification system that updates users on the status of their backtests, allowing them to monitor performance without needing to manually check the results. This feature is particularly useful for extensive backtesting scenarios where wait times can be significant.
Utilizes a dedicated notification system that provides real-time updates on backtest progress, enhancing user experience during lengthy operations.
More user-friendly than traditional backtesting interfaces that require manual refreshes to check status.
strategy writing assistance
Medium confidenceThis capability allows users to request the agent to write a trading strategy based on specified criteria. It uses natural language processing to interpret user requests and generate PineScript code that aligns with the user's trading objectives. This feature streamlines the strategy development process, making it accessible even to those with limited coding experience.
Incorporates NLP to understand user requests and generate relevant PineScript code, making strategy development more intuitive for non-coders.
More accessible than traditional coding environments, enabling users to create strategies without deep programming knowledge.
Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.
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Best For
- ✓traders looking to automate backtesting of their PineScript strategies
- ✓developers creating automated trading systems
- ✓traders and analysts needing detailed performance metrics
- ✓traders running extensive backtests requiring long processing times
- ✓traders without coding skills looking to automate their strategies
Known Limitations
- ⚠Only supports Binance Futures tickers; other markets are not available.
- ⚠Enforces a maximum of 1440 candles per backtest, limiting the depth of historical analysis.
- ⚠Requires structured input formats; free-text inputs may not be supported.
- ⚠Limited to the parameters defined within the PineScript strategies.
- ⚠Results are limited to the metrics defined by the backtest engine; custom metrics may not be available.
- ⚠Requires parsing of structured data to extract meaningful insights.
Requirements
Input / Output
UnfragileRank
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About
tv-pinescript-backtest-mcp exposes a remote MCP endpoint so agents can: run strategy backtests by symbol/timeframe/date range, pass strategy inputs programmatically, receive structured backtest results (trades, win rate, profit, drawdown), keep long-running runs observable via progress notifications, support Binance Futures tickers only, enforce a maximum of 1440 candles per backtest, apply a rate limit of 3 backtests per minute per user, ask your agent to write a strategy and backtest it. Troubleshooting The backtest-engine server has been tested on 30 strategies and tuned to match TradingView backtests 1:1 as closely as possible. Some operators may still be unsupported. If you hit this case, please create a minimal strategy that reproduces the issue and submit it in Issues. We will do our best to add support quickly. https://backtest-engine-mcp.click/ https://github.com/vtlk/tv-pinescript-backtest-engine-mcp
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