robonet-workbench
Robonet MCP Integration
Overview
Robonet provides an MCP server that enables AI assistants to build, test, and deploy trading strategies. The server offers 24 tools organized into 6 categories: Data Access (8), AI-Powered Strategy Generation (6), Backtesting (2), Prediction Markets (3), Deployment (4), and Account Management (2).
Quick Start
Load the required MCP tools before using them:
Use MCPSearch to select: mcp__workbench__get_all_symbols
Use MCPSearch to select: mcp__workbench__create_strategy
Use MCPSearch to select: mcp__workbench__run_backtest
After loading, call the tools directly to interact with Robonet.
Tool Categories
More from robonet-tech/skills
trade-prediction-markets
Build and test Polymarket prediction market trading strategies for YES/NO token trading. Provides 6 tools: get_all_prediction_events (browse markets, $0.001), get_prediction_market_data (analyze price history, $0.001), create_prediction_market_strategy (generate code, $1-$4.50), run_prediction_market_backtest (test performance, $0.001). Trade on real-world events (politics, economics, sports, crypto). Currently simulation only (live deployment coming soon).
250build-trading-strategies
AI-powered generation of complete trading strategy code. Uses create_strategy and create_prediction_market_strategy to transform requirements into production-ready Python code. Most expensive AI tool ($1.00-$4.50 per generation). Generates complete Jesse framework strategies with entry/exit logic, position sizing, and risk management. Use after exploring data and optionally generating ideas. ALWAYS test with test-trading-strategies before deploying.
82test-trading-strategies
Backtest trading strategies on historical data and interpret performance metrics. Provides run_backtest (crypto strategies) and run_prediction_market_backtest (Polymarket strategies). Fast execution (20-60s), minimal cost ($0.001). Returns Sharpe ratio, max drawdown, win rate, profit factor, and trade statistics. Use this skill after building or improving strategies to validate performance before deploying. NEVER deploy without thorough backtesting (6+ months recommended).
46improve-trading-strategies
Iterative refinement, parameter optimization, and ML enhancement of existing trading strategies. Provides 3 tools: refine_strategy (targeted code changes, $0.50-$3.00), optimize_strategy (parameter tuning, $2-$4), enhance_with_allora (ML integration, $1-$2.50). More cost-effective than regenerating from scratch. Use when you have working strategies that need improvement. Always test improvements with test-trading-strategies before deploying.
19design-trading-strategies
AI-powered strategy ideation and concept exploration. Generate 1-10 creative trading strategy concepts based on current market data using the generate_ideas tool. Cheapest AI operation ($0.05-$1.00 vs $1-$4.50 for full strategy creation). Use this skill to explore creative concepts before committing to expensive development. Best for: exploring new markets, brainstorming approaches, validating ideas before building.
13browse-robonet-data
Fast, low-cost exploration of Robonet trading resources. Browse 8 data tools to explore available trading pairs, technical indicators, Allora ML topics, existing strategies, and backtest results. All tools execute in <1 second with minimal cost (free to $0.001). Use this skill first before building or testing strategies to understand what resources are available.
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