Robonet

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.

1. Data Access Tools (Fast, <1s execution)

Browse available resources before building strategies: get_all_strategies - List your trading strategies with optional backtest results get_strategy_code - View Python source code of a strategy get_strategy_versions - Track strategy evolution across versions get_all_symbols - List tradeable pairs on Hyperliquid (BTC-USDT, ETH-USDT, etc.) get_all_technical_indicators - Browse 170+ indicators (RSI, MACD, Bollinger Bands, etc.) get_allora_topics - List Allora Network ML prediction topics get_data_availability - Check data ranges before backtesting get_latest_backtest_results - View recent backtest performance Pricing: Most $0.001, some free. Use these liberally to explore. When to use: Start every workflow by checking available symbols, indicators, or existing strategies before generating new code.

2. AI-Powered Strategy Tools (20-60s execution)

Generate and improve trading strategies: generate_ideas - Get AI-generated strategy concepts based on market data create_strategy - Generate complete Python strategy from description optimize_strategy - Tune parameters for better performance enhance_with_allora - Add Allora Network ML predictions to strategy refine_strategy - Make targeted code improvements create_prediction_market_strategy - Generate Polymarket YES/NO trading logic Pricing: Real LLM cost + margin ($0.50-$4.50 typical). These are the most expensive tools. When to use: After understanding available resources, use these to build or improve strategies. Always backtest after generation.

3. Backtesting Tools (20-40s execution)

Test strategy performance on historical data: run_backtest - Test crypto trading strategies run_prediction_market_backtest - Test Polymarket strategies Pricing: $0.001 per backtest Returns: Performance metrics (Sharpe ratio, max drawdown, win rate, total return, profit factor), trade statistics, equity curve data When to use: After creating or modifying a strategy, always backtest before deploying. Use multiple time periods to validate robustness.

4. Prediction Market Tools

Build Polymarket trading strategies: get_all_prediction_events - Browse available prediction markets get_prediction_market_data - Analyze YES/NO token price history create_prediction_market_strategy - Generate Polymarket strategy code Pricing: $0.001 for data tools, Real LLM cost + margin for creation When to use: For prediction market trading strategies on Polymarket (politics, crypto price predictions, economics events)

5. Deployment Tools

Deploy strategies to live trading on Hyperliquid: deployment_create - Launch live trading agent (EOA or Hyperliquid Vault) deployment_list - Monitor active deployments deployment_start - Resume stopped deployment deployment_stop - Halt live trading Pricing: $0.50 to create, free for list/start/stop Constraints: EOA (wallet): Max 1 active deployment per wallet Hyperliquid Vault: Requires 200+ USDC in wallet, unlimited deployments When to use: After thorough backtesting shows positive results. Never deploy without backtesting first.

6. Account Tools

Manage credits and view account info: get_credit_balance - Check available USDC credits get_credit_transactions - View transaction history Pricing: Free When to use: Check balance before expensive operations. Monitor spending via transaction history.

Workflow 1: Create and Test New Strategy

1. get_all_symbols → See available trading pairs 2. get_all_technical_indicators → Browse indicators 3. create_strategy → Generate Python code from description 4. run_backtest → Test on 6+ months of data 5. If promising: optimize_strategy → Tune parameters 6. If excellent: enhance_with_allora → Add ML signals 7. run_backtest → Validate improvements 8. If ready: deployment_create → Deploy to live trading Cost: ~$1-5 depending on optimization and enhancement

Workflow 2: Enhance Existing Strategy

1. get_all_strategies (include_latest_backtest=true) → Find strategy 2. get_strategy_code → Review implementation 3. refine_strategy (mode="new") → Make targeted improvements 4. run_backtest → Test changes 5. If better: enhance_with_allora → Add ML predictions 6. run_backtest → Final validation Cost: ~$0.50-2.00

Workflow 3: Prediction Market Trading

1. get_all_prediction_events → Browse markets 2. get_prediction_market_data → Analyze price history 3. create_prediction_market_strategy → Build YES/NO logic 4. run_prediction_market_backtest → Test performance 5. If profitable: deployment_create → Deploy (when supported) Cost: ~$0.50-5.00

Workflow 4: Explore Ideas Before Building

1. get_all_symbols → Check available pairs 2. get_allora_topics → See ML prediction coverage 3. generate_ideas (strategy_count=3) → Get AI concepts 4. Pick favorite idea 5. create_strategy → Implement chosen concept 6. run_backtest → Validate Cost: ~$0.50-4.50 (use generate_ideas to explore cheaply)

Start with Data Exploration

Always check availability before building: Use get_data_availability to verify symbol has sufficient history Check get_allora_topics if planning ML enhancement Review get_all_technical_indicators to know what's available

Always Backtest

Never deploy without backtesting: Test on 6+ months of data minimum Use multiple time periods (train vs validation) Check metrics: Sharpe >1.0, max drawdown <20%, win rate 45-65% Compare performance across different market conditions

Cost Management

Tools are priced in tiers: Data tools ($0.001 or free) - Use liberally Backtesting ($0.001) - Use frequently AI generation (LLM cost + margin) - Most expensive Deployment ($0.50) - One-time per deployment Cost-saving tips: Use generate_ideas ($0.05-0.50) before create_strategy ($1-4) Check get_latest_backtest_results (free) before running new backtest Use refine_strategy ($0.50-1.50) instead of regenerating with create_strategy Review get_strategy_code (free) before modifying

Strategy Naming Convention

Follow this pattern: {Name}_{RiskLevel}[_suffix] Examples: RSIMeanReversion_M - Base strategy, medium risk MomentumBreakout_H_optimized - After optimization, high risk TrendFollower_L_allora - With Allora ML, low risk Risk levels: H (high), M (medium), L (low)

Strategy Framework

Strategies use the Jesse trading framework with these required methods: should_long() - Check if conditions met for long entry should_short() - Check if conditions met for short entry go_long() - Execute long entry with position sizing go_short() - Execute short entry with position sizing Optional methods: on_open_position(order) - Set stop loss, take profit after entry update_position() - Trailing stops, position management should_cancel_entry() - Cancel unfilled orders

Available Indicators

170+ technical indicators via jesse.indicators: Momentum: RSI, MACD, Stochastic, ADX, CCI, MFI Trend: EMA, SMA, Supertrend, Parabolic SAR, VWAP Volatility: Bollinger Bands, ATR, Keltner Channels Volume: OBV, Volume Profile, Chaikin Money Flow And many more... Use get_all_technical_indicators to see the full list.

Allora Network Integration

Add ML price predictions to strategies: Prediction types: Log return (percentage change) or absolute price Horizons: 5m, 8h, 24h, 1 week Assets: BTC, ETH, SOL, NEAR Networks: Mainnet (10 topics) and Testnet (26 topics) Use enhance_with_allora to automatically integrate predictions, or manually add via self.get_predictions() in strategy code.

Deployment Options

EOA (Externally Owned Account): Direct wallet trading Max 1 active deployment per wallet Immediate deployment Lower setup complexity Hyperliquid Vault: Requires 200+ USDC in wallet Unlimited deployments Professional vault setup Public TVL and performance tracking

"Insufficient Credits" Error

Check balance: get_credit_balance Purchase credits in Robonet dashboard if needed

"No Data Available" for Backtest

Use get_data_availability to check symbol coverage Try shorter date range or different symbol BTC-USDT and ETH-USDT have longest history (2020-present)

"No Trades Generated" in Backtest

Entry conditions may be too restrictive Try longer test period or adjust thresholds Use get_strategy_code to review logic

Backtest Takes >2 Minutes

Long date ranges (>2 years) or high-frequency timeframes (1m) are slow Use shorter ranges or lower frequency timeframes

Strategy Not Showing in Web Interface

Strategies are linked to API key's wallet Ensure logged into same account that owns the API key Refresh "My Strategies" page

Complete Tool Reference

For detailed parameter documentation on all 24 tools, see: ./shared-references/tool-catalog.md The catalog includes: Full parameter specifications with types and defaults Return value descriptions Pricing for each tool Execution time estimates Usage examples

Example Prompts

• Create a simple strategy:
• Use Robonet MCP to create a momentum strategy for BTC-USDT on 4h timeframe that:
• Enters long when RSI crosses above 30 and price is above 50-day EMA
• Exits with 2% stop loss or 4% take profit
• Uses 95% of available margin
• Backtest existing strategy:
• Backtest my RSIMeanReversion_M strategy on ETH-USDT 1h timeframe from 2024-01-01 to 2024-06-30
• Optimize parameters:
• Optimize the RSI period and stop loss percentage for my MomentumBreakout_H strategy on BTC-USDT 4h from 2024-01-01 to 2024-12-31
• Add ML predictions:
• Enhance my TrendFollower_M strategy with Allora predictions for ETH-USDT 8h timeframe and compare performance
• Deploy to live trading:
• Deploy my RSIMeanReversion_M_allora strategy to Hyperliquid on BTC-USDT 4h with 2x leverage using EOA deployment

Security & Access

All tools require valid API key from Robonet Strategies are wallet-scoped (only creator can access) Credits reserved atomically before execution API keys never committed to version control Use environment variables or secure config for API keys

Resources

Robonet Dashboard: robonet.finance API Key Management: Dashboard → Settings → API Keys Credit Purchase: Dashboard → Settings → Billing Jesse Framework Docs: jesse.trade Allora Network: allora.network Hyperliquid: hyperliquid.xyz Support: Discord or support@robonet.finance