Robonet MCP Integration

Overview

Quick Start

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

Tool Categories

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

• 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

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

• 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

3. Backtesting Tools (20-40s execution)

• run_backtest

  - Test crypto trading strategies

• run_prediction_market_backtest

  - Test Polymarket strategies

4. Prediction Market Tools

• 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

5. Deployment Tools

• 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

• EOA (wallet): Max 1 active deployment per wallet
• Hyperliquid Vault: Requires 200+ USDC in wallet, unlimited deployments

6. Account Tools

• get_credit_balance

  - Check available USDC credits

• get_credit_transactions

  - View transaction history

Common Workflows

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

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

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)

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

Strategy Development Best Practices

Start with Data Exploration

• 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

• 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

1. Data tools ($0.001 or free) - Use liberally
2. Backtesting ($0.001) - Use frequently
3. AI generation (LLM cost + margin) - Most expensive
4. Deployment ($0.50) - One-time per deployment

• 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

{Name}_{RiskLevel}[_suffix]

• RSIMeanReversion_M

  - Base strategy, medium risk

• MomentumBreakout_H_optimized

  - After optimization, high risk

• TrendFollower_L_allora

  - With Allora ML, low risk

Technical Details

Strategy Framework

• 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

• 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

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...

get_all_technical_indicators

Allora Network Integration

• 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)

enhance_with_allora

self.get_predictions()

Deployment Options

• Direct wallet trading
• Max 1 active deployment per wallet
• Immediate deployment
• Lower setup complexity

• Requires 200+ USDC in wallet
• Unlimited deployments
• Professional vault setup
• Public TVL and performance tracking

Troubleshooting

"Insufficient Credits" Error

get_credit_balance

"No Data Available" for Backtest

get_data_availability

"No Trades Generated" in Backtest

get_strategy_code

Backtest Takes >2 Minutes

Strategy Not Showing in Web Interface

Complete Tool Reference

• ../../shared-references/tool-catalog.md

• Full parameter specifications with types and defaults
• Return value descriptions
• Pricing for each tool
• Execution time estimates
• Usage examples

Example Prompts

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 my RSIMeanReversion_M strategy on ETH-USDT 1h timeframe from 2024-01-01 to 2024-06-30

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

Enhance my TrendFollower_M strategy with Allora predictions for ETH-USDT 8h timeframe and compare performance

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