Solana MEV Bot

Solana MEV Bot-A production-ready MEV (Maximal Extractable Value) trading bot for the Solana blockchain, designed with clean architecture, modular code, and comprehensive risk controls.

✅ IMPLEMENTATION COMPLETE: This codebase includes a fully functional MEV bot with arbitrage, sandwich, and liquidation strategies, real-time mempool monitoring, transaction simulation, and optimized execution through Jito bundles.

📞 Contact

Preferred method for quick chat:

Also available on:

• Telegram: https://t.me/solanabull0
• WhatsApp: +1 (838) 273-9959
• Email: tradingsolana8@gmail.com
• Discord: solanabull0

⚠️ Disclaimer

This software carries significant financial risk. MEV trading can result in substantial losses. Use at your own risk and only with funds you can afford to lose.

🚀 Features

• Real-time Mempool Monitoring: WebSocket subscriptions to detect MEV opportunities
• Multi-DEX Arbitrage: Cross-DEX arbitrage between Raydium, Orca, and OpenBook
• Transaction Simulation: Pre-execution validation and profit analysis
• Optimized Execution: Jito bundle support and direct TPU submission
• Risk Management: Comprehensive safety controls and loss limits
• Structured Logging: JSON-formatted logs with performance metrics
• Modular Architecture: Easily extensible strategy system

🏗️ Architecture

mev-bot/
├── config/
│   └── config.toml          # Configuration file
├── src/
│   ├── main.rs              # Application entry point
│   ├── engine/              # Core bot engine
│   │   ├── mempool_listener.rs  # Real-time mempool monitoring
│   │   ├── strategy_router.rs   # Opportunity routing
│   │   ├── simulation.rs         # Transaction simulation
│   │   └── executor.rs           # Transaction execution
│   ├── strategies/          # MEV strategies
│   │   ├── arbitrage.rs     # DEX arbitrage
│   │   ├── sandwich.rs      # Sandwich attacks
│   │   └── liquidation.rs   # Liquidation monitoring
│   ├── dex/                 # DEX integrations
│   │   ├── raydium.rs       # Raydium AMM
│   │   ├── orca.rs          # Orca Whirlpool
│   │   └── openbook.rs      # OpenBook orderbook
│   └── utils/               # Shared utilities
│       ├── config.rs        # Configuration management
│       ├── logger.rs        # Logging system
│       ├── math.rs          # Mathematical operations
│       ├── fees.rs          # Fee calculations
│       └── priority.rs      # Priority fee management
├── tests/                   # Test suites
└── README.md

📋 Requirements

• Rust 1.70+
• Solana CLI tools
• Linux/Windows/macOS

🚀 Quick Start

1. Clone and Setup

git clone <repository-url>
cd solana-mev-bot
cargo build --release

2. Configuration

Edit config/config.toml:

[bot]
enabled = true
name = "solana-mev-bot"

[solana]
rpc_url = "https://api.mainnet-beta.solana.com"
ws_url = "wss://api.mainnet-beta.solana.com"

[strategies]
arbitrage = true
sandwich = false  # High risk, enable with caution
liquidation = false

[risk_management]
max_sol_per_trade = 1.0
daily_loss_limit_usd = 100.0
max_consecutive_failures = 5

3. Environment Variables

Set your wallet private key (never commit to version control):

export PRIVATE_KEY="your_private_key_here"

4. Run the Bot

cargo run --release

⚙️ Configuration

Core Settings

Setting	Description	Default
solana.rpc_url	Solana RPC endpoint	https://api.mainnet-beta.solana.com
solana.ws_url	WebSocket endpoint	wss://api.mainnet-beta.solana.com
risk_management.max_sol_per_trade	Max SOL per trade	1.0
arbitrage.min_profit_usd	Minimum arbitrage profit	0.1

Strategy Configuration

Arbitrage Strategy

[arbitrage]
enabled = true
min_profit_usd = 0.1
max_slippage_bps = 50  # 0.5%
supported_dexes = ["raydium", "orca", "openbook"]

Sandwich Strategy (High Risk)

[sandwich]
enabled = false  # Only enable if you understand the risks
min_target_size_usd = 100.0
max_front_run_bps = 20

Jito Integration

[jito]
enabled = true
block_engine_url = "https://mainnet.block-engine.jito.wtf"
tip_account = "96gYZGLnJYVFmbjzopPSU6QiEV5fGqZNyN9nmNhvrZU"
max_tip_lamports = 1000000

🎯 MEV Strategies

1. Arbitrage

How it works:

• Monitors price differences across DEXes
• Executes atomic swaps when profitable
• Supports multi-hop routes (A → B → C)

Supported DEXes:

• Raydium AMM
• Orca Whirlpool
• OpenBook (Phoenix)

Example Opportunity:

SOL/USD on Raydium: $150.00
SOL/USD on Orca: $150.05
→ Buy on Raydium, sell on Orca for $0.05 profit per SOL

2. Sandwich Attacks (Optional)

How it works:

• Detects large pending swaps in mempool
• Front-runs with buy, back-runs with sell
• Uses slippage protection

⚠️ High Risk: Can cause significant slippage and failed transactions

3. Liquidation Monitoring (Optional)

How it works:

• Monitors lending protocols (Marginfi, Solend)
• Detects undercollateralized positions
• Liquidates when profitable

🔒 Risk Management

Safety Features

1. Position Limits

   • Maximum SOL per trade
   • Daily loss limits
   • Auto-disable on consecutive failures

2. Transaction Validation

   • Pre-execution simulation
   • Slippage protection
   • Compute unit limits

3. Kill Switch

   [risk_management]
   kill_switch = false  # Set to true to disable trading

Monitoring

# View logs
tail -f logs/mev-bot.log

# Health check (if monitoring enabled)
curl http://localhost:9090/health

📊 Performance & Optimization

Latency Optimization

1. WebSocket Subscriptions: Real-time mempool monitoring
2. Jito Bundles: Optimized transaction ordering
3. Direct TPU: Minimal network latency
4. Pre-computed Routes: Cached DEX pool data

Memory Management

• Connection pooling for RPC calls
• Efficient data structures for price caching
• Garbage collection for stale opportunities

Error Handling

• Automatic retry with exponential backoff
• Circuit breakers for failing components
• Graceful degradation on network issues

🔧 Development

Building

# Debug build
cargo build

# Release build (optimized)
cargo build --release

# Run tests
cargo test

Code Quality

• Zero unsafe code unless justified
• Strong typing everywhere
• Comprehensive error handling
• Performance-first mindset

Adding New Strategies

1. Create strategy in src/strategies/
2. Implement required traits
3. Add to StrategyRouter
4. Update configuration

Example:

#[async_trait]
impl ExecutableOpportunity for MyStrategy {
    async fn get_simulation_data(&self) -> Result<SimulationData, Error> {
        // Implementation
    }

    fn get_expected_profit(&self) -> f64 {
        // Implementation
    }
}

📈 Monitoring & Metrics

Logging

Structured JSON logs include:

• Opportunity detection
• Transaction execution results
• Performance metrics
• Error conditions

Metrics (Optional)

[monitoring]
enabled = true
metrics_port = 9090
alert_webhook_url = "https://hooks.slack.com/..."

Available metrics:

• Opportunities detected/executed
• Success rates
• Latency measurements
• Error counts

🚨 Troubleshooting

Common Issues

1. Connection Failures

   Error: WebSocket connection failed
   

   • Check network connectivity
   • Verify RPC/WebSocket URLs
   • Consider using a different RPC provider

2. Transaction Failures

   Error: Simulation failed
   

   • Check account balances
   • Verify program IDs
   • Review slippage settings

3. Low Profit Detection

   Warning: No profitable opportunities found
   

   • Adjust minimum profit thresholds
   • Check DEX liquidity
   • Verify price feeds

Debug Mode

Enable debug logging:

[logging]
level = "DEBUG"

🤝 Contributing

1. Fork the repository
2. Create a feature branch
3. Add tests for new functionality
4. Ensure all tests pass
5. Submit a pull request

Code Standards

• Use rustfmt for formatting
• Add documentation for public APIs
• Include unit tests for critical functions
• Follow the existing modular structure

📄 License

MIT License - see LICENSE file for details.

🙏 Acknowledgments

• Solana Foundation for the excellent documentation
• Jito Labs for MEV infrastructure
• DEX communities for protocol transparency

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Remember: MEV trading is highly competitive and risky. This bot provides the infrastructure, but success depends on market conditions, timing, and risk management.