binance-spot-traderAutonomous Binance spot trading bot with LLM-powered market analysis. Supports momentum trading, mean reversion, and DCA strategies on any Binance spot pair. Use when user wants to trade on Binance, set up automated crypto trading, build a spot trading bot, or automate DCA buying. Features technical analysis, LLM sentiment evaluation, position sizing, and portfolio tracking.
Install via ClawdBot CLI:
clawdbot install srikanthbellary/binance-spot-traderAutonomous spot trading bot for Binance. Combines technical indicators with LLM-powered market sentiment analysis to execute trades on any Binance spot pair.
bash {baseDir}/scripts/setup.shCreate .env:
BINANCE_API_KEY=<your-api-key>
BINANCE_SECRET_KEY=<your-secret-key>
LLM_API_KEY=<anthropic-api-key>
PAIRS=BTCUSDT,ETHUSDT,SOLUSDT
STRATEGY=momentum
TRADE_SIZE_PCT=5
MAX_POSITIONS=5python3 {baseDir}/scripts/trader.pyOr via cron:
*/5 * * * * cd /opt/trader && python3 trader.py >> trader.log 2>&1| Parameter | Default | Description |
|-----------|---------|-------------|
| PAIRS | BTCUSDT | Comma-separated trading pairs |
| STRATEGY | momentum | momentum, mean_reversion, or dca |
| TRADE_SIZE_PCT | 5 | % of portfolio per trade |
| MAX_POSITIONS | 5 | Max concurrent open positions |
| TAKE_PROFIT_PCT | 5 | Take profit % |
| STOP_LOSS_PCT | 3 | Stop loss % |
| DCA_INTERVAL | daily | For DCA: hourly, daily, weekly |
| DCA_AMOUNT_USDT | 50 | USDT per DCA buy |
| USE_LLM | true | Enable LLM sentiment filter |
# Check portfolio
python3 {baseDir}/scripts/portfolio.py
# View trade history
tail -50 trades.jsonl
# Check logs
tail -f trader.logreferences/binance-api.md for REST API docsreferences/indicators.md for technical analysis detailsGenerated Mar 1, 2026
A retail investor uses the bot to manage a diversified crypto portfolio on Binance, automating trades based on momentum and mean reversion strategies to capture market trends and reduce manual oversight. It integrates LLM sentiment analysis to filter trades, enhancing decision-making in volatile conditions.
An individual employs the DCA strategy to systematically invest fixed amounts in cryptocurrencies like BTC and ETH at regular intervals, mitigating timing risks and building holdings over time without constant market monitoring. This is ideal for passive investors seeking gradual exposure.
A small fund or trading group leverages the bot to execute automated spot trades on Binance, using technical indicators and LLM insights to identify opportunities across multiple pairs, optimizing returns with controlled risk parameters like stop-loss and position sizing.
A student or enthusiast uses the bot in a sandbox environment to learn about algorithmic trading, experimenting with different strategies and parameters to understand market dynamics and backtest approaches without risking significant capital.
A research firm integrates the bot's LLM-powered sentiment evaluation to analyze crypto market trends, combining technical data with qualitative insights from news and volume patterns to generate reports or inform broader trading decisions.
Offer the trading bot as a SaaS platform with tiered subscriptions, providing users access to advanced features like LLM sentiment filtering and multiple strategies, generating recurring revenue from individual traders and small funds.
License the bot technology to cryptocurrency exchanges or fintech companies as a white-label product, allowing them to offer automated trading tools to their users and earning revenue through licensing fees or revenue-sharing agreements.
Operate a managed trading service where clients allocate funds, and the bot executes trades on their behalf, charging a performance fee based on profits or a fixed management fee, targeting investors seeking hands-off crypto exposure.
💬 Integration Tip
Ensure API keys are securely stored with restricted permissions and test strategies with small amounts first to validate performance in live markets.
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