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Project 4 min read

Solana Trading Bot Platform | Deploy OpenClaw Agents

Deploy autonomous Solana trading bots in minutes with Trawling Traders. Mobile-first control plane, risk management, paper trading by default.

Originally published:

GitHub by janebot2026

Solana Trading Bots Deployed in Minutes

Trawling Traders is a production-ready framework for deploying autonomous trading agents on Solana, powered by OpenClaw. It eliminates the complexity of building trading infrastructure by providing a complete stack: a React Native mobile app for management, a Rust-based control plane for orchestration, price aggregation services, and bot runners that execute on your own DigitalOcean VPS. Every trader runs paper trading by default, with transparent P&L tracking and full custody of keys—your infrastructure, your rules, your profits.

Core Capabilities

  • Deploy in minutes: From mobile app tap to live bot on your VPS—no manual server provisioning or DevOps expertise required
  • Three trading personas: Set-and-Forget (conservative defaults), Hands-On (tunable risk controls), and Power User (custom signal knobs and baskets)
  • Built-in algorithms: Trend following (SMA crossover with momentum), mean reversion (Z-score fading), and volume-confirmed breakouts
  • Real-time portfolio metrics: 7-day performance data, trade event logs (last 100 trades), and live P&L on mobile
  • Risk shields: Position sizing (% portfolio), max daily loss limits, drawdown circuit breakers, and trade-per-day caps—all configurable
  • Subscription tiers: Free (1 bot, 10 trades/day), Pro (4 bots, 100 trades/day), Enterprise (20 bots, 1000 trades/day, custom strategies)
  • No fork required: Sync adapter pattern lets bots poll control plane for config updates without modifying OpenClaw core
  • Secrets management: AES-256-GCM encryption for API keys, with rate limiting (100 req/120 sec) and health checks for reliability

Architecture Overview

The system is built as a distributed multi-service stack. The React Native mobile app handles bot creation, configuration, and monitoring with integrated Cedros login and payment processing. The Rust/Axum control plane provides REST APIs for bot lifecycle management (CRUD), subscription tier enforcement, configuration versioning, and secrets encryption. A dedicated data retrieval service aggregates real-time prices from CoinGecko, Binance WebSocket, and Pyth (for commodities/metals). Finally, individual bot runners deployed on DigitalOcean VPS instances poll the control plane for config updates, execute trades via claw-trader-cli, and report events back continuously.

Getting Started

Prerequisites: Rust (latest stable via rustup.rs), Node.js 18+, PostgreSQL 14+, and a DigitalOcean account.

  1. Clone the repository and run make setup to install dependencies
  2. Create .env file with database URL, encryption key, and API tokens (generate encryption key with openssl rand -base64 32)
  3. Start PostgreSQL and run migrations: cargo sqlx migrate run
  4. Launch services: make dev-tmux runs data retrieval (port 8080), control plane (port 3000), and mobile app in separate tmux panes
  5. Access mobile app on iOS/Android simulator to create and manage bots

API for Developers

The control plane exposes two API surfaces. App-facing endpoints (requires Cedros JWT) include bot CRUD, config updates, performance metrics, trade events, and signal simulation. Bot-facing endpoints (from VPS runners) handle registration, config polling with hash-based change detection, config acknowledgment, heartbeat pings, trade event submission, and wallet reporting. Health checks (/v1/healthz, /v1/readyz) require no auth and are designed for load balancer integration.

Who This Is For

  • Solana traders: Want to automate strategies without learning full infrastructure—just configure algorithms in the app
  • Rust developers: Building trading systems and need a modular, production-ready starting point with encryption and rate limiting baked in
  • Crypto projects: Looking to offer bot capabilities to users without maintaining centralized infrastructure
  • Quantitative traders: Need to backtest multiple personas and algorithms before committing capital

Key Resources

  • GitHub Repository — Source code, migrations, and deployment configs
  • Makefile — Development commands for all services (setup, dev, dev-tmux, db, migrations)
  • docker-compose.yml — Optional containerized deployment
  • Environment guides — cedros-login-embedding-guide.md and cedros-pay-embedding-guide.md for payment/auth integration
  • Mission Control Dashboard – OpenClaw Agent — The bot execution layer powering trade logic
  • Jupiter API — Optional: DCA and swap integration (configure JUPITER_API_KEY)

Development Workflow

The project structure separates concerns: apps/mobile for the React Native frontend, services/control-plane for API orchestration, services/data-retrieval for market data, services/bot-runner for agent execution, and packages/downrigger as a setup CLI. Database migrations use SQLx for type-safe SQL. All endpoints are versioned (/v1/) to enable backward compatibility as the system evolves. Rate limiting defaults to 100 requests per 120 seconds to prevent abuse.

Source: GitHub repository janebot2026/trawling-traders (last updated February 2026).

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https://github.com/janebot2026/trawling-traders

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