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Unlock the Power of Automated DeFi Yield Optimization with YieldSwarm

Maximize your returns across multiple chains with our intelligent, open-source yield optimization platform.

Networks To Be Supported

Ethereum
BSC
Polygon
Arbitrum
Solana

About YieldSwarm

An intelligent multi-agent system that autonomously discovers, analyzes, and executes1 optimal yield farming strategies2 across multiple blockchain networks3 using JuliaOS's swarm intelligence and AI capabilities.

Multi-Chain DeFi Excellence

Multi-Chain Support

Access yield opportunities across Ethereum, BSC, Polygon, Arbitrum, and Solana

Automated Yield Farming

Set parameters and let our algorithms handle the complex strategies

Intelligent Portfolio Optimization

Advanced algorithms optimize for maximum risk-adjusted returns

Open Source

Transparent, community-driven development with full code accessibility

Built with JuliaOS

Powered by JuliaOS, the next-generation AI swarm operating system for limitless scaling and bulletproof security

YieldSwarm Platform Overview
1. execution capabilities not yet built into the system
2. currently, just one algorithm is supported for this - Morden Portfolio Theory
3. currently, this current release just supports Solana with more chain support coming in future releases

Key Features

Discover the powerful features that make YieldSwarm the ultimate DeFi yield optimization platform.

Intelligent Portfolio Management
Advanced algorithms optimize your portfolio for maximum risk-adjusted returns using cutting-edge analytics.
Automated Strategies
Set your parameters and let YieldSwarm automate your yield farming strategies 24/7.
Risk Logger
Protect investments with built-in smart risk logging tools.
Swarm Intelligence
Leverage our unique multi-agent system for collective decision-making and enhanced performance optimization.

Open Source & Community

YieldSwarm aims to be an open-source project, built by the community, for the community. Join us in shaping the future of DeFi.

Community-Driven Development

Open Source Transparency

Our entire codebase is open source, ensuring complete transparency and allowing the community to audit, contribute, and improve the platform.

Community Contributions

We welcome contributions from developers, researchers, and DeFi enthusiasts. Help us build the next generation of yield optimization tools.

Powered by JuliaOS

YieldSwarm is built on JuliaOS, the next-generation AI swarm operating system that provides the platform for the application to function on.

White Paper

Dive deep into YieldSwarm's technical architecture, economic model, and roadmap. Our comprehensive white paper covers:

  • Technical implementation details
  • Economic model and tokenomics
  • Development roadmap
  • Risk management strategies
Read the Whitepaper

Getting Started

Follow these steps to set up YieldSwarm and start optimizing your DeFi yields.

1. Clone the Repository
git clone https://github.com/DavidNzube101/YieldSwarm.git
cd MCDYOS
2. Install Node.js Dependencies

YieldSwarm requires Node.js (v18 or later) and pnpm. Install dependencies using pnpm:

pnpm install
3. Set Up Environment Variables

Create a `test.env` file and add your Hugging Face API token.

cp env.example test.env
# Add your HF_TOKEN to test.env
HF_TOKEN=YOUR_HUGGINGFACE_ACCESS_TOKEN
4. Build the Project

Compile the TypeScript code and prepare the application for launch.

pnpm build
5. Running the Application

Start the Julia and Node.js servers in separate terminals.

# Terminal 1: Start Julia Backend
julia backend/julia_server.jl
# Terminal 2: Start Node.js Server
pnpm start:api

Access the dashboard at http://localhost:3000. Stuck on the dashboard? Read the more comprehensive manual in the official README

4. Running Tests

Run tests to ensure everything is working correctly:

full test procedures on the official GitHub
Important Disclaimer

This is an experimental software. Use at your own risk.

Explore the Future of DeFi Yield Optimization

Join the YieldSwarm community and start maximizing your DeFi returns with intelligent, automated strategies.