myselfgus/zeo-composable-mcp

🌟 ZEO Composable MCP Server

Revolutionary MCP Remote Server with 9 AI-Powered Composable Tools

A cutting-edge Model Context Protocol (MCP) remote server that combines 9 specialized AI tools into a unified, composable platform. Built on Cloudflare Workers for global edge computing with sub-50ms latency.

🚀 Features

🛠️ 9 AI-Powered Tools

⚡ Core Capabilities

• 🌍 Global Edge Computing: Deployed on Cloudflare Workers for worldwide availability
• 🔄 Real-time Processing: Sub-50ms response times with intelligent caching
• 🧮 Composable Architecture: Mix and match tools for complex workflows
• 📊 AI-Powered Insights: Every tool enhanced with advanced AI analysis
• 🔒 Enterprise Security: Built-in security auditing and compliance checking
• 📈 Scalable: Unlimited scalability with pay-per-use pricing
• 🔧 Easy Integration: Standard MCP protocol compatibility

🏁 Quick Start

Prerequisites

• Node.js 18+ and npm
• Cloudflare account with Workers enabled
• Wrangler CLI installed (npm install -g wrangler)

Installation

1. Clone the repository

   git clone https://github.com/myselfgus/zeo-composable-mcp.git
   cd zeo-composable-mcp
   

2. Install dependencies

   npm install
   

3. Configure Cloudflare resources

   # Create KV namespace
   wrangler kv:namespace create "ZEO_KV"
   
   # Create D1 database
   wrangler d1 create zeo-composable-db
   
   # Create R2 bucket
   wrangler r2 bucket create zeo-composable-storage
   

4. Update wrangler.toml with your resource IDs

5. Set up environment secrets

   wrangler secret put GITHUB_TOKEN
   wrangler secret put OPENAI_API_KEY
   wrangler secret put ANTHROPIC_API_KEY
   

6. Deploy to Cloudflare Workers

   npm run deploy
   

Local Development

# Start development server
npm run dev

# The server will be available at http://localhost:8787

📡 API Endpoints

🔧 Usage Examples

Using with Claude Desktop

Add to your MCP configuration:

{
  "mcpServers": {
    "zeo-composable": {
      "command": "npx",
      "args": ["mcp-remote", "https://your-worker.your-subdomain.workers.dev/sse"]
    }
  }
}

Direct API Usage

# Health check
curl https://your-worker.your-subdomain.workers.dev/health

# Use GitHub Orchestrator
curl -X POST https://your-worker.your-subdomain.workers.dev/mcp \
  -H "Content-Type: application/json" \
  -d '{
    "method": "tools/call",
    "params": {
      "name": "zeo_github_orchestrator",
      "arguments": {
        "action": "analyze_repo",
        "owner": "myselfgus",
        "repo": "zeo-composable-mcp"
      }
    }
  }'

🛠️ Tool Documentation

GitHub Orchestrator

Powerful GitHub integration with AI-enhanced analysis:

// Analyze repository with AI insights
{
  "action": "analyze_repo",
  "owner": "username",
  "repo": "repository",
  "analysis_depth": "comprehensive"
}

// Intelligent issue management
{
  "action": "create_issue",
  "owner": "username", 
  "repo": "repository",
  "title": "AI-Generated Issue",
  "body": "Detailed description with AI suggestions"
}

Memory Engine

Persistent memory with semantic search capabilities:

// Store knowledge with semantic indexing
{
  "action": "store",
  "content": "Complex technical documentation",
  "tags": ["technical", "documentation"],
  "context": {"project": "zeo-mcp", "version": "1.0"}
}

// Semantic search across stored knowledge
{
  "action": "semantic_search", 
  "query": "How to implement authentication?",
  "limit": 5,
  "similarity_threshold": 0.8
}

Unified Reasoner

Advanced AI reasoning with multiple strategies:

// Multi-strategy reasoning
{
  "action": "multi_strategy",
  "problem": "How to optimize database performance?",
  "strategies": ["analytical", "systematic", "creative"],
  "context": "High-traffic web application"
}

// Chain reasoning for complex problems
{
  "action": "chain_reasoning",
  "problem": "Design scalable microservices architecture",
  "chain_steps": [
    {"step": "Analyze current monolith", "strategy": "analytical"},
    {"step": "Identify service boundaries", "strategy": "systematic"},
    {"step": "Design communication patterns", "strategy": "architectural"}
  ]
}

Web Intelligence

Smart web scraping with AI-powered analysis:

// Comprehensive web analysis
{
  "action": "analyze",
  "url": "https://example.com",
  "analysis_depth": "comprehensive",
  "include_ai_insights": true
}

// Extract structured data
{
  "action": "extract",
  "url": "https://api-docs.example.com",
  "extract_type": "structured",
  "selectors": [".api-endpoint", ".code-example"]
}

🏗️ Architecture

graph TB
    A[Client Applications] --> B[ZEO MCP Server]
    B --> C[GitHub Orchestrator]
    B --> D[Memory Engine]
    B --> E[Web Intelligence]
    B --> F[Unified Reasoner]
    B --> G[Ideation Engine]
    B --> H[Implementation Bridge]
    B --> I[Workflow Orchestrator]
    B --> J[Code Architect]
    
    B --> K[Cloudflare AI]
    B --> L[KV Storage]
    B --> M[D1 Database]
    B --> N[R2 Bucket]
    
    subgraph "Edge Computing"
        O[Global CDN]
        P[Worker Instances]
        Q[Intelligent Caching]
    end
    
    B --> O

🔒 Security

• 🛡️ Built-in Security Auditing: Comprehensive security analysis tools
• 🔐 Encrypted Storage: All data encrypted at rest and in transit
• 🌐 Edge Security: Cloudflare's enterprise-grade security stack
• 🔑 API Key Management: Secure credential handling
• 📋 Compliance: OWASP, SANS, PCI-DSS, HIPAA, GDPR support

📊 Performance

• ⚡ Sub-50ms Latency: Global edge deployment
• 🔄 Intelligent Caching: Smart caching strategies
• 📈 Auto-scaling: Unlimited horizontal scaling
• 💾 Optimized Storage: Efficient data management
• 🎯 Resource Optimization: Memory and CPU optimizations

🤝 Contributing

We welcome contributions! Please see our for details.

Development Setup

1. Fork the repository
2. Create a feature branch: git checkout -b feature/amazing-feature
3. Make your changes
4. Add tests for new functionality
5. Submit a pull request

Code Style

• TypeScript with strict typing
• ESLint + Prettier for formatting
• Comprehensive JSDoc documentation
• Test coverage > 80%

📝 License

This project is licensed under the MIT License - see the file for details.

🙏 Acknowledgments

• Model Context Protocol (MCP): For the revolutionary AI integration standard
• Cloudflare Workers: For the incredible edge computing platform
• OpenAI & Anthropic: For the powerful AI models
• Open Source Community: For the tools and libraries that make this possible

📞 Support

• 🐛 Bug Reports: GitHub Issues
• 💡 Feature Requests: GitHub Discussions
• 📧 Email: gms@ireaje.cloud
• 🐦 Twitter: @MySelfGus

🗺️ Roadmap

• Analytics Dashboard: Real-time usage and performance analytics
• Plugin System: Custom tool development framework
• Multi-language Support: Python, Go, Rust implementations
• Enterprise Features: SSO, audit logs, advanced monitoring
• Mobile SDK: Native mobile app integration
• Webhook Support: Event-driven automation