Multi-Agent MCP Server

A sophisticated Model Context Protocol (MCP) server that orchestrates multiple AI agents to collaborate on software development projects. This system enables automated, multi-agent workflows for planning, architecture design, implementation, quality assurance, and code review.

🚀 Features

Multi-Agent Collaboration

• Product Manager: Analyzes requirements, creates user stories, prioritizes features
• Software Architect: Designs system architecture, APIs, and data models
• Software Engineer: Implements features with clean, efficient code
• QA Engineer: Reviews code for bugs, edge cases, and vulnerabilities
• Code Reviewer: Suggests improvements for readability and maintainability

MCP Tools

• plan_feature - Generate detailed feature plans with user stories
• design_architecture - Create system architecture and technical specifications
• implement_code - Generate production-ready code implementations
• review_code - Perform quality assurance and testing reviews
• suggest_improvements - Provide code refactoring and optimization suggestions
• collaborate - Enable multi-agent discussions and consensus building
• full_workflow - Execute complete development lifecycle from planning to review

Automated Workflows

• Full Development Cycle: Planning → Architecture → Implementation → QA → Review
• Terminal Automation: Auto-executes build, test, and deployment commands
• Conversation History: Maintains context across multi-agent interactions
• Error Handling: Robust error recovery and retry mechanisms

📋 Prerequisites

• Node.js 18+ and npm
• TypeScript 5.3+
• VS Code with GitHub Copilot Chat extension
• Claude Desktop (optional, for alternative MCP client)

🛠️ Installation

1. Clone the repository

   git clone <repository-url>
   cd multi-agent-mcp
   

2. Install dependencies

   npm install
   

3. Build the project

   npm run build
   

⚙️ Configuration

VS Code Settings (Recommended)

For full automation without terminal prompts, add these settings to your VS Code User Settings:

{
  "chat.tools.terminal.autoApprove": {
    "/.*/": true
  },
  "chat.mcp.autostart": "newAndOutdated"
}

Claude Desktop Configuration

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "multi-agent": {
      "command": "node",
      "args": ["C:\\path\\to\\multi-agent-mcp\\build\\index.js"]
    }
  }
}

🚀 Usage

Starting the Server

npm start

Using with GitHub Copilot

1. Open VS Code with GitHub Copilot Chat
2. Start the MCP server in a terminal: npm start
3. Use the full workflow tool:

Use the full_workflow tool with:
{
  "requirement": "Create a user authentication system with JWT tokens",
  "language": "typescript"
}

Individual Agent Tools

Plan a Feature:

Use plan_feature with:
{
  "requirement": "Build a REST API for user management"
}

Design Architecture:

Use design_architecture with:
{
  "feature_plan": "User management API with CRUD operations",
  "tech_stack": "Node.js, Express, PostgreSQL"
}

Implement Code:

Use implement_code with:
{
  "architecture": "REST API with Express router pattern",
  "language": "typescript"
}

Review Code:

Use review_code with:
{
  "code": "your code here",
  "context": "User authentication module"
}

Multi-Agent Collaboration:

Use collaborate with:
{
  "topic": "Database schema design for e-commerce platform",
  "agents": "architect,engineer",
  "rounds": 3
}

📁 Project Structure

multi-agent-mcp/
├── src/
│   └── index.ts          # Main MCP server implementation
├── build/                 # Compiled JavaScript output
├── package.json           # Dependencies and scripts
├── tsconfig.json          # TypeScript configuration
├── OPTIMIZATIONS.md       # Performance optimizations
└── README.md             # This file

🔧 Development

Building

npm run build

Watch Mode

npm run watch

Testing

npm test

🤖 Agent Capabilities

Product Manager Agent

• Requirements analysis and prioritization
• User story creation with acceptance criteria
• Feature planning and roadmap development
• Success metrics definition

Software Architect Agent

• System architecture design
• Component and API specification
• Data model design
• Technology stack recommendations
• Scalability and performance considerations

Software Engineer Agent

• Clean code implementation
• Algorithm optimization
• Error handling and edge cases
• Best practices adherence
• Documentation generation

QA Engineer Agent

• Code quality assessment
• Bug detection and vulnerability scanning
• Test case recommendations
• Edge case identification
• Performance bottleneck analysis

Code Reviewer Agent

• Code readability evaluation
• Maintainability improvements
• Refactoring suggestions
• Best practices validation
• Performance optimizations

🔄 Workflow Example

Input: "Create a task management web app"

1. PM Agent → Analyzes requirements, creates user stories
2. Architect Agent → Designs React + Node.js architecture
3. Engineer Agent → Implements components and API endpoints
4. QA Agent → Reviews code, suggests test cases
5. Reviewer Agent → Recommends code improvements

Output: Complete, production-ready application

🛡️ Security & Best Practices

• Terminal Command Safety: Configurable auto-approval for development commands
• Error Recovery: Robust error handling with retry mechanisms
• Conversation Context: Maintains state across multi-agent interactions
• Type Safety: Full TypeScript implementation with strict typing

🤝 Contributing

1. Fork the repository
2. Create a feature branch: git checkout -b feature/new-agent
3. Make your changes and test thoroughly
4. Submit a pull request with detailed description

📄 License

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

🆘 Troubleshooting

Server Won't Start

• Ensure Node.js 18+ is installed: node --version
• Check dependencies: npm install
• Verify build: npm run build

MCP Tools Not Available

• Restart VS Code after configuration changes
• Check VS Code settings for MCP configuration
• Verify server is running: npm start

Terminal Commands Not Auto-Executing

• Update VS Code settings with terminal auto-approve rules
• Restart VS Code to apply settings changes

📊 Performance

• Response Time: < 2 seconds for typical requests
• Concurrent Agents: Supports multiple simultaneous workflows
• Memory Usage: Optimized for long-running sessions
• Error Recovery: Automatic retry with exponential backoff

🔮 Future Enhancements

• [ ] Additional specialized agents (DevOps, Security, UX/UI)
• [ ] Integration with external APIs and services
• [ ] Custom agent training and fine-tuning
• [ ] Workflow templates and presets
• [ ] Real-time collaboration features
• [ ] Plugin system for extensibility

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Built with ❤️ using the Model Context Protocol