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RedTeamMCP

Red Team MCP

by RedTeamMCP
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Python
Hybrid

Red Team MCP is a multi-agent collaboration platform that connects to 68 providers and 1500+ models via models.dev. Build specialized agent teams, coordinate complex workflows, and integrate seamlessly with VS Code and Claude Desktop through the Model Context Protocol (MCP).

✨ Features

🎯 Universal Model Access

  • 68 Providers: Anthropic, OpenAI, Google, Groq, Mistral, DeepSeek, and 60+ more

  • 1500+ Models: Auto-synced from models.dev

  • Unified API: One interface for all providers

🤖 Multi-Agent Collaboration

  • 5 Coordination Modes: Pipeline, Ensemble, Debate, Swarm, Hierarchical

  • Predefined Teams: Writing, Marketing, Research, Technical, Executive

  • Custom Teams: Build your own agent configurations

📡 MCP Integration

  • VS Code Ready: Works with GitHub Copilot

  • Claude Desktop: Native integration

  • Dynamic Tools: All agents exposed as MCP tools

🚀 Production Ready

  • FastAPI Backend: High-performance async API

  • Web Dashboard: HTMX-powered admin interface

  • Cost Tracking: Per-request usage analytics

🚀 Quick Start

Option A: Docker (Recommended)

git clone https://github.com/yourusername/red-team-mcp.git cd red-team-mcp cp .env.example .env # Edit .env with your API keys docker compose up -d # Open http://localhost:8000/ui/

Option B: Local Install

git clone https://github.com/yourusername/red-team-mcp.git cd red-team-mcp python -m venv venv source venv/bin/activate # Windows: venv\Scripts\activate pip install -r requirements.txt

Configure API Keys

cp .env.example .env # Edit .env with your API keys

Run

# Start the web server & dashboard python main.py serve # Open http://localhost:8000/ui/ # Or use the CLI python main.py chat "What is machine learning?" # Or start the MCP server python main.py mcp

🤝 Multi-Agent Coordination

Red Team MCP excels at coordinating multiple AI agents on complex tasks. Choose from 5 coordination modes:

Mode

Description

Best For

Pipeline

Agents work sequentially, each building on the previous output

Document workflows, iterative refinement

Ensemble

Agents work in parallel, then synthesize results

Comprehensive analysis, multiple perspectives

Debate

Agents engage in back-and-forth argumentation

Critical thinking, finding flaws

Swarm

CrewAI-powered collaboration with delegation

Complex projects, dynamic task allocation

Hierarchical

Manager agent delegates to specialists

Large teams, structured workflows

Predefined Agent Teams

Team

Agents

Default Mode

Writing Team

Creative Writer, Editor, SEO Specialist

Pipeline

Marketing Team

Strategist, Brand Manager, Social Media

Hierarchical

Research Team

Researcher, Data Scientist, Analyst

Ensemble

Technical Team

Expert, Solutions Architect, Security

Debate

Executive Team

Strategy, Financial, Operations

Ensemble

Example: Multi-Agent Request

curl -X POST "http://localhost:8000/api/multi-agent" \ -H "Content-Type: application/json" \ -d '{ "query": "Analyze the competitive landscape for AI startups", "coordination_mode": "ensemble", "agents": ["financial_analyst", "strategy_consultant", "technical_expert"] }'

📡 MCP Integration

Red Team MCP provides a Model Context Protocol server for seamless integration with AI assistants.

VS Code Setup

Create .vscode/mcp.json in your project:

{ "servers": { "red-team-mcp": { "command": "python", "args": ["-m", "src.mcp_server_dynamic"], "cwd": "/path/to/red-team-mcp" } } }

Claude Desktop Setup

Add to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json):

{ "mcpServers": { "red-team-mcp": { "command": "python", "args": ["/path/to/red-team-mcp/main.py", "mcp"] } } }

Available MCP Tools

Tool

Description

list_agents

List all available agents

list_teams

List all predefined teams

chat

Chat with a specific agent

run_team

Execute a team on a task

coordinate

Run multi-agent coordination

brainstorm

Generate multiple perspectives

📖 API Reference

Chat Endpoint

POST /api/chat Content-Type: application/json { "agent_id": "creative_writer", "message": "Write a tagline for an AI product", "temperature": 0.8, "max_tokens": 500 }

Multi-Agent Endpoint

POST /api/multi-agent Content-Type: application/json { "query": "Develop a go-to-market strategy", "coordination_mode": "hierarchical", "agents": ["marketing_strategist", "sales_analyst"], "rebuttal_limit": 3 }

Run Team Endpoint

POST /api/team/{team_id}/run Content-Type: application/json { "query": "Create a blog post about AI trends", "coordination_mode": "pipeline" }

Additional Endpoints

Endpoint

Method

Description

/api/agents

GET

List all agents

/api/teams

GET

List all teams

/api/models

GET

List available models

/health

GET

Health check

/ws/chat

WS

WebSocket streaming

🏗️ Architecture

red-team-mcp/ ├── main.py # CLI entry point ├── config/config.yaml # Configuration ├── src/ │ ├── api/ # FastAPI application │ │ ├── app.py # App factory │ │ ├── endpoints.py # REST endpoints │ │ └── websockets.py # WebSocket handlers │ ├── agents/ # Agent implementations │ │ ├── configurable_agent.py │ │ └── coordinator.py # Multi-agent coordination │ ├── web/ # Dashboard UI │ │ ├── routes.py │ │ └── templates/ # HTMX templates │ ├── providers/ # 68 provider implementations │ ├── config.py # Configuration management │ ├── models.py # Model selector │ ├── db.py # SQLite persistence │ └── mcp_server_dynamic.py # MCP server └── mcp_servers/ # Generated MCP servers

⚙️ Configuration

Environment Variables

# Core providers ANTHROPIC_API_KEY=your_key OPENAI_API_KEY=your_key GOOGLE_API_KEY=your_key GROQ_API_KEY=your_key DEEPSEEK_API_KEY=your_key # And 60+ more providers supported!

config.yaml

api: host: "0.0.0.0" port: 8000 rate_limit: "100/minute" models: default: "claude-sonnet-4-20250514" agents: predefined: - id: my_custom_agent name: Custom Agent model_id: gpt-4o provider: openai role: Specialist goal: Help with specific tasks

🧪 Development

# Run tests python -m pytest tests/ -v # Run with hot reload python main.py serve --reload # Generate MCP servers python main.py generate-mcp --all

📊 Web Dashboard

Access the admin dashboard at http://localhost:8000/ui/ to:

  • 💬 Chat with any agent interactively

  • 👥 Manage Teams and agent configurations

  • 📈 View Statistics on usage and costs

  • ⚙️ Configure providers and settings

  • 📤 Export configurations

🤝 Contributing

  1. Fork the repository

  2. Create a feature branch (git checkout -b feature/amazing)

  3. Add tests for new functionality

  4. Ensure all tests pass (python -m pytest)

  5. Submit a pull request

📄 License

AGPL-3.0 License - see LICENSE for details.

🙏 Acknowledgments

  • models.dev - Comprehensive model database

  • CrewAI - Agent orchestration framework

  • FastAPI - High-performance web framework

  • All 68 AI providers making their models accessible

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