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🚀 MCP Server Multi Tools 🌉

Note

Model Context Protocol (MCP) Bridge - A powerful service that connects AI agents with DevOps and communication tools through a standardized interface.

Welcome to the MCP Server Multi Tools! This service acts as a seamless integration layer, enabling AI agents and systems to interact with services like Azure DevOps, Slack, GitHub, and even other agents (with their own tools) using a simple, unified protocol.


🛠️ Available Tools & Providers

📊 DevOps & Project Management

A comprehensive suite for total project management:

  • 📝 Work Items: Create, read, update, search, and comment
  • 🏃‍♂️ Sprints: Manage sprints, view contents, and track progress
  • 🔍 WIQL: Execute custom Work Item Query Language statements
  • 🔗 Enrichment: Augment work items with GitHub, Slack, and Sentry context
  • 📁 Git Content: Fetch file content from associated repositories

🐙 GitHub Integration

  • Seamless version control and pull request workflows
  • Repository content access and management

💬 Communication

  • Real-time notifications and messaging
  • Channel posting for agent communication
  • Team collaboration enhancement

🤖 Advanced Agent System

Important

Agents-in-Agents: Revolutionary nested agent architecture

Your AI agent can create and manage other agents, each with:

  • 🐋 Docker container with full Debian Linux system
  • 🌐 Web browser capabilities
  • 🔄 Iterative work processes
  • 💬 Inter-agent communication

🚀 Quick Start Guide

📋 Prerequisites

Warning

Ensure you have the following before proceeding:

  • Go (latest version)
  • 🔑 Service credentials (Azure DevOps, Slack tokens, etc.)
  • 🐳 Docker Desktop (for agents-in-agents feature)

Step 1️⃣: Clone & Build

# Clone the repository
git clone https://github.com/theapemachine/mcp-server-multi-tools.git
cd mcp-server-devops-bridge

# Build the server
go build -o mcp-server-multi-tools .

Step 2️⃣: Environment Setup

# Copy and configure environment variables
cp start.sh.example start.sh
vim start.sh  # Add your credentials

Tip

The server is configured entirely through environment variables for maximum flexibility.

Step 3️⃣: MCP Client Configuration

Add to your Claude Desktop configuration:

{
  "mcpServers": {
    "multi-tools": {
      "command": "/path/to/mcp-server-multi-tools/start.sh",
      "args": []
    }
  }
}

🎬 See It In Action

Note

Real AI Development Workflow - Watch Claude Sonnet 4 leverage the bridge to understand requirements, manage tasks, and write code.

AI Agent Development Example

The agent uses MCP tools to orchestrate complex development workflows through a single, unified interface.

For a complete history of testing, including the upgraded communication system and the headless browser tool, see agents-full.pdf.


🤝 Contributing

We welcome contributions! Here's how to get involved:

🔄 Contribution Workflow

  1. 🍴 Fork the repository
  2. 🌿 Branch your feature (git checkout -b feature/AmazingFeature)
  3. 💾 Commit your changes (git commit -m 'Add AmazingFeature')
  4. 🚀 Push to branch (git push origin feature/AmazingFeature)
  5. 📬 Open a Pull Request

💡 What We're Looking For

  • 🔧 New tool integrations
  • 📚 Documentation improvements
  • 🐛 Bug fixes and optimizations
  • 🎨 UI/UX enhancements

📜 License

MIT License - See LICENSE for details


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