What is Ai Devcollab Mcp

AI-DevCollab-MCP is a tool designed for front-end/back-end separated projects, enabling direct communication between AI agents to collaboratively solve development scenarios.

Use cases

Use cases include collaborative problem-solving in development scenarios, task handoffs between AI agents, and simulating realistic team communication workflows.

How to use

To use AI-DevCollab-MCP, download the client and server files, start the server with socket_server.py, and run socket_mcp.py in your IDE. Connect to the server at localhost:8888 and set the AI identity before starting role-based conversations.

Key features

Key features include connection management, identity management, and message interaction capabilities such as sending targeted messages, receiving replies, and managing message history.

Where to use

AI-DevCollab-MCP can be used in software development environments where front-end and back-end teams need to collaborate efficiently, particularly in architecture-separated projects.

AI-DevCollab-MCP

• This is an MCP-based tool designed specifically for front-end/back-end separated projects. When you’re unable to clearly describe development scenarios, this system enables direct conversations between AI agents to collaboratively solve the issue.
• The system is built on socket communication, providing a real-time messaging interface for multiple AI instances. It supports identity management, message exchange, and synchronous replies—simulating realistic development team communication workflows.
• Architecture-separated projects can all use this MCP to handle task handoffs.

Quick Start

Installation & Startup

1. Download both the client and server files.
2. Start the server: run socket_server.py
   • You can manage the server using server_admin.py
3. Inside your IDE: run python socket_mcp.py
4. Please prompt AI: Connect to the server localhost:8888
5. Please prompt AI: Set the AI identity (e.g., “Front-End Developer”, “Back-End Developer”, “UI Designer”)
6. Begin role-based conversations

Core Features

Connection Management

• link_server - Connect to the specified server (param: server address:post)
• test_connection - Test current connection status and latency
• connection_status - Get detailed connection information
• disconnect - Disconnect from the server

Identity Management

• set_identity - Set the current AI’s developer role identity
• list_identities - List all currently online identities

Message Interaction

• send_message - Send a message, with optional synchronous reply waiting
  • Supports targeted messages and broadcasting
  • Supports blocking until a reply is received
  • Timeout and max reply count can be configured
  • Supports message referencing and reply chaining
• get_messages - Retrieve the message history
• get_pending_replies - Get messages awaiting replies

Use Cases

• API Design Discussion: Front-end AI consults with back-end AI on API specifications and data structures
• Data Flow Confirmation: Back-end AI verifies data handling logic with front-end AI
• UI/UX Coordination: Design AI collaborates with development AI on interface implementation details
• Cross-Role Requirement Alignment: Quickly resolve misunderstandings between different roles

IDE & Claude

• This configuration is for only Windows

{
  "mcpServers": {
    "AI-DevCollab-MCP": {
      "command": "cmd",
      "args": [
        "/c",
        "python",
        "socket_mcp.py"
      ]
    }
  }
}

Demo Video Link

• 【AI-DevCollab-MCP】

Updates

• 2025.05.04 — Version 0.1: Debugging code still present; updates pending