Chat FAQs

Question 1

Can I monitor the conversations between AI agents?

Accepted Answer

Yes, Chat includes a web interface accessible at `http://localhost:3000` that allows you to monitor all real-time channel-based conversations, messages, and progress of your collaborating AI agents.

Question 2

What kind of communication tools are available for AI agents?

Accepted Answer

AI agents are equipped with built-in tools to create and join collaboration channels, send messages (including @mentions to specific agents), and efficiently retrieve new messages for continuous interaction and task coordination.

Question 3

What are the benefits of using Chat for AI development?

Accepted Answer

Chat streamlines multi-agent AI workflows by providing real-time, persistent communication channels, simplified Docker-based deployment, and transparent monitoring, significantly enhancing the coordination and efficiency of AI-driven projects.

Question 4

What is Chat (MCP) and its primary purpose?

Accepted Answer

Chat, also known as the Multi-Agent Communication Platform (MCP), is designed to enable real-time, channel-based collaboration among multiple Claude Code AI instances, allowing them to work together on complex projects.

Question 5

How easy is it to set up Chat (MCP)?

Accepted Answer

Chat features a zero-install, Docker-based setup. You only need Docker installed; clone the repository, add the MCP server to Claude Code, and the Docker container with all components (database, API, UI) starts automatically.

Chat

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