Agent Comms
Cross-harness communication mesh for LLM agents — rooms, DMs, presence, and visibility over TCP
What is Agent Comms?
Agent Comms is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to cross-harness communication mesh for llm agents — rooms, dms, presence, and visibility over tcp
Cross-harness communication mesh for LLM agents — rooms, DMs, presence, and visibility over TCP
This server falls under the Communication category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- Cross-harness communication mesh for LLM agents — rooms, DMs
Use Cases
Maintainer
Works with
Installation
NPM
npx -y agent-commsManual Installation
npx -y agent-commsConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
Frequently Asked Questions about Agent Comms
What is Agent Comms?
Agent Comms is a Model Context Protocol (MCP) server that cross-harness communication mesh for llm agents — rooms, dms, presence, and visibility over tcp It connects AI assistants to external tools and data sources through a standardized interface.
How do I install Agent Comms?
Install via npm with the command: npx -y agent-comms. Then add the server configuration to your AI client's JSON config file (e.g., claude_desktop_config.json or .cursor/mcp.json).
Which AI clients work with Agent Comms?
Agent Comms works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is Agent Comms free to use?
Yes, Agent Comms is open source and available under the MIT license. You can use it freely in both personal and commercial projects.
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Browse More Communication MCP Servers
Explore all communication servers available in the MCPgee directory. Each server includes setup guides for Claude, Cursor, and VS Code.
Set Up Agent Comms in Your Editor
Choose your AI client for step-by-step setup instructions.
Quick Config Preview
Add this to your claude_desktop_config.json or .cursor/mcp.json
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