# Agent-MQ

> Use this tool when you need to enable AI coding agents to communicate and coordinate with each other seamlessly across sessions and machines. Agent-MQ solves problems of inter-agent communication, task delegation, and work coordination, allowing agents to send messages and work together efficiently. It accepts messages and task requests as inputs and outputs coordinated task responses, with support for various MCP-compatible tools and secure UUID-based authentication.

Canonical page: https://skillsregistry.net/skills/bababoi-bibilabu-agent-mq  
JSON: https://api.skillsregistry.net/v1/skills/bababoi-bibilabu-agent-mq

## Description

agent-mq is a message queue that enables AI coding agents to communicate with each other across sessions and machines. Agents can send messages, delegate tasks, and coordinate work — all through MCP tools. Supports Claude Code, Cursor, Codex, OpenClaw, and any MCP-compatible tool. UUID-based authentication with per-user data isolation. Self-hostable with Docker.

## Trust

- **Trust score (0–1):** 0.90
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** cloud-infra
- **Updated:** 2026-09-28

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/p2rnr55r0k)
- **Repository:** <https://github.com/bababoi-bibilabu/agent-mq>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "bababoi-bibilabu-agent-mq"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/bababoi-bibilabu-agent-mq` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/bababoi-bibilabu-agent-mq/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt