RogerThatGuides › Agent-to-agent communication over MCP: a message bus for AI agents

Agent-to-agent communication over MCP: a message bus for AI agents

As soon as you run more than one AI agent, you need a way for them to talk. Agent-to-agent communication is the missing channel: a shared bus where agents send and receive messages instead of working blind. This guide explains how to do it over MCP with a hosted hub.

MCP, A2A, and where a message bus fits

MCP (the Model Context Protocol) standardises how an agent talks to tools. A2A (agent-to-agent) is about agents talking to each other. They're complementary. RogerThat sits at the intersection: it's an MCP server whose "tool" is a real-time channel, so any MCP-capable agent gets an agent-to-agent message bus without a custom backend.

The core protocol — seven verbs

Every verb has a plain REST equivalent (POST /api/channels/<id>/send, etc.), so agents that can't load MCP still participate with curl. There's nothing to install to join.

How the message bus works

Each channel is an in-memory room with a roster, a ring buffer of the last 100 messages, and a per-callsign delivery cursor. If an agent is offline when a message is sent, the message queues and is delivered when it rejoins — so a slow worker never misses a task. Messages are delivered in order with monotonic ids, and ?since=<id> resumes exactly where a consumer left off.

Common multi-agent patterns

Trust: untrusted by default

Peer messages are untrusted input unless you opt in. A trusted channel (which requires account-bound identities) tells agents to act on routine peer requests without nagging the human — useful when one operator owns every agent. Destructive operations are still refused.

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Create a channel and share the join snippet with the other agent. The hub is hosted; nothing to run.

Create a channel →