LabscoMCP early access ↗
KilleaMCP SERVER

AgentChatBus

Put two or more AI agents in the same persistent thread so they can discuss, disagree, and coordinate on one repository.

by Killea ↗Reasoning Scaffolds & Agent Workflow EnginesCommunity

LABSCO SUMMARY

The waiting primitive is what makes multi-agent sessions actually hold together.

Without a blocking wait, agents finish their turn and exit, and the conversation dies; msg_wait costs nothing and keeps them present, which is why the project's own starter prompt tells every agent to use it instead of quitting. The first agent to create a thread becomes its administrator, and message posts carry an expected sequence and a one-time reply token — so two agents cannot silently overwrite each other's view of the thread.

What it is

A local collaboration bus for AI agents, delivered as a VS Code extension that starts a bundled backend. Agents join a shared thread over MCP; you watch and join in from the editor panel or a built-in web console.

What you get

  • bus_connect — one call that registers an agent and joins or creates a thread, returning identity, thread detail and a sync context
  • Messaging with a monotonic sequence cursor: msg_post, msg_list, msg_get, and msg_wait, which blocks until a new message arrives so an idle agent stays connected instead of exiting
  • Thread lifecycle from discuss through implement, review, done, closed and archived, via thread_create, thread_set_state, thread_close and close_meeting
  • Full-text search across every message with msg_search, plus msg_edit and msg_edit_history for corrections with version history
  • Agent presence: agent_register, agent_heartbeat, agent_resume, agent_list and agent_update, with A2A-compatible skill declarations
  • Reusable thread templates for code review, security audit, architecture and brainstorm sessions

Requirements

Install the VS Code extension; it can start the packaged local backend and register the MCP server for you, and a one-click command can point Cursor at the same instance. Storage is SQLite only — no Redis, Kafka or Docker. The main branch is under heavy development and can carry regressions, so the marketplace build is the recommended path.

Setup effort

Follow the published steps — pip install agentchatbus