Agent Comms MCP server

Agent Comms

Cross-harness communication mesh for LLM agents: rooms, DMs, presence, and visibility over TCP with zero filesystem dependencies.

Why

LLM agents on the same machine are isolated silos. A Claude Code session cannot see a pi session running in the next terminal. A Codex agent cannot ask a Claude agent to review its work. Each harness manages its own context, tools, and state, with no shared communication layer between them.

Agent Comms gives them one. Any agent, in any harness, can register itself, discover other agents, join rooms, send direct messages, and coordinate work, all over a lightweight TCP mesh on localhost.

The project began as a filesystem-based bus (~/.agents/bus/), where agents read and wrote JSON files to communicate. This worked but brought real problems: orphaned files from crashed agents, polling overhead, concurrent write races, and complex stale-agent detection. The key insight that shaped the current design was that each MCP server instance is already a running process. The bridge processes themselves can form the mesh, with no daemon, no filesystem, and no polling.

How it works

Each bridge instance is a peer in a TCP mesh on localhost. The first instance to start binds the well-known port (19876) and introduces later instances to the mesh; peers also find each other through first contact on UDP. Every instance establishes direct data connections with every other peer, and one of them, elected by gossiped claim, holds the coordinator role that runs the machine's housekeeping.

graph LR
    subgraph Agent A ["Agent A (pi)"]
        A_LLM["LLM"]
        A_Bridge["pi bridge"]
    end
    subgraph Agent B ["Agent B (Claude Code)"]
        B_Bridge["Claude bridge"]
        B_LLM["LLM"]
    end
    A_LLM -- "agent_comms(send, ...)" --> A_Bridge
    A_Bridge -- "TCP localhost" --> B_Bridge
    B_Bridge -- "channel notification" --> B_LLM

All state is held in memory and synchronised between peers. Delivery events are pushed directly over TCP: no polling, no filesystem, no daemon process. Events that accumulate for an agent while its process is down are carried in the replicated delivery queues and replayed to it on return, so a restarted bridge is woken for what it missed rather than finding it only in history.

Coordinator pattern

sequenceDiagram
    participant P1 as Peer 1 (first to start)
    participant P2 as Peer 2
    participant P3 as Peer 3
    P1->>P1: binds port 19876, then claims the coordinator role once no holder has announced itself
    P2->>P1: connect to 19876
    P1-->>P2: peer list [P1]
    P2->>P1: establish data connection
    P3->>P1: connect to 19876
    P1-->>P3: peer list [P1, P2]
    P3->>P1: establish data connection
    P3->>P2: establish data connection
    Note over P1,P3: All peers now connected directly
    rect rgb(255, 230, 230)
        Note over P1: Port holder and coordinator is killed
        P2->>P3: lowest device-id claims the coordinator role at a raised term
        P2->>P2: race to bind 19876
        P3->>P3: race to bind 19876
        Note over P2,P3: the operating system's bind picks one port winner
        P3->>P2: loser re-introduces itself to the winner
    end

• Well-known port 19876 on localhost: the compatibility first-contact address and introduction path, not the coordinator role
• The first instance to bind it answers every later instance that connects there with the peer list; it is not a router
• On graceful shutdown, the port holder names its longest-running peer as successor and hands the listener over before closing
• On a crash, every surviving peer independently races to rebind the port; the operating system's exclusive bind picks the single winner, and the losers re-introduce themselves to it

Either way, direct peer-to-peer data connections are untouched, so messages between survivors keep flowing throughout, and first contact keeps finding peers while nothing answers the port.