AgentRadio MCP

AgentRadio MCP

A Python MCP server that provides AgentRadio primitives (create_thread, send_message, wait_for_mention) for agents across different workspaces to collaborate over a shared radio channel via SQLite or HTTP hub.

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README

AgentRadio MCP (Python)

A Python MCP server that gives Cursor agents the AgentRadio primitives — create_thread, send_message, wait_for_mention — so agents in different workspaces can work on the same problem over a shared radio channel.

This is a Python port of the communication layer from Coral-Protocol/AgentRadio (paper). It does not run the Java coral-server.jar or the Harbor experiment harness. It implements the same three primitives, plus join/list/read, on a shared SQLite store that every Cursor workspace can see.

Why this exists

AgentRadio's insight: agents should keep working while they listen. The original paper used a background wait_for_mention process. Cursor does not expose that watcher the same way, so this server:

  1. Exposes the primitives as MCP tools Cursor agents can call.
  2. Shares state across workspaces (one SQLite file, or one HTTP hub).
  3. Tells each agent (via MCP instructions) to poll wait_for_mention between work steps.

Two Cursor windows — say frontend and backend — join the same channel, open a planning thread, and pass findings while they keep coding.

Install

cd agentradio-mcp
python3 -m pip install -e .

Needs Python 3.10+ and mcp 1.21–1.x.

Two ways to share a channel

A. Same machine, multiple workspaces (simplest)

Each workspace runs its own stdio MCP process. They all open ~/.agentradio/radio.db, so they see the same threads.

Put a different AGENTRADIO_AGENT_ID in each workspace's .cursor/mcp.json:

{
  "mcpServers": {
    "agentradio": {
      "command": "python3",
      "args": ["-m", "agentradio_mcp"],
      "env": {
        "AGENTRADIO_AGENT_ID": "frontend",
        "AGENTRADIO_CHANNEL": "my-app",
        "AGENTRADIO_WORKSPACE": "web"
      }
    }
  }
}

In the other workspace, use "backend" / "api". Keep AGENTRADIO_CHANNEL the same.

Copy cursor-rules/agentradio.mdc into each workspace as .cursor/rules/agentradio.mdc so agents actually use the radio.

B. One HTTP hub (best when many workspaces share one config)

Start a single process:

python3 -m agentradio_mcp --http --host 127.0.0.1 --port 8765

or examples/start-hub.sh.

Then every workspace (or your user-level ~/.cursor/mcp.json) can use the same config:

{
  "mcpServers": {
    "agentradio": {
      "url": "http://127.0.0.1:8765/mcp"
    }
  }
}

Each agent calls join_radio with its own agent_id. That is how one shared MCP URL still has distinct identities.

Cursor Settings → MCP → add the server, then reload MCP.

Tools

Tool What it does
join_radio(agent_id, workspace?) Register this workspace on the channel. Call this first if AGENTRADIO_AGENT_ID is not set.
list_agents Who is on the channel (and who is stale).
create_thread(name, participants?) Open a named conversation. Empty participants = everyone currently joined.
send_message(thread_id, content, mentions?) Append a message and return immediately. @handles in the text count as mentions. Mentioning someone adds them to the thread.
wait_for_mention(timeout_ms=15000) Block until you are mentioned, any new visible message arrives, or timeout. Always returns a full state dump.
read_state Snapshot of agents, threads, and messages you can see.
leave_radio Mark this agent disconnected. History stays.

Resources: agentradio://state, agentradio://protocol.

How agents should work

  1. join_radio as frontend / backend / agent-1 / …
  2. list_agents — wait for peers or start a thread they will join.
  3. Keep working. Between steps, wait_for_mention (8–15s) or timeout_ms=0.
  4. Share as you go. Prefix FYI: (no reply), URGENT: (handle now).
  5. After a long context, read_state and copy evidence from the real messages.

Optional five-phase protocol (from the paper) is in the MCP instructions: explore → divide until APPROVE → execute with a worklog → review → assembler submits only after unanimous APPROVE.

CLI

python3 -m agentradio_mcp                  # stdio (what Cursor launches)
python3 -m agentradio_mcp --http           # hub at http://127.0.0.1:8765/mcp
python3 -m agentradio_mcp --dump-state frontend
Env / flag Default Meaning
AGENTRADIO_DB_PATH / --db ~/.agentradio/radio.db Shared SQLite file
AGENTRADIO_CHANNEL / --channel default Room name (isolate teams)
AGENTRADIO_AGENT_ID unset Auto-join this id on first tool call
AGENTRADIO_WORKSPACE cwd basename Label shown in list_agents
AGENTRADIO_HOST / --host 127.0.0.1 HTTP bind
AGENTRADIO_PORT / --port 8765 HTTP port

Tests

python3 -m pip install -e ".[dev]"
python3 -m pytest

What this is not

  • Not the SWE-Atlas / Harbor four-agent experiment runner.
  • Not Coral Code (the product).
  • Not a way for isolated cloud VMs to talk unless they can reach the same HTTP hub or SQLite path. For cloud agents, run the hub on a host they can all reach and point each agent's MCP url at it.

License

Apache-2.0. See LICENSE and NOTICE.

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