team-table 0.1.0

Multi-model AI team coordination via MCP — the missing coordination layer for multi-agent, multi-provider AI systems

Team Table

Multi-model AI team coordination via MCP (Model Context Protocol).

An MCP server that lets multiple AI instances discover each other, coordinate tasks, and communicate through a shared SQLite database.

Quick Start

pip install -e ".[dev]"

Register as MCP server in Claude Code

claude mcp add --transport stdio --scope user team-table -- \
  path/to/.venv/Scripts/python.exe -m team_table.server

Network Mode (LAN)

Run the server over the network so other machines can connect:

# Start the server in SSE mode (or use streamable-http)
TEAM_TABLE_TRANSPORT=sse python -m team_table.server

From another PC on the LAN, register the remote server:

claude mcp add --transport sse team-table http://<host-ip>:8741/sse

Environment Variables

Variable	Default	Description
TEAM_TABLE_DB	~/.team-table/team_table.db	Path to the SQLite database
TEAM_TABLE_TRANSPORT	stdio	Transport mode: stdio, sse, or streamable-http
TEAM_TABLE_HOST	0.0.0.0	Bind address for network transports
TEAM_TABLE_PORT	8741	Listen port for network transports

Architecture

Each Claude Code instance spawns its own STDIO MCP server process. All processes share one SQLite database (~/.team-table/team_table.db) using WAL mode for concurrent access. Alternatively, a single server can be run in network mode (SSE or streamable-http) to serve multiple clients over the LAN.

Tools (13)

• Registration: register, deregister, list_members, heartbeat
• Messaging: send_message, get_messages, broadcast
• Task Board: create_task, list_tasks, claim_task, update_task
• Shared Context: share_context, get_shared_context

Poll Daemon (Auto-Messaging)

By default, agents must manually check for messages. The poll daemon automates this — it monitors an agent's inbox and auto-responds, only escalating to the user when needed.

How It Works

1. Polls the database every 30 seconds for unread messages
2. Sends an acknowledgement reply to each incoming message
3. Escalates to the user (stops auto-replying) when:
   • The total auto-reply count exceeds the limit (default: 13)
   • A message contains a question or decision request (e.g. "should we…?", "please approve", "what do you think")
4. Notifies the sender with an [AUTO] message explaining the escalation

Usage

# Start polling for an agent (default: 30s interval, 13 message max)
python scripts/poll_daemon.py claude-opus

# Custom interval and message limit
python scripts/poll_daemon.py claude-opus --interval 15 --max-messages 13

# With a custom database path
TEAM_TABLE_DB=/path/to/db python scripts/poll_daemon.py claude-opus

Safety

• Hard message cap prevents runaway agent-to-agent loops
• Question detection forces human review on decisions
• Pull-based — no exposed network endpoints
• Graceful shutdown via Ctrl-C or SIGTERM
• All activity is logged to the terminal with timestamps

Development

pytest          # run tests
ruff check .    # lint

License

GPL-3.0-or-later