[Claude Code] Team Agent Communication Architecture

Sat, 28 Feb 2026 14:07:38 +0900

Claude Code Team Agent Communication Architecture Design

Overview

When multiple AI agents collaborate in Claude Code, an efficient communication method is needed. This article shares the communication architecture designed while building a Discord-integrated server monitoring team.

Problem Definition

Claude Code has two types of agents:

Python Processes (Daemon)
- Discord Gateway, user_comm_daemon, etc.
- Always running, filesystem access available
LLM Agents (Created as Tasks)
- gcp-monitor, oci-monitor, alert-manager, etc.
- Use SendMessage tool, Claude Code native communication

Communication between these two types was needed.

Considered Approaches

1. File-based Message Queue (Existing)

Pros: Simple implementation, no dependencies
Cons: Latency (~1s), file management required

2. WebSocket

Pros: Real-time bidirectional communication
Cons: Server/client implementation required

3. gRPC

Pros: Strong type checking, streaming
Cons: proto file management, high complexity

4. SQLite Message Hub (Adopted)

Pros: Fast (~10ms), transactions, no additional dependencies
Cons: Works only on a single machine

Final Architecture

┌─────────────────────────────────────────────────────────────────┐
│ SQLite Message Hub (messages.db) │
│ ~/.claude/teams/{team}/messages.db │
└───────────────────────────┬─────────────────────────────────────┘
 │
 ┌───────────────────┼───────────────────┐
 ↓ ↓ ↓
┌──────────────┐ ┌──────────────┐ ┌──────────────┐
│ Discord │ │ Python │ │ LLM │
│ Gateway │ │ Daemon │ │ Agent │
│ (Direct Access)│ │ (Direct Access)│ │ (MCP Tool) │
└──────────────┘ └──────────────┘ └──────────────┘

SQLite Message Hub Structure

Messages Table

CREATE TABLE messages (
 id INTEGER PRIMARY KEY AUTOINCREMENT,
 message_id TEXT UNIQUE NOT NULL,
 sender TEXT NOT NULL,
 recipient TEXT, -- NULL = broadcast
 message_type TEXT DEFAULT 'message',
 content TEXT NOT NULL,
 priority TEXT DEFAULT 'normal',
 metadata TEXT DEFAULT '{}',
 status TEXT DEFAULT 'pending',
 created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
 processed_at TIMESTAMP,
 expires_at TIMESTAMP
);

Agent Status Table

CREATE TABLE agent_status (
 agent_name TEXT PRIMARY KEY,
 status TEXT DEFAULT 'offline',
 last_heartbeat TIMESTAMP,
 metadata TEXT DEFAULT '{}'
);

Communication Methods

LLM Agent ↔ LLM Agent

Use SendMessage (Claude Code native)
Auto-managed, idle notification provided

Python ↔ LLM Agent

SQLite Hub + MCP Tool
Python accesses SQLite directly
LLM Agent accesses via MCP Tool

MCP Server Implementation

MCP tools for LLM Agents:

@server.list_tools()
async def list_tools():
 return [
 Tool(name="team_send_message", ...),
 Tool(name="team_read_messages", ...),
 Tool(name="team_broadcast", ...),
 Tool(name="team_get_status", ...),
 Tool(name="team_update_status", ...),
 ]

Message Flow Example

1. Discord user: "Hello"
 ↓
2. Discord Gateway → SQLite: INSERT message
 ↓
3. user_comm Daemon → SQLite: SELECT pending
 ↓
4. user_comm → SQLite: INSERT response
 ↓
5. Discord Gateway → SQLite: SELECT response
 ↓
6. Discord channel: "Hi there! 👋"

Performance Comparison

Method	Latency	Stability	Complexity
File-based	~1000ms	Medium	Low
WebSocket	~5ms	High	Medium
SQLite	~10ms	High	Low

Conclusion

The SQLite Message Hub + MCP Server combination was most suitable for Claude Code team agent communication:

Low Latency: 100x faster than file-based
Stability: Data integrity guaranteed through transactions
Simplicity: Uses Python’s built-in sqlite3 without additional dependencies
Flexibility: Both Python and LLM Agents use the same data source

Code

Core components:

message_hub.py: SQLite Message Hub
team_comm_mcp_server.py: MCP Server
discord_gateway.py: Discord integration gateway
user_comm_daemon.py: Message processing daemon

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