Claude Code MCP Async Server

Asynchronous MCP wrapper for Claude Code CLI

Enable Claude Code to spawn child Claude Code sessions for parallel task execution.

Features

• ✅ Async execution - Start tasks in background, continue working
• ✅ Multi-instance parallelism - Run multiple Claude Code sessions simultaneously
• ✅ Automatic cleanup - No zombie processes
• ✅ Zero config - Works out of the box

Quick Start

1. Install

git clone https://github.com/jeanchristophe13v/claudecode-mcp-async.git
cd claudecode-mcp-async
chmod +x claudecode_mcp_async_server.py

2. Configure Claude Code

Add to your ~/.claude/settings.json:

{
  "mcpServers": {
    "claude-code-mcp": {
      "command": "/absolute/path/to/claudecode-mcp-async/claudecode_mcp_async_server.py",
      "args": [],
      "env": {}
    }
  }
}

Tip: Use absolute path. Replace /absolute/path/to/ with your actual path.

3. Restart Claude Code

Reload or restart Claude Code to load the MCP server.

Usage

Example: Async execution (recommended)

The key advantage is non-blocking execution - start a task and continue working immediately.

# Start a long-running task in background
task = claude_code_execute_async(
    prompt="Analyze all Python files and generate a comprehensive report",
    working_dir="/path/to/project",
    skip_permissions=True
)
# ✅ Returns immediately with Task ID: abc12345

# Continue your work while Claude Code runs in background
# ... do other things ...

# Check result when ready
result = claude_code_check_result(task_id="abc12345")

Example: Parallel execution

Run multiple tasks simultaneously:

# Start multiple tasks at once
task1 = claude_code_execute_async(
    prompt="Generate unit tests for utils.py"
)

task2 = claude_code_execute_async(
    prompt="Refactor database.py to use async/await"
)

task3 = claude_code_execute_async(
    prompt="Add type hints to all functions in api.py"
)

# All three tasks run in parallel
# Check results when ready
result1 = claude_code_check_result(task_id=task1)
result2 = claude_code_check_result(task_id=task2)
result3 = claude_code_check_result(task_id=task3)

Example: Synchronous execution

For simple tasks that need immediate results:

result = claude_code_execute(
    prompt="Write a Python function to validate email addresses",
    skip_permissions=True
)
# ⏳ Blocks until completion, then returns result

API Reference

claude_code_execute_async

Start a task in background, return immediately.

Parameters:

• prompt (required): Task description
• working_dir (optional): Working directory
• model (optional): "sonnet", "opus", or "haiku"
• skip_permissions (optional): Skip permission checks (default: true)

Returns: Task ID string

claude_code_check_result

Check async task status.

Parameters:

• task_id (required): Task ID from claude_code_execute_async

Returns:

• running: Task in progress
• completed: Task finished with result

claude_code_execute

Synchronous execution (blocks until completion).

Parameters:

• prompt (required): Task description
• working_dir (optional): Working directory
• model (optional): "sonnet", "opus", or "haiku"
• timeout (optional): Timeout in seconds
• skip_permissions (optional): Skip permission checks (default: true)

Returns: Task result

Why Async?

Problem: Claude Code blocks the parent session while running.

Solution: This MCP server spawns child Claude Code processes that run in the background.

Benefits:

• 🚀 Start a task and continue working immediately
• ⚡ Run multiple tasks in parallel
• 🎯 No blocking, no waiting
• 🧹 Automatic process cleanup

Troubleshooting

Server not showing up?

• Use absolute path in config
• Run: chmod +x claudecode_mcp_async_server.py
• Restart Claude Code

Task stuck in "running"?

• Wait a moment, large tasks take time
• Check: ls -la /tmp/claude_code_tasks/
• View logs: tail -f /tmp/claude_code_mcp_debug.log

Requirements

• Python 3.6+
• Claude Code CLI installed

License

MIT License

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Questions? Open an issue on GitHub.