Celery MCP

A Python library that provides a connector to use Celery distributed task queues over the Model Context Protocol (MCP).

Features

• Seamless integration of Celery with MCP

• Easy-to-use API for task management

• Support for asynchronous task execution

• MCP server with tools for LLM interaction

• Comprehensive documentation and examples

Related MCP server: Clickup Universal MCP Server

Installation

Install from PyPI:

pip install celery-mcp

Or install from source:

git clone https://github.com/yourusername/celery-mcp.git
cd celery-mcp
pip install -e .

Quick Start

Using the Python API

from celery_mcp import CeleryMCP

# Initialize the connector
mcp = CeleryMCP(broker_url='redis://localhost:6379/0')

# Send a task
result = mcp.send_task('my_app.add', args=[4, 4])
print(result.get())  # 8

Using the MCP Server

The package includes an MCP server that exposes Celery functionality as tools that can be used by LLMs:

# Start the MCP server
celery-mcp-server

Available MCP Tools

1. initialize_celery_connection - Initialize connection to Celery broker

2. list_registered_tasks - List all registered task names

3. send_task - Send a task to the Celery queue

4. get_task_status - Get the status of a Celery task

5. get_active_tasks - Get information about active (running) tasks

6. get_scheduled_tasks - Get information about scheduled tasks

7. revoke_task - Revoke (cancel) a task

8. get_worker_stats - Get statistics about Celery workers

MCP Client Configuration

To use the MCP server with Claude Desktop, add this to your claude_desktop_config.json:

{
  "mcpServers": {
    "celery-mcp": {
      "command": "celery-mcp-server"
    }
  }
}

Documentation

Full documentation is available at https://celery-mcp.readthedocs.io/.

Contributing

We welcome contributions! Please see our Contributing Guide for details.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support

If you have any questions or issues, please open an issue on GitHub.