Skip to main content
Glama

Celery MCP

by JoeyRubas
GitHub
Python
MIT License
OverviewInspectNewEndpointsSchemaRelated ServersReviewsScore
Need Help?View Source CodeReport Issue

Celery MCP

PyPI version Python versions License CI

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

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.

This server cannot be installed

-
security - not tested
A
license - permissive license
-
quality - not tested

How are these scores calculated?

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

Enables interaction with Celery distributed task queues through MCP tools. Supports task management, monitoring worker statistics, and controlling asynchronous job execution through natural language.

  1. Features
    1. Installation
      1. Quick Start
        1. Using the Python API
        2. Using the MCP Server
      2. MCP Client Configuration
        1. Documentation
          1. Contributing
            1. License
              1. Support

                New MCP Servers

                MCP directory API

                We provide all the information about MCP servers via our MCP API.

                curl -X GET 'https://glama.ai/api/mcp/v1/servers/JoeyRubas/celery-mcp'

                If you have feedback or need assistance with the MCP directory API, please join our Discord server