What is SupervisordMCP?

SupervisordMCP is a process management tool with built-in Model Context Protocol (MCP) support, enabling AI agents to manage local development processes. It runs on any operating system with Python 3.10 or higher and provides a command-line interface for adding, starting, stopping, and monitoring processes.

How to use SupervisordMCP?

Install with uv add supervisord-mcp (or pip install supervisord-mcp). Start the daemon with uv run supervisord-mcp start-daemon, then add a process (e.g., uv run supervisord-mcp add webapp "python app.py"), and start it. Use overview, logs, status-all for monitoring. For AI integration, run uv run supervisord-mcp mcp and configure the client with the provided JSON.

Key features of SupervisordMCP

- Process management with intelligent state handling (ensure-started/stopped)
- Bulk operations: start-all, stop-all, restart-all
- Comprehensive monitoring with overview and status commands
- Real-time log viewing with filtering by stream and line count
- Built-in MCP protocol support for AI agent automation
- Cross-platform: works on Linux, macOS, and Windows
- Lightweight alternative to Docker Compose and systemd

FAQ from SupervisordMCP

How does SupervisordMCP compare to Docker Compose or systemd?

SupervisordMCP is lighter (no containers), faster (direct process execution), simpler (one command), cross-platform, and includes built-in MCP support for AI automation, unlike Docker Compose or systemd.

What platforms and Python versions are supported?

Any operating system (Linux, macOS, Windows) with Python 3.10 or higher.

Does SupervisordMCP support MCP for AI agents?

Yes. It provides an MCP server via uv run supervisord-mcp mcp using the stdio transport method, designed for local development environments.

What is the licensing for SupervisordMCP?

It is released under the MIT License.

Are there any known limitations?

SupervisordMCP is intended for local development environments only and uses the stdio transport method as specified in the MCP documentation. It is not designed for remote or production deployment.

Quick Start Installation uv add supervisord-mcp Basic Usage

Start the daemon

uv run supervisord-mcp start-daemon

Add and start a web application

uv run supervisord-mcp add webapp "python app.py" uv run supervisord-mcp start webapp

Check what's running

uv run supervisord-mcp overview

View logs

uv run supervisord-mcp logs webapp That's it! Your process is now managed by Supervisord MCP.

Key Features 🚀 Process Management Made Easy

Add processes with options

uv run supervisord-mcp add api "uvicorn app:api" --numprocesses 4 --working-dir /app

Smart operations (won't fail if already running)

uv run supervisord-mcp ensure-started api

Bulk operations

uv run supervisord-mcp start-all uv run supervisord-mcp restart-all 📊 Comprehensive Monitoring

Beautiful overview of all services

uv run supervisord-mcp overview

Detailed status information

uv run supervisord-mcp status-all

Real-time log viewing

uv run supervisord-mcp tail api uv run supervisord-mcp logs-all 🤖 AI Agent Integration Supervisord MCP includes built-in MCP protocol support, allowing AI agents to manage your processes:

Start MCP server for AI integration

uv run supervisord-mcp mcp Configure in your AI agent using the recommended stdio transport:

{ "mcpServers": { "supervisord-mcp": { "command": "uv", "args": ["run", "supervisord-mcp", "mcp"] } } } Note: This tool is designed for local development environments using MCP's stdio transport method as specified in the MCP documentation. This approach provides secure, direct communication between AI agents and the process manager.

Common Use Cases Web Application Management

Production web app with multiple workers

uv run supervisord-mcp add webapp "gunicorn app:application" --numprocesses 4 uv run supervisord-mcp add worker "celery worker -A app" --numprocesses 2 uv run supervisord-mcp ensure-started all Development Environment

Start your development stack

uv run supervisord-mcp add frontend "npm run dev" --working-dir /app/frontend uv run supervisord-mcp add backend "python manage.py runserver" --working-dir /app/backend uv run supervisord-mcp add redis "redis-server" uv run supervisord-mcp start-all Microservices

Manage multiple services

uv run supervisord-mcp add auth-service "python auth_service.py" uv run supervisord-mcp add user-service "python user_service.py" uv run supervisord-mcp add notification-service "python notification_service.py" uv run supervisord-mcp ensure-started all Why Supervisord MCP? vs. Docker Compose Lighter: No containers needed, just process management Faster: Direct process execution, no container overhead Simpler: One command to rule them all vs. systemd User-friendly: Simple commands instead of unit files Cross-platform: Works on any system with Python AI-ready: Built-in MCP support for automation vs. PM2 Python-native: Perfect for Python applications AI integration: MCP protocol support out of the box Comprehensive: Process + log management in one tool Advanced Features Intelligent State Management

These commands are safe to run multiple times

uv run supervisord-mcp ensure-started webapp # Only starts if not running uv run supervisord-mcp ensure-stopped worker # Only stops if running Bulk Operations

Work with all processes at once

uv run supervisord-mcp start-all # Start everything uv run supervisord-mcp stop-all # Stop everything uv run supervisord-mcp restart-all # Restart everything uv run supervisord-mcp logs-all # See all logs Log Management

View logs with filtering

uv run supervisord-mcp logs webapp --lines 100 --stream stderr uv run supervisord-mcp tail webapp --stream stdout

See recent activity across all services

uv run supervisord-mcp logs-all Installation & Setup System Requirements Python 3.10 or higher Any operating system (Linux, macOS, Windows) Installation Options

From PyPI (recommended)

uv add supervisord-mcp

With pip (alternative)

pip install supervisord-mcp

From source

git clone https://github.com/aether-platform/supervisord-mcp.git cd supervisord-mcp uv sync Verify Installation uv run supervisord-mcp --help uv run supervisord-mcp daemon-status Configuration Supervisord MCP works out of the box with sensible defaults. For advanced usage:

Custom Supervisord Configuration

Use your own Supervisord.ini

uv run supervisord-mcp start-daemon -c /path/to/your/Supervisord.ini Process Configuration

Add processes with full configuration

uv run supervisord-mcp add myapp "python app.py" --numprocesses 4 --working-dir /app Getting Help Documentation Development Guide - For contributors and advanced usage API Reference - Complete command and API documentation Support GitHub Issues: Report bugs or request features Discussions: Join the community Releases: Latest releases and changelogs Quick Command Reference

Daemon

uv run supervisord-mcp start-daemon uv run supervisord-mcp stop-daemon uv run supervisord-mcp daemon-status

Process Management

uv run supervisord-mcp add uv run supervisord-mcp start/stop/restart uv run supervisord-mcp ensure-started/ensure-stopped

Monitoring

uv run supervisord-mcp overview uv run supervisord-mcp status-all uv run supervisord-mcp logs

AI Integration

uv run supervisord-mcp mcp

Examples Repository Check out our examples repository for real-world usage patterns:

Django + Celery setup FastAPI microservices React + Node.js development stack Machine learning pipeline management License MIT License - see LICENSE for details.

About the Author AetherPlatform - Building the future of cloud-native development tools

GitHub: @aether-platform Project Website: AetherPlatform Contact: aether-platform@re-x.info Our Mission We develop tools that enhance developer productivity through AI integration and modern cloud-native technologies. SupervisordMCP is part of our broader ecosystem of development tools designed to streamline the software development lifecycle.

Acknowledgments We extend our heartfelt gratitude to the Supervisord development team for creating such a robust and reliable process management foundation. Their excellent work made this project possible. Supervisord MCP builds upon their solid architecture to bring modern AI agent integration to process management.

Related Projects Supervisord - The underlying process manager (Thank you to the Supervisord team!) Model Context Protocol - AI agent communication standard AetherPlatform - Cloud-native development tools Made with ❤️ by AetherPlatform

Supervisord MCP: Simple process management, powerful automation.

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