Console Automation

Console Automation

Production-ready MCP server enabling AI to control and monitor console applications.

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Overview

Production-ready MCP server enabling AI assistants to fully interact with terminal-based applications, monitor outputs, detect errors, and automate workflows across local and remote environments. It supports up to 50 concurrent sessions across local shells (cmd, PowerShell, pwsh, Bash, Zsh, Sh) and SSH, with password and key-based authentication, profiles, and cloud/container integration. The server provides real-time output monitoring, regex-assisted filtering, pattern-based search, and streaming for long-running processes. Built-in automatic error detection covers language traces and generic failures. A test automation framework offers assertions, output validation, exit-code checks, and session snapshots. Background jobs run asynchronously with a priority queue, progress tracking, cancellation, and complete results retrieval, plus cleanup of finished jobs. Profile management stores SSH/app connections, environment variables, and working directories for quick reuse. Advanced output processing enables time-based filtering, multi-pattern searches, and pagination. Enterprise monitoring dashboards provide system and session metrics, alerting, and diagnostics. The architecture uses node-pty, MCP SDK, TypeScript, and Winston for cross-platform compatibility with no native compilation.

Details

Owner
ooples
Language
TypeScript
License
MIT License
Updated
2025-12-07

Features

Full Terminal Control

Create and manage up to 50 concurrent console sessions across local and SSH connections, enabling comprehensive terminal automation.

Multi-Protocol & SSH Remote Connections

Supports local shells (cmd, PowerShell, pwsh, bash, zsh, sh) and remote SSH connections with password and key-based authentication, plus connection profiles and cloud/container integration.

Real-time Output Monitoring & Advanced Search

Capture, filter, and analyze console output in real time, with regex filtering and multi-pattern search.

Streaming & Long-Running Processes

Efficient streaming for long-running processes with pattern matching to detect events.

Automatic Error Detection

Built-in patterns to detect errors, exceptions, stack traces, and other failure indicators across languages.

Test Automation Framework

Built-in assertions, output validation, exit-code checks, and state snapshots for robust testing workflows.

Background Job Execution

Async command execution with priority queue, job monitoring, control (cancel/pause/resume), and complete result retrieval.

Profile & Environment Management

Profile management of connections (SSH, Docker, WSL, cloud), application configurations, environment variables, and working directories with quick connect.

Audience

AI developersLeverage MCP to control, monitor, and automate console applications via AI assistants.

Tags

MCPConsole automationAI-driven automationTerminalSSHRemote connectionsSession managementMonitoringBackground jobsTest automationOutput processingCross-platform